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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Ann Surg Oncol. Author manuscript; available in PMC 2012 October 1.
Published in final edited form as:
PMCID: PMC3461951

Factors Predictive of the Status of Sentinel Lymph Nodes in Melanoma Patients from a Large Multicenter Database



Numerous predictive factors for cutaneous melanoma metastases to sentinel lymph nodes have been identified; however, few have been found to be reproducibly significant. This study investigated the significance of factors for predicting regional nodal disease in cutaneous melanoma using a large multicenter database.


Seventeen institutions submitted retrospective and prospective data on 3463 patients undergoing sentinel lymph node (SLN) biopsy for primary melanoma. Multiple demographic and tumor factors were analyzed for correlation with a positive SLN. Univariate and multivariate statistical analyses were performed.


Of 3445 analyzable patients, 561 (16.3%) had a positive SLN biopsy. In multivariate analysis of 1526 patients with complete records for 10 variables, increasing Breslow thickness, lymphovascular invasion, ulceration, younger age, the absence of regression, and tumor location on the trunk were statistically significant predictors of a positive SLN.


These results confirm the predictive significance of the well-established variables of Breslow thickness, ulceration, age, and location, as well as consistently reported but less well-established variables such as lymphovascular invasion. In addition, the presence of regression was associated with a lower likelihood of a positive SLN. Consideration of multiple tumor parameters should influence the decision for SLN biopsy and the estimation of nodal metastatic disease risk.

Many researchers have attempted to identify factors that are associated with a positive sentinel lymph node (SLN) in primary melanoma. Factors that have been investigated include patient age,124 sex,121,23,24 site of primary tumor,13,6,811,1321,2327 Breslow thickness,127 Clark level,14,6,8,9,12,13,1518,20,23,24,27 ulceration,18,1020,2224,26,27 vertical growth phase,1,8,14,17 tumor-infiltrating lymphocytes (TIL),1,6,10,15,17 tumor mitotic rate (TMR),1,6,7,10,11,1417,20,25 histologic type,1,4,7,8,11,17,19,20,22 lymphovascular invasion (LVI),1,7,8,10,11,14,22,23 regression,1,68,10,11,14,22,24,2830 number of draining basins,1,4,7,8,11,12,16,17,22 number of SLNs collected,7,11,17 T classification,13,17 primary margin status,14 microsatellitosis,7,10,11,14 neurotropism,7,11,14 and periadnexal extension.11,14 Of these factors, all except number of SLNs collected, margin status, neurotropism, and periadnexal extension have been found to be important predictors of SLN status on at least univariate analysis. However, only a few of these variables have been found to be reproducibly significant—that is, significant by multivariable analysis in more than one study. These factors are Breslow thickness,1,68,1120,2225,27,31 ulceration,1,8,12,13,15,17,20,22,23,27,31 TMR,6,7,11,14,16,17,25 patient age,1,7,8,11,13,14,16,20,22,23,31 primary site,11,13,22,25 Clark level,8,22 LVI,11,22,23 the absence of TIL,6,15 and male sex.31

The objective of this study was to use a multicenter database to identify factors predictive of positive SLNs.


The Sentinel Lymph Node Working Group (SLNWG) consists of 30 member institutions and is based in San Francisco, California. Seventeen institutions contributed a total of 3463 patients for this study. All members obtained approval from their respective institutional review boards before submitting patients for this study. Informed consent was obtained from all patients except where waiver of informed consent was granted by the institutional review board for retrospective data collection.

The SLNWG database is maintained at Vanderbilt University in Nashville, Tennessee. Patient data are submitted by each member institution through a password-protected Web site into this standardized database.

SLN biopsy was performed as previously described using blue dye, radioactive colloid, or both.32 Indications for SLN biopsy and specific operative techniques were determined by individual investigators. In general, the investigators in this multicenter study used a combination of radioactive colloid and blue dye with preoperative lymphoscintigraphy. One pioneer group in the 1980s initially used blue dye only from November 6, 1985, to October 7, 1992, in 45 patients (1.3% of analyzable patients). Pathologic assessment was performed by institutional pathologists and was not standardized.

