Association of Sentinel Lymph Node Biopsy With Survival for Head and Neck Melanoma: Survival Analysis Using the SEER Database

Importance  Sentinel lymph node biopsy (SLNB) provides prognostic information for melanoma; however, a survival benefit has not been demonstrated.

Objective  To assess the association of SLNB with survival for melanoma arising in head and neck subsites (HNM).

Design, Setting, and Participants  Propensity score–matched retrospective cohort study using the Surveillance Epidemiology and End Results (SEER) database to compare US patients with HNM meeting current recommendations for SLNB, treated from 2004 to 2011 with either (1) SLNB with or without neck dissection, or (2) no SLNB or neck dissection.

Interventions  SLNB with or without neck dissection.

Main Outcomes and Measures  Disease-specific survival (DSS) estimates based on the Kaplan-Meier method, and Cox proportional hazards modeling to compare survival outcomes between matched pair cohorts.

Results  A total of 7266 patients with HNM meeting study criteria were identified from the SEER database. Matching of treatment cohorts was performed using propensity scores modeled on 10 covariates known to be associated with SLNB treatment or melanoma survival. Cohorts were stratified by tumor thickness (thin, >0.75-1.00 mm Breslow thickness; intermediate, >1.00-4.00 mm; and thick, >4.00 mm) and exactly matched within 5 age categories. In the intermediate-thickness cohort, 2808 patients with HNM were matched and balanced by propensity score for SLNB treatment; the 5-year DSS estimate for those treated by SLNB was 89% vs 88% for nodal observation (log-rank P = .30). The hazard ratio for melanoma-specific death was 0.87 for those undergoing SLNB (95% CI, 0.66-1.14; P = .31). In each of the other cohorts analyzed, including those with thin and thick melanomas, and cohorts with melanoma overall, no significant difference in DSS was demonstrated.

Conclusions and Relevance  This SEER cohort analysis demonstrates no significant association between SLNB and improved disease-specific survival for patients with HNM.

There were an estimated 68 000 new melanoma cases in the United States in 2010, and the incidence seems to be increasing.¹ At diagnosis, 82% of patients have localized disease, while in 11% disease has already spread to regional sites.² Any regional lymph node metastasis in melanoma decreases survival.³ Sentinel lymph node biopsy (SLNB) for melanoma was introduced in the early 1990s to identify the presence of occult regional metastatic disease.⁴ The procedure has been shown to provide important prognostic information^3,5 and obviates the need for elective regional node dissection in most patients.⁶ Patients with a positive result from an SLNB may be offered more aggressive treatment, including regional node dissection, other adjuvant therapy, or enrollment in clinical trials. Quiz Ref IDAlthough SLNB identifies patients with microscopic nodal disease, improves regional disease control,⁷ and may facilitate the escalation of treatment, it is still controversial whether there is any therapeutic benefit of the procedure, especially in terms of survival.^8-10 In fact, the only randomized clinical (RCT) to evaluate the question of a survival benefit demonstrated no difference in disease-specific survival (DSS) for those treated with an SLNB for intermediate-thickness melanoma.^11,12 A criticism of the trial has been that it was underpowered to detect a small but clinically significant survival effect.¹³

Quiz Ref IDAnother adequately powered RCT to assess survival of those treated with SLNB for melanoma is likely impossible, owing to the size of study necessary to detect a small treatment difference and that the SLNB intervention is now widely practiced as the standard of care for the diagnostic information it provides, so enrolling patients into an RCT to assess therapeutic effect is unlikely to succeed. The Surveillance Epidemiology and End Results (SEER) database provides prospectively collected and updated patient data from 18 registries, representing nearly 26% of the population of the United States. Although an RCT is ideal for comparing the effects of treatment because it controls for confounding factors through the randomization of treatment assignment, an observational study can approximate an RCT if bias in treatment assignment is controlled, using methods such as a propensity score matched pairs design.

Eighteen percent of new melanoma cases occur in the head and neck.¹⁴ There are multiple lines of evidence suggesting that head and neck melanoma (HNM) behaves differently from melanoma in other skin sites. Quiz Ref IDFor example, patients with HNM have worse survival rates than those with trunk or extremity melanoma.^14-16 The decision to perform SLNB for HNM poses unique considerations. A lower rate of SLNB positivity in HNM has been reported (10% vs 17%-19% for trunk or extremity in 1 study).^14-16 In addition, patients with HNM with a negative result from SLNB have worse survival and less of an absolute survival difference relative to patients with positive results from SLNB than those with melanoma in other body sites.¹⁶ A higher false-negative rate for SLNB in HNM also has been reported in several studies.^16-18 Therefore, the prognostic information from performing SLNB may not be as valuable for HNM as in other body sites, and the relative benefit to patients of undergoing the surgical procedure should be carefully evaluated.

