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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Sentinel lymph node &#40;SN&#41; metastasis is currently the most important predictor of survival in patients with melanoma&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Although early dissection of affected lymph nodes has not been proven to improve overall survival&#44;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> it is accepted that knowledge of regional involvement permits a more accurate prognosis and helps in the planning of treatment&#46;<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Breslow thickness and presence of ulceration have been systematically linked to a higher likelihood of SN involvement in melanoma&#46;<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4&#8211;7</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">In recent years&#44; however&#44; mitotic rate has gained increasing recognition as both a prognostic and predictive factor for SN metastasis&#44; particularly since the best method for calculating this rate was established&#46;<a class="elsevierStyleCrossRefs" href="#bib0040"><span class="elsevierStyleSup">8&#8211;11</span></a> Nonetheless&#44; in the latest version of the Cancer Staging Manual of the American Joint Committee on Cancer &#40;AJCC&#41;&#44; mitotic rate is recognized only as a prognostic factor in thin melanomas&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">When taking decisions in medicine&#44; it is important to consider evidence based on sound methods to resolve problems that arise when classifying or stratifying patients or assessing prognosis&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> Decision trees are being increasingly used for this purpose&#44; and one particularly useful tool is classification and regression tree &#40;CART&#41; analysis&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> CART offers several advantages over logistic regression&#46; It is simpler to use and interpret&#44; and furthermore&#44; the fact that it is based on a nonparametric method means that no prior assumptions need to be made regarding the distribution of predictors&#44; the relationships between predictors and outcome&#44; or interactions between predictors&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">The main aim of this study was to identify predictors of SN metastasis in cutaneous melanoma using CART and logistic regression&#46; A secondary goal was to evaluate the role of these factors in predicting disease-free survival and melanoma-specific survival&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Material and Methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">This was a retrospective&#44; observational study&#46;</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study Population</span><p id="par0035" class="elsevierStylePara elsevierViewall">The study participants were selected from the melanoma databases at Hospital Virgen de la Victoria &#40;HVV&#41; in Malaga&#44; Spain and Instituto Valenciano de Oncolog&#237;a &#40;IVO&#41; in Valencia&#44; Spain&#46; All ethical requirements regarding the use of databases were complied with&#46; The 2 databases have been described in detail in previous studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0070"><span class="elsevierStyleSup">14&#8211;16</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">For this particular study&#44; we selected all patients with a single cutaneous melanoma&#44; classified as clinical stage I or II&#44; who had undergone SN biopsy and been prospectively included in the IVO database between January 1&#44; 2000 and December 31&#44; 2012 or in the HVV database between October 1&#44; 2001 and December 31&#44; 2012&#46; Patients without an identifiable SN during the SN biopsy were excluded from the study&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">The study was approved by the ethics committees at the HVV and IVO&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">The dependent variable was SN status&#44; which was classified as positive in the presence of melanoma cells in the SN and negative otherwise&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">SN Status</span><p id="par0055" class="elsevierStylePara elsevierViewall">The methods used for the pathologic examination of the SN are quite similar in both hospitals and are summarized below&#58;</p><p id="par0060" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">HVV</span>&#46; The first step is the gross identification and retrieval of the SN&#44; with clearing of surrounding fat where necessary&#46; The SN is then fixed in formalin 10&#37; prior to embedding in a paraffin block&#46; Each block is serially sectioned into 3 slices every 250<span class="elsevierStyleHsp" style=""></span>&#956;m until the whole block is cut&#46; The first and last sections are used for hematoxylin-eosin staining&#44; while the middle section is used for immunohistochemical staining with HMB-45&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">IVO</span>&#46; The first stage is the same as at the HVV&#58; identification and retrieval of the SN and clearing of fat where necessary&#46; The specimen is also immersed in formalin 10&#37; and embedded in a paraffin block&#46; Serial sections are taken from the entire block every 250<span class="elsevierStyleHsp" style=""></span>&#956;m&#46; Three cross-sections are taken from each section&#46; One is stained with hematoxylin-eosin&#44; and the other 2 are kept for immunohistochemical staining with S-100 protein and HMB-45&#46; The immunohistochemical study is only performed following confirmation of the absence of metastasis in the hematoxylin-eosin section&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Independent Variables</span><p id="par0070" class="elsevierStylePara elsevierViewall">The following clinical and histologic characteristics were selected as independent variables&#58;</p><p id="par0075" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">Clinical characteristics&#46;</span> Patient sex and age &#40;&#8804;<span class="elsevierStyleHsp" style=""></span>65 vs &#62;<span class="elsevierStyleHsp" style=""></span>65 years&#41; and anatomic location of the primary melanoma&#46; Anatomic location was dichotomized into axial &#40;head&#44; neck&#44; trunk&#44; and volar or subungual sites&#41; and extremities&#46; The system proposed by Kruper et al&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> was used to classify volar and subungual melanomas&#44; as these are associated with a worse prognosis &#40;possibly partly due to genetic alterations&#41; that distinguishes them from other types of melanoma&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a></p><p id="par0080" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">Histologic characteristics&#46;</span> Breslow thickness &#40;categorized according to the AJCC as &#8804;<span class="elsevierStyleHsp" style=""></span>1&#46;00&#44; 1&#46;01-2&#44; 2&#46;01-4&#44; and &#62;<span class="elsevierStyleHsp" style=""></span>4<span class="elsevierStyleHsp" style=""></span>mm&#41;&#44; ulceration &#40;present vs absent&#41;&#44; regression &#40;present vs absent&#41;&#44; mitotic rate &#40;0&#44; 1-5&#44; or &#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> and tumor infiltrating lymphocytes &#40;TILs&#41; &#40;absent&#44; nonbrisk&#44; and brisk&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a></p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical Analysis</span><p id="par0085" class="elsevierStylePara elsevierViewall">The dependent variable was SN positivity&#46; Independent variables were included as binary variables &#40;sex&#44; age&#44; ulceration&#44; anatomic location&#44; and regression&#41; or categorical variables &#40;Breslow thickness&#44; TILs&#44; and mitotic rate&#41;&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">In the logistic regression analysis&#44; we first analyzed the association between SN positivity and the study variables using the &#967;<span class="elsevierStyleSup">2</span> test or univariate logistic regression analysis&#46; The Wald test was used to calculate odds ratios with 95&#37; CIs for all variables&#46; Multiple logistic regression was used to identify independent predictors of SN positivity&#46; All possible interactions between variables were also analyzed&#46; Goodness of fit was assessed with the Hosmer-Lemeshow test&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">The classification tree was built using the CART method&#44;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> which is used to build decision trees through a set of rules governing decisions taken to assign an output value to each alternative through a process known as binary recursive partitioning&#46; Each parent note is split into 2 homogeneous child nodes by asking questions with a <span class="elsevierStyleItalic">yes</span> and <span class="elsevierStyleItalic">no</span> answer&#46; The CART process involves several stages&#58; <span class="elsevierStyleItalic">a</span>&#41; tree growing&#59; <span class="elsevierStyleItalic">b</span>&#41; application of stopping rules for the tree-growing process &#40;a maximal tree that overadjusts the data used to generate the tree is built&#41;&#59; <span class="elsevierStyleItalic">c</span>&#41; pruning to create a simpler tree containing only the most important nodes&#59; and <span class="elsevierStyleItalic">d</span>&#41; selection of tree with the best generalization ability&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a></p><p id="par0100" class="elsevierStylePara elsevierViewall">We used the CART tree-growing process in SPSS version 20&#46;0&#44; with analysis of sensitivity based on the Gini criterion<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> and the cross-validation system&#46; In the final tree&#44; each group had at least 20 cases &#40;10 for subgroup analyses&#41;&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">MedCalc statistical software &#40;version 14&#46;8&#46;1&#41; was used to generate receiver operating characteristic &#40;ROC&#41; curves for the CART and logistic regression models and to calculate the respective areas under the curve&#46; The curves were compared using the DeLong method&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">Kaplan-Meier