We retrospectively reviewed all cases in the database for this study. SLN surgery dates ranged from 1985 (data from the John Wayne Cancer Institute) to 2007. Variables analyzed for association with a positive SLN included patient age, sex, site of primary tumor, Breslow thickness, Clark level, ulceration, TMR, LVI, vertical growth phase, histologic type, regression, TIL, the number of draining basins, and the number of SLNs collected.

Tumor parameters were entered directly into the database as described on the original pathology reports. Regression was reported as present or absent. LVI was recorded as present if either lymphatic, vascular, or lymphovascular (angiolymphatic) invasion was noted on the pathology report. TMR was entered into the database as a whole number per square millimeter, as reported on local pathology reports. For the purposes of data analysis, TMR was grouped as <1, 1–5, or >5 as reported by Sondak et al.14 and subsequent reports from the University of Michigan.7,11 Because mitoses recorded per high-power field cannot be directly converted to per square millimeter, TMR reported in this manner was not entered into the database. TIL classification was defined in the database as brisk, nonbrisk, and absent as described by Taylor et al.15

All variables were summarized in frequency tables by SLN status. Cutpoints of naturally continuous variables were chosen for consistency with presentations in the literature. Nonparametric loess smoothers were used to visualize the underlying association of continuous variables with SLN positivity. Recursive cubic splines were applied to continuous predictors in single and multivariable modeling, as appropriate. SLN positivity was compared by selected covariates, stratified by Breslow thickness, by Cochran-Mantel-Haenszel analysis. Single and multivariable associations between potential predictors and SLN positivity were estimated by logistic regression with odds ratios representing effect size. For multivariable analysis of SLN positivity, four candidate variables were excluded because >50% of their values were missing (TMR, TIL, vertical growth phase, and histological subtype). Of the 3445 evaluable patients, 1526 (44%) had complete records for the remaining 10 candidate variables and formed the basis of the multivariable selection procedure.

Cluster analysis with the nonparametric Spearman correlation used as the similarity metric was used on the 10 remaining candidate variables to assess the multivariable associations among them. The Spearman correlation was less than 0.2 among all variables, so all 10 variables were included in subsequent variable selection. Bootstrapping (300 replicates) was used to identify the most parsimonious model among 10 candidate variables by backward elimination (P = 0.05 to stay in the model), and to provide shrinkage estimates of model fit criteria (e.g., c-index). P-values are from the Wald chi-square test. Unless otherwise indicated, “significance” implies P-values of <0.05. Statistical analysis was conducted by SAS, version 9.2 (SAS Institute, Cary, NC), and R, version 2.9.1.


A total of 3463 patients were included in the database. Patients without a clear diagnosis of melanoma (e.g., atypical Spitz nevi) were excluded. Patients were also excluded when the results of the SLN biopsy were not in the database. After these exclusions, 3445 patients were included in the overall analysis. The clinical and pathologic characteristics of the patients and tumors are listed in Table 1. Reporting of all variables was well distributed across all institutions. Of the 3445 analyzable patients, 561 (16.3%; 95% confidence interval 15.1–17.5) had a positive SLN biopsy. The likelihood of a positive SLN based on T classification33 is provided in Table 2 (only patients where all variables are known are included). Given the selection bias inherent in the use of T1a and T1b patients as the reference, we elected to use the T2a group, whose patients routinely underwent SLN biopsy.

Patient characteristics by SLN status
SLN incidence by AJCC T classification (7th edition; N = 2426)

The results of the univariate analysis to predict a positive SLN are presented in Table 3. Increasing Breslow thickness, the presence of ulceration, deeper Clark level, the presence of LVI, younger age, >5 mitoses, and male sex were all significant predictors of positive SLN status on univariate analysis. Additionally, tumor location on the trunk and the absence of regression, nodular or acral lentiginous histologic type, and >1 mapped nodal basin were also significant predictors of positive SLNs. Microsatellitosis was excluded from further consideration because it affected less than 4% of the study population (Table 1). From all factors that were significant in the univariate analysis, multivariable analysis with 1526 cases in the model revealed Breslow thickness (P <0.0001), LVI (P <0.0001), ulceration (P = 0.002), age (P = 0.005), trunk location (P = 0.0009), and regression (P = 0.005) to be significant independent predictors of SLN status (Table 4; 257, 16.8%, of these patients had a positive SLN). Among 14 variables, 4 variables (TMR, n = 1192; TIL, n = 823; histological subtype, n = 1683; vertical growth phase, n = 512) were excluded from analysis because of a preponderance of missing values for these variables. In this multivariable analysis, tumor location was found to be significant only when comparing trunk location to head and neck location (P = 0.0009). Patients with trunk tumors were more than twice as likely to have a positive SLN as patients with tumors on the head and neck, whereas there was no difference in SLN positivity when comparing extremity tumors with head/neck tumors.