survival curves were used to evaluate disease-free survival &#40;DFS&#41; and melanoma-specific survival &#40;MSS&#41;&#44; and the log rank rest was applied to compare groups in the univariate analysis&#46; The Cox proportional hazards model was used for the multivariate analysis&#46; A <span class="elsevierStyleItalic">P</span> value of less than &#46;05 was considered statistically significant&#46; SSPS 20&#46;0 was used for statistical analyses&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Participants</span><p id="par0115" class="elsevierStylePara elsevierViewall">In total&#44; 855 patients met the histologic criteria&#44; provided informed consent&#44; and underwent SNB&#46; The SN was identified in 818 patients &#40;95&#46;6&#37;&#41;&#46; Of these 818 patients included in the analysis&#44; 434 &#40;53&#46;1&#37;&#41; were women and 384 &#40;46&#46;9&#37;&#41; were men&#44; with a median age of 53 years &#40;interquartile range&#44; 43-66 years&#41;&#46; <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> summarizes the clinical and histologic characteristics of the study population stratified by SN status&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0120" class="elsevierStylePara elsevierViewall">SN metastasis was associated with increased Breslow thickness&#44; presence of ulceration&#44; absence of regression&#44; a high mitotic rate&#44; and absence of TILs&#46; It was not associated with sex&#44; age&#44; or anatomic location&#46; The association between mitotic rate&#44; increased Breslow thickness&#44; and presence of ulceration is shown graphically in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">SN Status</span><p id="par0125" class="elsevierStylePara elsevierViewall">The following variables were associated with SN metastasis in the univariate analysis&#58; Breslow thickness&#44; presence of ulceration&#44; absence of regression&#44; high mitotic rate&#44; and absence of TILs &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; In the multiple logistic regression model&#44; only ulceration&#44; Breslow thickness&#44; and high mitotic rate &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41; were independently associated with SN metastasis&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">CART Analysis</span><p id="par0130" class="elsevierStylePara elsevierViewall">Six of the 8 variables included initially in the CART analysis were used&#46; Breslow thickness &#40;&#62;2<span class="elsevierStyleHsp" style=""></span>mm vs all other thicknesses&#41; was the most important factor&#46; The variables used for melanomas with a thickness of over 2<span class="elsevierStyleHsp" style=""></span>mm were&#44; by order of importance&#44; inflammatory infiltrate &#40;absent vs brisk&#47;nonbrisk&#41;&#44; age&#44; and anatomic location&#46; For thinner melanomas&#44; they were&#44; also in order of importance&#44; mitotic rate &#40;&#8804;<span class="elsevierStyleHsp" style=""></span>6 vs &#60;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; ulceration&#44; and Breslow thickness &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; Accordingly&#44; patients with the greatest risk of SN involvement were those aged 65 years or younger with melanomas thicker than 2<span class="elsevierStyleHsp" style=""></span>mm located on the extremities&#44; without TILs &#40;SN positivity 58&#37;&#44; n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>60&#41;&#46; By contrast&#44; patients with the least risk of SN involvement were those with ulcerated melanomas with a Breslow thickness of 1<span class="elsevierStyleHsp" style=""></span>mm or less and a mitotic rate of under 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span> &#40;SN positivity 3&#46;3&#37;&#44; n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>181&#41;&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall">The ROC curves for the CART and logistic regression models were similar &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>&#46;7&#41;&#44; with an area under the curve of 0&#46;77 &#40;95&#37; CI&#44; 0&#46;73-0&#46;81&#41; and 0&#46;78 &#40;0&#46;74-0&#46;82&#41;&#44; respectively &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">DFS and MSS</span><p id="par0140" class="elsevierStylePara elsevierViewall">In a median follow-up period of 58 months &#40;range&#44; 1-157 months&#41;&#44; 104 patients died of melanoma and 172 experienced some form of recurrence &#40;uncensured data in the Cox proportional hazards model&#41;&#46; The most important predictor of both DFS and MSS was SN metastasis&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">MSS was 68&#46;1&#37; for patients with SN involvement and 93&#46;1&#37; for those without&#46; The Cox proportional hazards model was adjusted for significant variables in the univariate analysis&#46; SN metastasis was the most important prognostic factor for both DFS &#40;hazard ratio&#44; 2&#46;3&#59; 95&#37; CI&#44; 1&#46;5-3&#46;6&#41; and MSS &#40;hazard ratio&#44; 3&#46;5&#59; 95&#37; CI&#44; 1&#46;9-6&#46;3&#41;&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">Other significant predictors of DFS &#40;shown in detail in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41; were Breslow thickness&#44; age&#44; anatomic location&#44; and mitotic rate &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>&#41;&#46; In the case of MSS &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#44; mitotic rate was an independent prognostic factor&#44; together with age&#44; anatomic location&#44; and Breslow thickness &#40;<a class="elsevierStyleCrossRef" href="#fig0025">Fig&#46; 5</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="fig0025"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Discussion</span><p id="par0155" class="elsevierStylePara elsevierViewall">We have shown in a series of 818 patients with melanoma that mitotic rate&#44; in addition to Breslow thickness and presence of ulceration&#44; is a significant predictor of SN metastasis&#46; Furthermore&#44; mitotic rate was found to be an independent predictor of survival&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">Mitotic rate has not been consistently observed to predict SN metastasis in melanoma&#44; unlike ulceration and&#44; even more so&#44; Breslow thickness&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a></p><p id="par0165" class="elsevierStylePara elsevierViewall">In our series&#44; a mitotic rate of 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span> or more was predictive in the logistic regression model&#46; In the CART analysis&#44; mitotic rate&#44; split into &#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span> versus all other rates&#44; was the most important factor after Breslow thickness&#44; but only in tumors 2<span class="elsevierStyleHsp" style=""></span>mm or thinner&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">Different classifications and models can be built using the same variables&#46; CART&#44; however&#44; is much more intuitive and offers easier-to-interpret results than logistic regression&#44; as it can identify predictors that exert different influences on specific groups of patients&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> It is not&#44; however a question of choosing one model or the other&#44; as different methods should be employed to find an optimal solution for any given problem&#46;<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a></p><p id="par0175" class="elsevierStylePara elsevierViewall">Breslow thickness is considered the most important predictor of SN metastasis&#46;<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a> In our series&#44; we used a cutoff of 2<span class="elsevierStyleHsp" style=""></span>mm in the CART analysis&#44; as this thickness appears to best value for differentiating between different risks of lymph node metastasis&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a></p><p id="par0180" class="elsevierStylePara elsevierViewall">Ulceration has also been highlighted as an important predictor in several studies&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> In our series&#44; it was an independent predictor of SN involvement&#44; but in the CART model it was relevant only for melanomas with a thickness of 2<span class="elsevierStyleHsp" style=""></span>mm or less and a mitotic rate of under 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">The results of the CART analysis suggest that neither mitotic rate nor presence of ulceration can predict an increased risk of SN involvement in patients with melanomas with a thickness of over 2<span class="elsevierStyleHsp" style=""></span>mm&#46; Absence of TILs&#44; by contrast&#44; was associated with a greater likelihood of SN metastasis&#46; Taylor et al&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> were the first authors to describe a significant association between absence of TILs and presence of regional metastasis&#46; Like us&#44; they found no differences in survival with respect to inflammatory infiltrate&#46; They did find that patients without TILs had a higher frequency of regional lymph node recurrence&#44; but the same patients had a similar frequency of distant recurrences to patients with TILs&#44; offering at least a partial explanation for this discrepancy&#46;</p><p id="par0190" class="elsevierStylePara elsevierViewall">Patient age and anatomic location were also among the deeper nodes in the CART model&#44; but they were not statistically significant in the logistic regression analysis&#46;</p><p id="par0195" class="elsevierStylePara elsevierViewall">Compared with melanomas on the extremities&#44; axial melanomas were associated with a lower relative risk of SN involvement in patients with thick tumors or thin tumors &#40;&#8804;<span class="elsevierStyleHsp" style=""></span>2<span class="elsevierStyleHsp" style=""></span>mm&#41; with ulceration&#46; Axial location&#44; however&#44; has been associated with worse DSF and overall survival in some studies&#46; This observation&#44; which has been corroborated by other authors&#44; is intriguing&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> One explanation is that the increased vascularization in axial tumors&#44; and particularly those located on the head and neck&#44; would result in an increased likelihood of hematogenous metastasis&#46; Alternatively&#44; it is possible that the complexity of the lymph system at this level would make it difficult to identify affected SNs&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a></p><p id="par0200" class="elsevierStylePara elsevierViewall">For thick melanomas located on the extremities&#44; we also found that an age of 65 years or younger was associated with greater SN involvement&#44; and paradoxically&#44; better survival&#46;</p><p id="par0205" class="elsevierStylePara elsevierViewall">In the case of melanomas measuring 1<span class="elsevierStyleHsp" style=""></span>mm or less&#44; the frequency of SN involvement was 5&#46;6&#37;&#44; but this dropped to 3&#46;3&#37; in the absence of ulceration and a mitotic rate of under 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#46; Venna et al&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> reviewed a large body of literature aimed at identifying subgroups of patients with thin melanomas and an increased risk of SN involvement and worse prognosis&#46; More recent studies have identified ulceration as an important predictor in this setting&#44;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">28&#44;29</span></a> but the predictors that are most commonly associated with SN involvement in thin melanomas are Breslow thickness&#44; mitotic rate&#44; Clark level&#44; and absence of TILs&#46; Other&#44; less frequently reported factors are age&#44; sex&#44; vertical growth phase&#44; and lymphovascular invasion&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a></p><p id="par0210" class="elsevierStylePara elsevierViewall">In our series&#44; mitotic rate&#44; after SN involvement and Breslow thickness&#44; proved to be an important prognostic factor in both DFS and MSS&#46; This finding is consistent with reports by Azzola et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> whose group in a recent study including more cases confirmed that mitotic rate was a clearly more powerful prognostic indicator than ulceration in primary cutaneous melanoma&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a></p><p id="par0215" class="elsevierStylePara elsevierViewall">In conclusion&#44; mitotic rate was associated with a higher frequency of SN involvement in melanomas with a thickness of 2<span class="elsevierStyleHsp" style=""></span>mm or less&#44; although its most important role was as a predictor of survival in this group&#46; After regional lymph node involvement and Breslow thickness&#44; it was the most important prognostic factor&#44; ahead even of ulceration&#46; Finally&#44; inflammatory infiltrate was a predictor of SN metastasis in patients with melanomas measuring over 2<span class="elsevierStyleHsp" style=""></span>mm&#44; but it had no role as a prognostic factor in these patients&#46;</p><p id="par0220" class="elsevierStylePara elsevierViewall">The practical implications of this study are that CART analysis offers a practical and intuitive method for predicting SN metastasis in melanoma and may contribute to improved clinical management in these patients and guide decisions regarding inclusion in clinical trials&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Ethical Disclosures</span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Protection of humans and animals</span><p id="par0225" class="elsevierStylePara elsevierViewall">The authors declare that no tests were carried out in humans or animals for the purpose of this study&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Confidentiality of data</span><p id="par0230" class="elsevierStylePara elsevierViewall">The authors declare that they have followed their hospital&#39;s protocol on the publication of data concerning patients&#46;</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Right to privacy and informed consent</span><p id="par0235" class="elsevierStylePara elsevierViewall">The authors declare that no private patient data appear in this article&#46;</p></span></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conflicts of Interest</span><p id="par0240" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest&#46;</p></span></span>"
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              "identificador" => "abst0035"
              "titulo" => "Resultados"
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              "titulo" => "Conclusi&#243;n"
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        3 => array:2 [
          "identificador" => "xpalclavsec1558316"
          "titulo" => "Palabras clave"
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        4 => array:2 [
          "identificador" => "sec0005"
          "titulo" => "Introduction"
        ]
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          "identificador" => "sec0010"
          "titulo" => "Material and Methods"
          "secciones" => array:4 [
            0 => array:2 [
              "identificador" => "sec0015"
              "titulo" => "Study Population"
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            1 => array:2 [
              "identificador" => "sec0020"
              "titulo" => "SN Status"
            ]
            2 => array:2 [
              "identificador" => "sec0025"
              "titulo" => "Independent Variables"
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            3 => array:2 [
              "identificador" => "sec0030"
              "titulo" => "Statistical Analysis"
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        ]
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          "titulo" => "Results"
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            0 => array:2 [
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              "titulo" => "Participants"
            ]
            1 => array:2 [
              "identificador" => "sec0045"
              "titulo" => "SN Status"
            ]
            2 => array:2 [
              "identificador" => "sec0050"
              "titulo" => "CART Analysis"
            ]
            3 => array:2 [
              "identificador" => "sec0055"
              "titulo" => "DFS and MSS"
            ]
          ]
        ]
        7 => array:2 [
          "identificador" => "sec0060"
          "titulo" => "Discussion"
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        8 => array:3 [
          "identificador" => "sec0065"
          "titulo" => "Ethical Disclosures"
          "secciones" => array:3 [
            0 => array:2 [
              "identificador" => "sec0070"
              "titulo" => "Protection of humans and animals"
            ]
            1 => array:2 [
              "identificador" => "sec0075"
              "titulo" => "Confidentiality of data"
            ]
            2 => array:2 [
              "identificador" => "sec0080"
              "titulo" => "Right to privacy and informed consent"
            ]
          ]
        ]
        9 => array:2 [
          "identificador" => "sec0085"
          "titulo" => "Conflicts of Interest"
        ]
        10 => array:1 [
          "titulo" => "References"
        ]
      ]
    ]
    "pdfFichero" => "main.pdf"
    "tienePdf" => true
    "fechaRecibido" => "2014-07-10"
    "fechaAceptado" => "2014-10-24"
    "PalabrasClave" => array:2 [
      "en" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1558315"
          "palabras" => array:5 [
            0 => "Melanoma"
            1 => "Sentinel lymph node biopsy"
            2 => "Prognosis"
            3 => "Mitotic index"
            4 => "Tumor infiltrating lymphocytes"
          ]
        ]
      ]
      "es" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Palabras clave"
          "identificador" => "xpalclavsec1558316"
          "palabras" => array:5 [
            0 => "Melanoma"
            1 => "Biopsia de ganglio linf&#225;tico centinela"
            2 => "Pron&#243;stico"
            3 => "&#205;ndice mit&#243;tico"
            4 => "Linfocitos que infiltran los tumores"
          ]
        ]
      ]
    ]
    "tieneResumen" => true
    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The main aim of this study was to identify predictors of sentinel lymph node &#40;SN&#41; metastasis in cutaneous melanoma&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">This was a retrospective cohort study of 818 patients in 2 tertiary-level hospitals&#46; The primary outcome variable was SN involvement&#46; Independent predictors were identified using multiple logistic regression and a classification and regression tree &#40;CART&#41; analysis&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Ulceration&#44; tumor thickness&#44; and a high mitotic rate &#40;&#8805;6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41; were independently associated with SN metastasis in the multiple regression analysis&#46; The most important predictor in the CART analysis was Breslow thickness&#46; Absence of an inflammatory infiltrate&#44; patient age&#44; and tumor location were predictive of SN metastasis in patients with tumors thicker than 2<span class="elsevierStyleHsp" style=""></span>mm&#46; In the case of thinner melanomas&#44; the predictors were mitotic rate &#40;&#62;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; presence of ulceration&#44; and tumor thickness&#46; Patient age&#44; mitotic rate&#44; and tumor thickness and location were predictive of survival&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">A high mitotic rate predicts a higher risk of SN involvement and worse survival&#46; CART analysis improves the prediction of regional metastasis&#44; resulting in better clinical management of melanoma patients&#46; It may also help select suitable candidates for inclusion in clinical trials&#46;</p></span>"
        "secciones" => array:4 [
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            "identificador" => "abst0005"
            "titulo" => "Objective"
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          1 => array:2 [
            "identificador" => "abst0010"
            "titulo" => "Patients and methods"
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          2 => array:2 [
            "identificador" => "abst0015"
            "titulo" => "Results"
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          3 => array:2 [
            "identificador" => "abst0020"
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      "es" => array:3 [