Univariable logistic regression analysis of factors predicting a positive SLN
Multivariable logistic regression model of factors predicting a positive SLN (n = 1526)

The effects of ulceration alone, LVI and ulceration together, and ulceration with regression stratified by Breslow thickness on the percentage of patients with positive SLNs are presented in Figs. 1, ,2,2, and and3.3. Tumors with LVI and ulceration present a higher risk of SLN metastases across all T categories (P <0.0001).

FIG. 1
Association between ulceration (P <0.0001) and positive SLNs stratified by Breslow thickness; total n = 2781. Numbers above the bars represent the percentage of patients with positive SLNs in each category; numbers below the x-axis labels represent ...
FIG. 2
Associations among lymphovascular invasion (LVI; P <0.0001), ulceration (P <0.003), and positive SLNs by Breslow thickness; total n = 1836. Numbers above the bars represent the percentage of patients with positive SLNs in each category; ...
FIG. 3
Associations among regression (P <0.008), ulceration (P <0.003) and positive SLNs by Breslow thickness; total n = 2003. Numbers above the bars represent the percentage of patients with positive SLNs in each category; numbers below the ...


In our study of 3445 patients, 16.3% had one or more positive SLNs. Reported rates of sentinel node positivity have ranged from 12.66 to 31%.34 The rate noted in this report is consistent with several other large series including those from the Italian Multicenter Study (16.9%),24 the Sydney Melanoma Unit (16.8%),20 and the M. D. Anderson Cancer Center (16.9%).13 In this large multicenter SLNWG dataset increasing Breslow thickness, younger age, trunk tumor location, the presence of LVI or ulceration, and the absence of regression were found to be independent predictors of a positive SLN in multivariate analysis. The findings of Breslow thickness, ulceration, age, and LVI are consistent with previous published reports.1,68,1120,22,23,27

The prognostic significance of regression, particularly in patients with thin melanomas, has been debated for decades. Some studies have found the presence of regression to be a poor prognostic indicator,30,3537 while other studies have found regression to have no effect on the risk of recurrence or survival.3840 On the supposition that the primary tumor was at one time more deeply invasive, the presence of regression in a thin melanoma has been used as justification for SLN biopsy.41 Although Cook et al. and others have suggested that regression may be required for thin melanomas to metastasize,30 other host immune responses, including vitiligo, have been previously shown either to be beneficial on their own or to correlate with a response to systemic therapy.4245 Thus, regression or vitiligo may indicate an autoimmune response to the primary tumor and therefore may be a beneficial prognostic indicator. In accordance with this theory, the presence of regression has been previously found to be statistically significantly associated with a decreased risk of SLN metastases in univariate analysis in several studies.7,11,28,29 One recent large study by Testori et al. confirmed the protective effect of regression on the risk of SLN metastases in a multivariate analysis.24 In the Testori study, the presence of regression was a significant predictor of negative lymph nodes when stratified by Breslow thickness, which contrasts a report from Morris et al. that found regression lost its prediction significance when stratified by Breslow thickness.29 Our current report demonstrating an odds ratio of 2.4 (95% confidence interval 1.3–4.4) further supports the findings of Testori et al.24 on the significance of regression. Together, these large studies lend further credence to the theory that a significant immunologic response in melanoma is suggestive of an improved outcome. Regression in the thin melanoma population was not specifically examined in this report; further study is warranted to elucidate the role of this potential criterion in determining indications for SLN biopsy in patients with thin melanomas.