        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">El objetivo principal de este estudio es identificar factores predictivos de la afectaci&#243;n metast&#225;sica del ganglio centinela &#40;GC&#41;&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Pacientes y m&#233;todo</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se trata de un estudio de cohortes retrospectivo realizado en 2 centros hospitalarios de tercer nivel&#46; Se incluyeron un total de 818 pacientes&#46; La medida de resultado principal fue la afectaci&#243;n del GC&#46; La valoraci&#243;n de predictores independientes de esta afectaci&#243;n se realiz&#243; mediante una regresi&#243;n log&#237;stica m&#250;ltiple y un &#225;rbol de clasificaci&#243;n y regresi&#243;n &#40;CART&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">El an&#225;lisis de regresi&#243;n log&#237;stica m&#250;ltiple mostr&#243; que la ulceraci&#243;n&#44; el grosor tumoral y un alto &#237;ndice mit&#243;tico &#40;IM&#41; &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitosis&#47;mm<span class="elsevierStyleSup">2</span>&#41; se relacionaron con la afectaci&#243;n metast&#225;sica del GC de forma independiente&#46; El CART mostr&#243; que el grosor de Breslow fue el factor m&#225;s importante como predictor de la afectaci&#243;n linf&#225;tica&#46; Para los melanomas gruesos &#40;&#62;2<span class="elsevierStyleHsp" style=""></span>mm&#41; las variables predictoras fueron la ausencia de infiltrado inflamatorio&#44; la edad y la localizaci&#243;n&#46; Para los melanomas menores de 2<span class="elsevierStyleHsp" style=""></span>mm las variables predictoras fueron el IM &#40;&#62;6<span class="elsevierStyleHsp" style=""></span>mitosis&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; la ulceraci&#243;n y el grosor&#46; El grosor tumoral&#44; la edad&#44; la localizaci&#243;n y el IM fueron predictores de la supervivencia de estos pacientes&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Un alto IM se asocia con una mayor afectaci&#243;n metast&#225;sica del GC y una peor supervivencia&#46; Con la metodolog&#237;a CART es posible una mejor predicci&#243;n de la afectaci&#243;n metast&#225;sica regional con vistas al mejor manejo cl&#237;nico de estos pacientes o su inclusi&#243;n en ensayos cl&#237;nicos&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0025"
            "titulo" => "Objetivo"
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          1 => array:2 [
            "identificador" => "abst0030"
            "titulo" => "Pacientes y m&#233;todo"
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          2 => array:2 [
            "identificador" => "abst0035"
            "titulo" => "Resultados"
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          3 => array:2 [
            "identificador" => "abst0040"
            "titulo" => "Conclusi&#243;n"
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      ]
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    "NotaPie" => array:1 [
      0 => array:2 [
        "etiqueta" => "&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Please cite this article as&#58; Tejera-Vaquerizo A&#44; Mart&#237;n-Cuevas P&#44; Gallego E&#44; Herrera-Acosta E&#44; Traves V&#44; Herrera-Ceballos E&#44; et al&#46; Factores predictivos del estado del ganglio centinela en el melanoma cut&#225;neo&#58; an&#225;lisis mediante un &#225;rbol de clasificaci&#243;n y regresi&#243;n&#46; Actas Dermosifiliogr&#46; 2015&#59;106&#58;208&#8211;218&#46;</p>"
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        "descripcion" => array:1 [
          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Graph showing association between mitotic rate&#44; Breslow thickness&#44; and ulceration in the study population&#46;</p>"
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        "identificador" => "fig0010"
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Classification and regression tree with the following variables&#58; Breslow thickness&#44; tumor infiltrating lymphocytes&#44; mitotic rate&#44; age&#44; sex&#44; anatomic location&#44; ulceration&#44; and regression&#46; RR indicates relative risk&#46;</p>"
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        "etiqueta" => "Figure 3"
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic curve graph comparing classification and regression tree analysis &#40;CART&#41; and multiple logistic regression &#40;MLR&#41;&#46;</p>"
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          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Kaplan-Meier survival curves for disease-free survival&#46; A&#44; Comparison of patients with a low mitotic rate &#40;0 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; a moderate mitotic rate &#40;1-5 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; and a high mitotic rate &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#46; B&#44; Stratification by sentinel lymph node &#40;SN&#41; involvement&#46;</p>"
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        "etiqueta" => "Figure 5"
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          "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Kaplan-Meier survival curves for melanoma-specific survival&#46; A&#44; Comparison of patients with a low mitotic rate &#40;0 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; a moderate mitotic rate &#40;1-5 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; and a high mitotic rate &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#46; B&#44; Stratification by sentinel lymph node &#40;SN&#41; involvement&#46;</p>"
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        "tabla" => array:2 [
          "leyenda" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Abbreviations&#58; NS&#44; not significant&#59; SNB&#44; sentinel lymph node biopsy&#46;</p>"
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8804;<span class="elsevierStyleHsp" style=""></span>65&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Female&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">330 &#40;51&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  """
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Univariate Analysis</th><th class="td" title="\n
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                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12&#46;4 &#40;6-26&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Present&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Regression</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Present&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;01&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">2&#46;1 &#40;1&#46;1-3&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Mitotic rate&#44; No&#46; of mitoses&#47;mm</span><span class="elsevierStyleSup">2</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>1-5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;8 &#40;1&#46;2-6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7&#46;5 &#40;3&#46;2-17&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;046&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;6 &#40;1&#46;1-6&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Tumor infiltrating lymphocytes</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Brisk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Nonbrisk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;5&#40;0&#46;8-7&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;03&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;2 &#40;1&#46;1-9&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Breslow thickness&#44; mm</span><a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a><span class="elsevierStyleItalic">ulceration</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>1&#46;01-2<a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a> ulceration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;06&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;16 &#40;0&#46;02-1&#46;05&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>2&#46;01-4<a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a> ulceration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">15&#46;1 &#40;4&#46;5-50&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Present&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Regression</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Present&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;5 &#40;0&#46;8-3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Mitotic rate&#44; No&#46; of mitoses&#47;mm</span><span class="elsevierStyleSup">2</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>1-5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;032&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;8 &#40;1&#46;2-17&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;029&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;2 &#40;0&#46;9-18&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14&#46;3 &#40;3&#46;5-59&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;004&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9&#46;1 &#40;2&#46;1-41&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Inflammatory infiltrate</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Brisk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Nonbrisk&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;2 &#40;0&#46;5-4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;5 &#40;0&#46;4-3&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">SNB result</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Positive&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;6 &#40;2&#46;9-7&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;5 &#40;1&#46;9-6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Negative&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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Original Article
Predictors of Sentinel Lymph Node Status in Cutaneous Melanoma: A Classification and Regression Tree Analysis
Factores predictivos del estado del ganglio centinela en el melanoma cutáneo: análisis mediante un árbol de clasificación y regresión
A. Tejera-Vaquerizoa,
Autor para correspondencia
antoniotejera@aedv.es
antoniotejera@globalderm.es

Corresponding author. Tel.: +0034653440826.
, P. Martín-Cuevasa, E. Gallegob, E. Herrera-Acostaa, V. Travesc, E. Herrera-Ceballosa, E. Nagored
a Servicio de Dermatología, Instituto de Biomedicina de Málaga (IBIMA), Hospital Universitario Virgen de la Victoria/Universidad de Málaga, Málaga, Spain
b Servicio de Anatomía Patológica, Instituto de Biomedicina de Málaga (IBIMA), Hospital Universitario Virgen de la Victoria/Universidad de Málaga, Málaga, Spain
c Departamento de Anatomía Patológica, Instituto Valenciano de Oncología, Valencia, Spain
d Servicio de Dermatología, Instituto Valenciano de Oncología, Valencia, Spain
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and one particularly useful tool is classification and regression tree &#40;CART&#41; analysis&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> CART offers several advantages over logistic regression&#46; It is simpler to use and interpret&#44; and furthermore&#44; the fact that it is based on a nonparametric method means that no prior assumptions need to be made regarding the distribution of predictors&#44; the relationships between predictors and outcome&#44; or interactions between predictors&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">The main aim of this study was to identify predictors of SN metastasis in cutaneous melanoma using CART and logistic regression&#46; A secondary goal was to evaluate the role of these factors in predicting disease-free survival and melanoma-specific survival&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Material and Methods</span><p id="par0030" class="elsevierStylePara elsevierViewall">This was a retrospective&#44; observational study&#46;</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study Population</span><p id="par0035" class="elsevierStylePara elsevierViewall">The study participants were selected from the melanoma databases at Hospital Virgen de la Victoria &#40;HVV&#41; in Malaga&#44; Spain and Instituto Valenciano de Oncolog&#237;a &#40;IVO&#41; in Valencia&#44; Spain&#46; All ethical requirements regarding the use of databases were complied with&#46; The 2 databases have been described in detail in previous studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0070"><span class="elsevierStyleSup">14&#8211;16</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">For this particular study&#44; we selected all patients with a single cutaneous melanoma&#44; classified as clinical stage I or II&#44; who had undergone SN biopsy and been prospectively included in the IVO database between January 1&#44; 2000 and December 31&#44; 2012 or in the HVV database between October 1&#44; 2001 and December 31&#44; 2012&#46; Patients without an identifiable SN during the SN biopsy were excluded from the study&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">The study was approved by the ethics committees at the HVV and IVO&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">The dependent variable was SN status&#44; which was classified as positive in the presence of melanoma cells in the SN and negative otherwise&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">SN Status</span><p id="par0055" class="elsevierStylePara elsevierViewall">The methods used for the pathologic examination of the SN are quite similar in both hospitals and are summarized below&#58;</p><p id="par0060" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">HVV</span>&#46; The first step is the gross identification and retrieval of the SN&#44; with clearing of surrounding fat where necessary&#46; The SN is then fixed in formalin 10&#37; prior to embedding in a paraffin block&#46; Each block is serially sectioned into 3 slices every 250<span class="elsevierStyleHsp" style=""></span>&#956;m until the whole block is cut&#46; The first and last sections are used for hematoxylin-eosin staining&#44; while the middle section is used for immunohistochemical staining with HMB-45&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">IVO</span>&#46; The first stage is the same as at the HVV&#58; identification and retrieval of the SN and clearing of fat where necessary&#46; The specimen is also immersed in formalin 10&#37; and embedded in a paraffin block&#46; Serial sections are taken from the entire block every 250<span class="elsevierStyleHsp" style=""></span>&#956;m&#46; Three cross-sections are taken from each section&#46; One is stained with hematoxylin-eosin&#44; and the other 2 are kept for immunohistochemical staining with S-100 protein and HMB-45&#46; The immunohistochemical study is only performed following confirmation of the absence of metastasis in the hematoxylin-eosin section&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Independent Variables</span><p id="par0070" class="elsevierStylePara elsevierViewall">The following clinical and histologic characteristics were selected as independent variables&#58;</p><p id="par0075" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">Clinical characteristics&#46;</span> Patient sex and age &#40;&#8804;<span class="elsevierStyleHsp" style=""></span>65 vs &#62;<span class="elsevierStyleHsp" style=""></span>65 years&#41; and anatomic location of the primary melanoma&#46; Anatomic location was dichotomized into axial &#40;head&#44; neck&#44; trunk&#44; and volar or subungual sites&#41; and extremities&#46; The system proposed by Kruper et al&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> was used to classify volar and subungual melanomas&#44; as these are associated with a worse prognosis &#40;possibly partly due to genetic alterations&#41; that distinguishes them from other types of melanoma&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a></p><p id="par0080" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">Histologic characteristics&#46;</span> Breslow thickness &#40;categorized according to the AJCC as &#8804;<span class="elsevierStyleHsp" style=""></span>1&#46;00&#44; 1&#46;01-2&#44; 2&#46;01-4&#44; and &#62;<span class="elsevierStyleHsp" style=""></span>4<span class="elsevierStyleHsp" style=""></span>mm&#41;&#44; ulceration &#40;present vs absent&#41;&#44; regression &#40;present vs absent&#41;&#44; mitotic rate &#40;0&#44; 1-5&#44; or &#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> and tumor infiltrating lymphocytes &#40;TILs&#41; &#40;absent&#44; nonbrisk&#44; and brisk&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a></p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical Analysis</span><p id="par0085" class="elsevierStylePara elsevierViewall">The dependent variable was SN positivity&#46; Independent variables were included as binary variables &#40;sex&#44; age&#44; ulceration&#44; anatomic location&#44; and regression&#41; or categorical variables &#40;Breslow thickness&#44; TILs&#44; and mitotic rate&#41;&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">In the logistic regression analysis&#44; we first analyzed the association between SN positivity and the study variables using the &#967;<span class="elsevierStyleSup">2</span> test or univariate logistic regression analysis&#46; The Wald test was used to calculate odds ratios with 95&#37; CIs for all variables&#46; Multiple logistic regression was used to identify independent predictors of SN positivity&#46; All possible interactions between variables were also analyzed&#46; Goodness of fit was assessed with the Hosmer-Lemeshow test&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">The classification tree was built using the CART method&#44;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> which is used to build decision trees through a set of rules governing decisions taken to assign an output value to each alternative through a process known as binary recursive partitioning&#46; Each parent note is split into 2 homogeneous child nodes by asking questions with a <span class="elsevierStyleItalic">yes</span> and <span class="elsevierStyleItalic">no</span> answer&#46; The CART process involves several stages&#58; <span class="elsevierStyleItalic">a</span>&#41; tree growing&#59; <span class="elsevierStyleItalic">b</span>&#41; application of stopping rules for the tree-growing process &#40;a maximal tree that overadjusts the data used to generate the tree is built&#41;&#59; <span class="elsevierStyleItalic">c</span>&#41; pruning to create a simpler tree containing only the most important nodes&#59; and <span class="elsevierStyleItalic">d</span>&#41; selection of tree with the best generalization ability&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a></p><p id="par0100" class="elsevierStylePara elsevierViewall">We used the CART tree-growing process in SPSS version 20&#46;0&#44; with analysis of sensitivity based on the Gini criterion<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> and the cross-validation system&#46; In the final tree&#44; each group had at least 20 cases &#40;10 for subgroup analyses&#41;&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">MedCalc statistical software &#40;version 14&#46;8&#46;1&#41; was used to generate receiver operating characteristic &#40;ROC&#41; curves for the CART and logistic regression models and to calculate the respective areas under the curve&#46; The curves were compared using the DeLong method&#46;<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a></p><p id="par0110" class="elsevierStylePara elsevierViewall">Kaplan-Meier survival curves were used to evaluate disease-free survival &#40;DFS&#41; and melanoma-specific survival &#40;MSS&#41;&#44; and the log rank rest was applied to compare groups in the univariate analysis&#46; The Cox proportional hazards model was used for the multivariate analysis&#46; A <span class="elsevierStyleItalic">P</span> value of less than &#46;05 was considered statistically significant&#46; SSPS 20&#46;0 was used for statistical analyses&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Participants</span><p id="par0115" class="elsevierStylePara elsevierViewall">In total&#44; 855 patients met the histologic criteria&#44; provided informed consent&#44; and underwent SNB&#46; The SN was identified in 818 patients &#40;95&#46;6&#37;&#41;&#46; Of these 818 patients