In our data set, absence of regression and presence of LVI are statistically significant independent predictors of SLN status. In contrast to our results, multiple reports from the Sunbelt Melanoma Trial have found regression carries no significance for predicting SLN metastases.1,8,22 With regard to LVI, an early report from the Sunbelt Melanoma Trial found this factor to be statistically significant in univariate analysis but nonsignificant in multivariate analysis.8 However, in a subsequent report, LVI was found to be significant in multivariate analysis.22 Figure 2 graphically demonstrates the importance of LVI across Breslow depth and in both ulcerated and nonulcerated tumors. LVI was not investigated as a predictive factor in the recent multi-institutional report from Testori et al.24

Two additional variables that have shown promise in predicting SLN status are the TMR6,7,11,14,16,17 and absence of TIL.6,15 Although neither of these factors reached statistical significance in this report, high TMR and the absence of TIL both trended toward predicting a positive SLN. It is possible that the lack of clear significance was related to the relative paucity of data for these factors in this data set; 65% of patients had no data for TMR, and 76% had no data reported for TIL. The reporting of TIL is not required by the College of American Pathologists guidelines,46 and the routine use of mitotic rate began in January 2010 with the adoption of the 7th edition of the American Joint Committee on Cancer Cancer Staging Manual.33 We have updated the current SLNWG database to include these parameters, which will be analyzed in future reports. Given the potential prognostic significance as evidenced by the trends in our report and the significance reported by others,6,7,11,1417 we encourage pathologists to include TIL status on primary melanoma pathology reports.

Limitations of these data include those inherent to a partially retrospective, multi-institutional, multinational report. As is the nature of these types of reports, indications for performing SLN biopsy were not strictly standardized (particularly for the patients with thin lesions), nor was there a single standard procedural approach for SLN biopsy including the methods used by nuclear medicine physicians, surgeons and pathologists. In general, the investigators in this multicenter study used a combination of radioactive colloid and blue dye with preoperative lymphoscintigraphy. One pioneer group in the 1980s initially used blue dye only from November 6, 1985, to October 7, 1992, in 45 patients; thereafter, they used a combination of blue dye and radioactive colloid. For the remaining groups, the usual method was the use of radioactive colloid and blue dye. On some occasions, radioactive colloid was used alone and blue dye omitted. It has been shown that radioactive colloid is far superior in the identification of SLNs to the blue dye.47 Because most of the patients in this multicenter database had radiocolloid used as a tracer for preoperative lymphoscintigraphy and intraoperative gamma probe detection, we believe the results reported are reliable. Furthermore, to date, the absolute standard of the technique for SLN identification has not been established and agreed on by the experts in the field. Similarly, the pathology reports were not standardized. All the pathology assessment was performed by institutional pathologists; however, the conventional method to process the SLN and identify micrometastasis was similar in that multiple level sections were made and stained with hematoxylin and eosin. If negative, immunochemistry was performed. Given the varied interests of the investigators and/or their institutions, for some aspects of this report, only small cohorts were studied. Standard definitions of some variables (e.g., TMR, TIL) did not exist. No strict criteria were used in patients with T1a lesions who underwent SLN biopsy (Table 2), limiting extrapolation of this information. Despite these limitations, we believe the data we present here are representative of the broad spectrum of current practice. In the future, a central pathologist may be recruited to review the slides for these specific factors to achieve uniformity among different centers.

This large data set from the SLNWG represents 17 institutions from around the world. Our findings suggest reemphasizing the importance of pathologic factors such as LVI and regression, in addition to the well-established factors of ulceration and Breslow thickness, when selecting candidates for SLN biopsy and estimating the risk of involved lymph nodes.


This study is supported in part by an educational grant from Schering Oncology. The authors thank Cissy Swartz for her editorial and logistic assistance.


This study is conducted for the Sentinel Lymph Node Working Group

Portions of this study were presented in part at the Sixth Biennial International Sentinel Node Society Meeting, Sydney, Australia, February 18–20, 2008.

DISCLOSURE Merck/Schering Oncology Speakers Bureau: Drs. White, Gershenwald, Charney, Hauschild, Vetto, Whitman and Kashani-Sabet. Dr. Leong is a Neoprobe contract recipient.

CONFLICT OF INTEREST Mr. Ayers, Ms. Stell, Drs. Soong, Ding, Salo, Pockaj, Essner, Faries, Averbook, Avisar, Egberts, Garberoglio, Ross, Chu, Trisal, Hoekstra, Wanebo, DeBonis, Vezeridis, Chevinsky, Shyr, Berry, and Zhoa indicate no potential conflicts of interest.


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