included in the analysis&#44; 434 &#40;53&#46;1&#37;&#41; were women and 384 &#40;46&#46;9&#37;&#41; were men&#44; with a median age of 53 years &#40;interquartile range&#44; 43-66 years&#41;&#46; <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> summarizes the clinical and histologic characteristics of the study population stratified by SN status&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0120" class="elsevierStylePara elsevierViewall">SN metastasis was associated with increased Breslow thickness&#44; presence of ulceration&#44; absence of regression&#44; a high mitotic rate&#44; and absence of TILs&#46; It was not associated with sex&#44; age&#44; or anatomic location&#46; The association between mitotic rate&#44; increased Breslow thickness&#44; and presence of ulceration is shown graphically in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">SN Status</span><p id="par0125" class="elsevierStylePara elsevierViewall">The following variables were associated with SN metastasis in the univariate analysis&#58; Breslow thickness&#44; presence of ulceration&#44; absence of regression&#44; high mitotic rate&#44; and absence of TILs &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; In the multiple logistic regression model&#44; only ulceration&#44; Breslow thickness&#44; and high mitotic rate &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41; were independently associated with SN metastasis&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">CART Analysis</span><p id="par0130" class="elsevierStylePara elsevierViewall">Six of the 8 variables included initially in the CART analysis were used&#46; Breslow thickness &#40;&#62;2<span class="elsevierStyleHsp" style=""></span>mm vs all other thicknesses&#41; was the most important factor&#46; The variables used for melanomas with a thickness of over 2<span class="elsevierStyleHsp" style=""></span>mm were&#44; by order of importance&#44; inflammatory infiltrate &#40;absent vs brisk&#47;nonbrisk&#41;&#44; age&#44; and anatomic location&#46; For thinner melanomas&#44; they were&#44; also in order of importance&#44; mitotic rate &#40;&#8804;<span class="elsevierStyleHsp" style=""></span>6 vs &#60;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; ulceration&#44; and Breslow thickness &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; Accordingly&#44; patients with the greatest risk of SN involvement were those aged 65 years or younger with melanomas thicker than 2<span class="elsevierStyleHsp" style=""></span>mm located on the extremities&#44; without TILs &#40;SN positivity 58&#37;&#44; n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>60&#41;&#46; By contrast&#44; patients with the least risk of SN involvement were those with ulcerated melanomas with a Breslow thickness of 1<span class="elsevierStyleHsp" style=""></span>mm or less and a mitotic rate of under 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span> &#40;SN positivity 3&#46;3&#37;&#44; n<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>181&#41;&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0135" class="elsevierStylePara elsevierViewall">The ROC curves for the CART and logistic regression models were similar &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>&#46;7&#41;&#44; with an area under the curve of 0&#46;77 &#40;95&#37; CI&#44; 0&#46;73-0&#46;81&#41; and 0&#46;78 &#40;0&#46;74-0&#46;82&#41;&#44; respectively &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">DFS and MSS</span><p id="par0140" class="elsevierStylePara elsevierViewall">In a median follow-up period of 58 months &#40;range&#44; 1-157 months&#41;&#44; 104 patients died of melanoma and 172 experienced some form of recurrence &#40;uncensured data in the Cox proportional hazards model&#41;&#46; The most important predictor of both DFS and MSS was SN metastasis&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">MSS was 68&#46;1&#37; for patients with SN involvement and 93&#46;1&#37; for those without&#46; The Cox proportional hazards model was adjusted for significant variables in the univariate analysis&#46; SN metastasis was the most important prognostic factor for both DFS &#40;hazard ratio&#44; 2&#46;3&#59; 95&#37; CI&#44; 1&#46;5-3&#46;6&#41; and MSS &#40;hazard ratio&#44; 3&#46;5&#59; 95&#37; CI&#44; 1&#46;9-6&#46;3&#41;&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">Other significant predictors of DFS &#40;shown in detail in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41; were Breslow thickness&#44; age&#44; anatomic location&#44; and mitotic rate &#40;<a class="elsevierStyleCrossRef" href="#fig0020">Fig&#46; 4</a>&#41;&#46; In the case of MSS &#40;<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>&#41;&#44; mitotic rate was an independent prognostic factor&#44; together with age&#44; anatomic location&#44; and Breslow thickness &#40;<a class="elsevierStyleCrossRef" href="#fig0025">Fig&#46; 5</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0020"></elsevierMultimedia><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="fig0025"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Discussion</span><p id="par0155" class="elsevierStylePara elsevierViewall">We have shown in a series of 818 patients with melanoma that mitotic rate&#44; in addition to Breslow thickness and presence of ulceration&#44; is a significant predictor of SN metastasis&#46; Furthermore&#44; mitotic rate was found to be an independent predictor of survival&#46;</p><p id="par0160" class="elsevierStylePara elsevierViewall">Mitotic rate has not been consistently observed to predict SN metastasis in melanoma&#44; unlike ulceration and&#44; even more so&#44; Breslow thickness&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a></p><p id="par0165" class="elsevierStylePara elsevierViewall">In our series&#44; a mitotic rate of 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span> or more was predictive in the logistic regression model&#46; In the CART analysis&#44; mitotic rate&#44; split into &#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span> versus all other rates&#44; was the most important factor after Breslow thickness&#44; but only in tumors 2<span class="elsevierStyleHsp" style=""></span>mm or thinner&#46;</p><p id="par0170" class="elsevierStylePara elsevierViewall">Different classifications and models can be built using the same variables&#46; CART&#44; however&#44; is much more intuitive and offers easier-to-interpret results than logistic regression&#44; as it can identify predictors that exert different influences on specific groups of patients&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> It is not&#44; however a question of choosing one model or the other&#44; as different methods should be employed to find an optimal solution for any given problem&#46;<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a></p><p id="par0175" class="elsevierStylePara elsevierViewall">Breslow thickness is considered the most important predictor of SN metastasis&#46;<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a> In our series&#44; we used a cutoff of 2<span class="elsevierStyleHsp" style=""></span>mm in the CART analysis&#44; as this thickness appears to best value for differentiating between different risks of lymph node metastasis&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a></p><p id="par0180" class="elsevierStylePara elsevierViewall">Ulceration has also been highlighted as an important predictor in several studies&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> In our series&#44; it was an independent predictor of SN involvement&#44; but in the CART model it was relevant only for melanomas with a thickness of 2<span class="elsevierStyleHsp" style=""></span>mm or less and a mitotic rate of under 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#46;</p><p id="par0185" class="elsevierStylePara elsevierViewall">The results of the CART analysis suggest that neither mitotic rate nor presence of ulceration can predict an increased risk of SN involvement in patients with melanomas with a thickness of over 2<span class="elsevierStyleHsp" style=""></span>mm&#46; Absence of TILs&#44; by contrast&#44; was associated with a greater likelihood of SN metastasis&#46; Taylor et al&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> were the first authors to describe a significant association between absence of TILs and presence of regional metastasis&#46; Like us&#44; they found no differences in survival with respect to inflammatory infiltrate&#46; They did find that patients without TILs had a higher frequency of regional lymph node recurrence&#44; but the same patients had a similar frequency of distant recurrences to patients with TILs&#44; offering at least a partial explanation for this discrepancy&#46;</p><p id="par0190" class="elsevierStylePara elsevierViewall">Patient age and anatomic location were also among the deeper nodes in the CART model&#44; but they were not statistically significant in the logistic regression analysis&#46;</p><p id="par0195" class="elsevierStylePara elsevierViewall">Compared with melanomas on the extremities&#44; axial melanomas were associated with a lower relative risk of SN involvement in patients with thick tumors or thin tumors &#40;&#8804;<span class="elsevierStyleHsp" style=""></span>2<span class="elsevierStyleHsp" style=""></span>mm&#41; with ulceration&#46; Axial location&#44; however&#44; has been associated with worse DSF and overall survival in some studies&#46; This observation&#44; which has been corroborated by other authors&#44; is intriguing&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> One explanation is that the increased vascularization in axial tumors&#44; and particularly those located on the head and neck&#44; would result in an increased likelihood of hematogenous metastasis&#46; Alternatively&#44; it is possible that the complexity of the lymph system at this level would make it difficult to identify affected SNs&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a></p><p id="par0200" class="elsevierStylePara elsevierViewall">For thick melanomas located on the extremities&#44; we also found that an age of 65 years or younger was associated with greater SN involvement&#44; and paradoxically&#44; better survival&#46;</p><p id="par0205" class="elsevierStylePara elsevierViewall">In the case of melanomas measuring 1<span class="elsevierStyleHsp" style=""></span>mm or less&#44; the frequency of SN involvement was 5&#46;6&#37;&#44; but this dropped to 3&#46;3&#37; in the absence of ulceration and a mitotic rate of under 6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#46; Venna et al&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> reviewed a large body of literature aimed at identifying subgroups of patients with thin melanomas and an increased risk of SN involvement and worse prognosis&#46; More recent studies have identified ulceration as an important predictor in this setting&#44;<a class="elsevierStyleCrossRefs" href="#bib0140"><span class="elsevierStyleSup">28&#44;29</span></a> but the predictors that are most commonly associated with SN involvement in thin melanomas are Breslow thickness&#44; mitotic rate&#44; Clark level&#44; and absence of TILs&#46; Other&#44; less frequently reported factors are age&#44; sex&#44; vertical growth phase&#44; and lymphovascular invasion&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a></p><p id="par0210" class="elsevierStylePara elsevierViewall">In our series&#44; mitotic rate&#44; after SN involvement and Breslow thickness&#44; proved to be an important prognostic factor in both DFS and MSS&#46; This finding is consistent with reports by Azzola et al&#46;&#44;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> whose group in a recent study including more cases confirmed that mitotic rate was a clearly more powerful prognostic indicator than ulceration in primary cutaneous melanoma&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a></p><p id="par0215" class="elsevierStylePara elsevierViewall">In conclusion&#44; mitotic rate was associated with a higher frequency of SN involvement in melanomas with a thickness of 2<span class="elsevierStyleHsp" style=""></span>mm or less&#44; although its most important role was as a predictor of survival in this group&#46; After regional lymph node involvement and Breslow thickness&#44; it was the most important prognostic factor&#44; ahead even of ulceration&#46; Finally&#44; inflammatory infiltrate was a predictor of SN metastasis in patients with melanomas measuring over 2<span class="elsevierStyleHsp" style=""></span>mm&#44; but it had no role as a prognostic factor in these patients&#46;</p><p id="par0220" class="elsevierStylePara elsevierViewall">The practical implications of this study are that CART analysis offers a practical and intuitive method for predicting SN metastasis in melanoma and may contribute to improved clinical management in these patients and guide decisions regarding inclusion in clinical trials&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Ethical Disclosures</span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Protection of humans and animals</span><p id="par0225" class="elsevierStylePara elsevierViewall">The authors declare that no tests were carried out in humans or animals for the purpose of this study&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Confidentiality of data</span><p id="par0230" class="elsevierStylePara elsevierViewall">The authors declare that they have followed their hospital&#39;s protocol on the publication of data concerning patients&#46;</p></span><span id="sec0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0140">Right to privacy and informed consent</span><p id="par0235" class="elsevierStylePara elsevierViewall">The authors declare that no private patient data appear in this article&#46;</p></span></span><span id="sec0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0145">Conflicts of Interest</span><p id="par0240" class="elsevierStylePara elsevierViewall">The authors declare that they have no conflicts of interest&#46;</p></span></span>"
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              "identificador" => "sec0055"
              "titulo" => "DFS and MSS"
            ]
          ]
        ]
        7 => array:2 [
          "identificador" => "sec0060"
          "titulo" => "Discussion"
        ]
        8 => array:3 [
          "identificador" => "sec0065"
          "titulo" => "Ethical Disclosures"
          "secciones" => array:3 [
            0 => array:2 [
              "identificador" => "sec0070"
              "titulo" => "Protection of humans and animals"
            ]
            1 => array:2 [
              "identificador" => "sec0075"
              "titulo" => "Confidentiality of data"
            ]
            2 => array:2 [
              "identificador" => "sec0080"
              "titulo" => "Right to privacy and informed consent"
            ]
          ]
        ]
        9 => array:2 [
          "identificador" => "sec0085"
          "titulo" => "Conflicts of Interest"
        ]
        10 => array:1 [
          "titulo" => "References"
        ]
      ]
    ]
    "pdfFichero" => "main.pdf"
    "tienePdf" => true
    "fechaRecibido" => "2014-07-10"
    "fechaAceptado" => "2014-10-24"
    "PalabrasClave" => array:2 [
      "en" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1558315"
          "palabras" => array:5 [
            0 => "Melanoma"
            1 => "Sentinel lymph node biopsy"
            2 => "Prognosis"
            3 => "Mitotic index"
            4 => "Tumor infiltrating lymphocytes"
          ]
        ]
      ]
      "es" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Palabras clave"
          "identificador" => "xpalclavsec1558316"
          "palabras" => array:5 [
            0 => "Melanoma"
            1 => "Biopsia de ganglio linf&#225;tico centinela"
            2 => "Pron&#243;stico"
            3 => "&#205;ndice mit&#243;tico"
            4 => "Linfocitos que infiltran los tumores"
          ]
        ]
      ]
    ]
    "tieneResumen" => true
    "resumen" => array:2 [
      "en" => array:3 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Objective</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">The main aim of this study was to identify predictors of sentinel lymph node &#40;SN&#41; metastasis in cutaneous melanoma&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">This was a retrospective cohort study of 818 patients in 2 tertiary-level hospitals&#46; The primary outcome variable was SN involvement&#46; Independent predictors were identified using multiple logistic regression and a classification and regression tree &#40;CART&#41; analysis&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Ulceration&#44; tumor thickness&#44; and a high mitotic rate &#40;&#8805;6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41; were independently associated with SN metastasis in the multiple regression analysis&#46; The most important predictor in the CART analysis was Breslow thickness&#46; Absence of an inflammatory infiltrate&#44; patient age&#44; and tumor location were predictive of SN metastasis in patients with tumors thicker than 2<span class="elsevierStyleHsp" style=""></span>mm&#46; In the case of thinner melanomas&#44; the predictors were mitotic rate &#40;&#62;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; presence of ulceration&#44; and tumor thickness&#46; Patient age&#44; mitotic rate&#44; and tumor thickness and location were predictive of survival&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">A high mitotic rate predicts a higher risk of SN involvement and worse survival&#46; CART analysis improves the prediction of regional metastasis&#44; resulting in better clinical management of melanoma patients&#46; It may also help select suitable candidates for inclusion in clinical trials&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0005"
            "titulo" => "Objective"
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          1 => array:2 [
            "identificador" => "abst0010"
            "titulo" => "Patients and methods"
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          2 => array:2 [
            "identificador" => "abst0015"
            "titulo" => "Results"
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          3 => array:2 [
            "identificador" => "abst0020"
            "titulo" => "Conclusions"
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      "es" => array:3 [
        "titulo" => "Resumen"
        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">El objetivo principal de este estudio es identificar factores predictivos de la afectaci&#243;n metast&#225;sica del ganglio centinela &#40;GC&#41;&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Pacientes y m&#233;todo</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se trata de un estudio de cohortes retrospectivo realizado en 2 centros hospitalarios de tercer nivel&#46; Se incluyeron un total de 818 pacientes&#46; La medida de resultado principal fue la afectaci&#243;n del GC&#46; La valoraci&#243;n de predictores independientes de esta afectaci&#243;n se realiz&#243; mediante una regresi&#243;n log&#237;stica m&#250;ltiple y un &#225;rbol de clasificaci&#243;n y regresi&#243;n &#40;CART&#41;&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">El an&#225;lisis de regresi&#243;n log&#237;stica m&#250;ltiple mostr&#243; que la ulceraci&#243;n&#44; el grosor tumoral y un alto &#237;ndice mit&#243;tico &#40;IM&#41; &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitosis&#47;mm<span class="elsevierStyleSup">2</span>&#41; se relacionaron con la afectaci&#243;n metast&#225;sica del GC de forma independiente&#46; El CART mostr&#243; que el grosor de Breslow fue el factor m&#225;s importante como predictor de la afectaci&#243;n linf&#225;tica&#46; Para los melanomas gruesos &#40;&#62;2<span class="elsevierStyleHsp" style=""></span>mm&#41; las variables predictoras fueron la ausencia de infiltrado inflamatorio&#44; la edad y la localizaci&#243;n&#46; Para los melanomas menores de 2<span class="elsevierStyleHsp" style=""></span>mm las variables predictoras fueron el IM &#40;&#62;6<span class="elsevierStyleHsp" style=""></span>mitosis&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; la ulceraci&#243;n y el grosor&#46; El grosor tumoral&#44; la edad&#44; la localizaci&#243;n y el IM fueron predictores de la supervivencia de estos pacientes&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Un alto IM se asocia con una mayor afectaci&#243;n metast&#225;sica del GC y una peor supervivencia&#46; Con la metodolog&#237;a CART es posible una mejor predicci&#243;n de la afectaci&#243;n metast&#225;sica regional con vistas al mejor manejo cl&#237;nico de estos pacientes o su inclusi&#243;n en ensayos cl&#237;nicos&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0025"
            "titulo" => "Objetivo"
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          1 => array:2 [
            "identificador" => "abst0030"
            "titulo" => "Pacientes y m&#233;todo"
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          2 => array:2 [
            "identificador" => "abst0035"
            "titulo" => "Resultados"
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          3 => array:2 [
            "identificador" => "abst0040"
            "titulo" => "Conclusi&#243;n"
          ]
        ]
      ]
    ]
    "NotaPie" => array:1 [
      0 => array:2 [
        "etiqueta" => "&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0010">Please cite this article as&#58; Tejera-Vaquerizo A&#44; Mart&#237;n-Cuevas P&#44; Gallego E&#44; Herrera-Acosta E&#44; Traves V&#44; Herrera-Ceballos E&#44; et al&#46; Factores predictivos del estado del ganglio centinela en el melanoma cut&#225;neo&#58; an&#225;lisis mediante un &#225;rbol de clasificaci&#243;n y regresi&#243;n&#46; Actas Dermosifiliogr&#46; 2015&#59;106&#58;208&#8211;218&#46;</p>"
      ]
    ]
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        "figura" => array:1 [
          0 => array:4 [
            "imagen" => "gr1.jpeg"
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        "descripcion" => array:1 [
          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Graph showing association between mitotic rate&#44; Breslow thickness&#44; and ulceration in the study population&#46;</p>"
        ]
      ]
      1 => array:7 [
        "identificador" => "fig0010"
        "etiqueta" => "Figure 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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        "figura" => array:1 [
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Classification and regression tree with the following variables&#58; Breslow thickness&#44; tumor infiltrating lymphocytes&#44; mitotic rate&#44; age&#44; sex&#44; anatomic location&#44; ulceration&#44; and regression&#46; RR indicates relative risk&#46;</p>"
        ]
      ]
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        "identificador" => "fig0015"
        "etiqueta" => "Figure 3"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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        "figura" => array:1 [
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          "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic curve graph comparing classification and regression tree analysis &#40;CART&#41; and multiple logistic regression &#40;MLR&#41;&#46;</p>"
        ]
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        "etiqueta" => "Figure 4"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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        "figura" => array:1 [
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          "en" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">Kaplan-Meier survival curves for disease-free survival&#46; A&#44; Comparison of patients with a low mitotic rate &#40;0 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; a moderate mitotic rate &#40;1-5 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; and a high mitotic rate &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#46; B&#44; Stratification by sentinel lymph node &#40;SN&#41; involvement&#46;</p>"
        ]
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      4 => array:7 [
        "identificador" => "fig0025"
        "etiqueta" => "Figure 5"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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        "figura" => array:1 [
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        "descripcion" => array:1 [
          "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Kaplan-Meier survival curves for melanoma-specific survival&#46; A&#44; Comparison of patients with a low mitotic rate &#40;0 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; a moderate mitotic rate &#40;1-5 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#44; and a high mitotic rate &#40;&#8805;<span class="elsevierStyleHsp" style=""></span>6 mitoses&#47;mm<span class="elsevierStyleSup">2</span>&#41;&#46; B&#44; Stratification by sentinel lymph node &#40;SN&#41; involvement&#46;</p>"
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        "tabla" => array:2 [
          "leyenda" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">Abbreviations&#58; NS&#44; not significant&#59; SNB&#44; sentinel lymph node biopsy&#46;</p>"
          "tablatextoimagen" => array:1 [
            0 => array:1 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No&#46; &#40;&#37;&#41; of Patients With Negative SNB&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No&#46; &#40;&#37;&#41; of Patients With Positive SNB&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8804;<span class="elsevierStyleHsp" style=""></span>65&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">479 &#40;75&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">130 &#40;74&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">45 &#40;25&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Female&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">330 &#40;51&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">104 &#40;58&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">311 &#40;48&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">73 &#40;41&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleItalic">Anatomic Location</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Axial&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">136 &#40;21&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">30 &#40;16&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Extremities&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Univariate Analysis</th><th class="td" title="\n
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                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>4&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Present&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;2 &#40;2&#46;1-4&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;003&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12&#46;3 &#40;2&#46;3-65&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Regression</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Present&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;1 &#40;1&#46;1-3&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Mitotic rate&#44; No&#46; of mitoses&#47;mm</span><span class="elsevierStyleSup">2</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>1-5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;01&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;8 &#40;1&#46;2-6&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7&#46;5 &#40;3&#46;2-17&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;046&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;6 &#40;1&#46;1-6&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Tumor infiltrating lymphocytes</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Brisk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Nonbrisk&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;5&#40;0&#46;8-7&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;03&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;2 &#40;1&#46;1-9&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Breslow thickness&#44; mm</span><a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a><span class="elsevierStyleItalic">ulceration</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>1&#46;01-2<a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a> ulceration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;06&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;16 &#40;0&#46;02-1&#46;05&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>2&#46;01-4<a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a> ulceration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#46;03&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;15 &#40;0&#46;02-0&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>&#62;<span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>4<a class="elsevierStyleCrossRef" href="#tblfn0005">&#42;</a> ulceration&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Absent&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleItalic">Regression</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Present&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#8230;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">2&#46;3 &#40;1&#46;3-4&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="5" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Mitotic rate&#46; No&#46; of mitoses&#47;mm</span><span class="elsevierStyleSup">2</span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>0&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>1-5&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>&#8805;<span class="elsevierStyleHsp" style=""></span>6&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Univariate Analysis</th><th class="td" title="\n
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Información del artículo
ISSN: 15782190
Idioma original: Inglés
DOI:10.1016/j.adengl.2015.01.005
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