Given the small sample size of the previously conducted RCT,^11,12 and the lack of other published studies on this important clinical question, particularly for HNM, we sought to use a large, national population-based data set (SEER) to compare the survival of patients treated with SLNB for HNM with those who did not undergo any initial treatment of the regional lymphatics, controlling for bias in treatment selection. The hypothesis was that SLNB as part of initial treatment for HNM has no association with melanoma DSS relative to observation.

Data from the SEER Program of the National Cancer Institute Public Use Data set were extracted for patients with a primary diagnosis of invasive melanoma (International Classification of Diseases for Oncology, Third Edition codes 8720-8723, 8726, 8730, 8740-8745, 8760, 8761, 8770-8774, and 8780). The SEER data were obtained from population-based prospective tumor registries in the following areas from 2004 to 2011: the metropolitan areas of San Francisco–Oakland, Los Angeles County, and the San Jose-Monterey area; Detroit, Michigan; Atlanta, Georgia; and Seattle, Washington; and rural Georgia; the Alaska Native Registry; Greater California; Greater Georgia; and the states of Connecticut, Kentucky, Iowa, Louisiana, New Jersey, New Mexico, Utah, and Hawaii. The data were accessed from SEER on May 9, 2014. The data used in this study are public access and deidentified, and therefore this study was granted exemption from institutional review board oversight by the University of Iowa.

The intention of the selection criteria for this study was to include patients who would have been offered an SLNB in the treatment of their melanoma based on current national consensus guidelines in the United States. The National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology for Melanoma¹⁹ currently recommends SLNB for patients with stage IB-II melanoma (ie, 0.76-1.00 mm thick with ulceration or ≥1 mitosis/mm², or >1.00 mm thick with or without ulceration). The NCCN guidelines suggest that SLNB be considered for patients with stage IA melanoma with tumor thickness greater than 0.75 mm; for other stage IA melanomas, it is controversial whether SLNB should be offered, and for which adverse factors (eg, positive deep margins, lymphovascular invasion, mitoses, or Clark level IV or V). Patients were selected for this study if they qualified for SLNB based on these recommendations, limiting selection of stage IA melanomas to those greater than 0.75 mm in thickness.

Patients were also required to have had at least an excision of the primary melanoma. Those with distant metastatic disease, regional disease, in-transit metastasis, or satellitosis at presentation, as well as patients who underwent a neck dissection without SLNB or underwent needle biopsy of lymph nodes without SLNB, were excluded. Patients younger than 18 years were excluded. Patients older than 85 years were also excluded because they are less likely to undergo SNLB and their survival rate is lower; it was not possible to control this bias by matching.

Two treatment groups were considered: a control group, which had no SLNB or other lymph node dissection performed, and the intervention group, which underwent an SLNB and possibly additional lymph node dissection. The SEER database recorded whether an SLNB was performed for melanoma beginning in 1998, in the variables “Scope of regional lymph nd surg (1998-2002)” and “Rx Summ—Scope Reg LN Sur (2003+).” However, it has been recognized that the receipt of SLNB vs neck dissection may have been inconsistently coded in the years 1998 to 2002, with patients undergoing both procedures coded only as having undergone neck dissection by coding rules.¹³ In addition, SEER introduced the “CS Site-Specific Factor 3” variable for melanoma in 2004, which identifies lymph node metastases as clinically occult vs clinically evident, allowing for consistently accurate inclusion for this study. Consequently, the years of inclusion for the study are 2004 to 2011.

To control for confounding factors and minimize bias in the initial treatment selection from influencing the observed outcome, the 2 cohorts were matched using propensity scores and the prognostic factors available at the time of diagnosis. Propensity score computation should include those variables that affect the outcome or those that affect both treatment selection and the outcome.²⁰ Variable selection for the propensity model was limited to the information available within the SEER database during all of the years of the study and included variables that have been shown to be related to treatment with an SLNB or to survival, which include age,^21-25 race,²¹ sex,^26-28 marital status,²¹ scalp location,^14,22,29,30 tumor registry,²¹ histology,² thickness,^3,31 and ulceration.³¹ The variables incorporate patient-specific, tumor-specific, and regional characteristics, which form a theoretical basis for bias in treatment selection. In addition, we used a SEER variable indicating whether the case was the patient’s first malignant neoplasm because we hypothesized that this may have some influence on the choice of treatment.

Dichotomous variables were created for marital status, race (white or other), sex, tumor location (face vs scalp and/or neck), any prior malignant neoplasm (yes or no), and ulceration. There were 18 tumor registries that contributed patients to this study; these were dichotomized according to whether they were above or below the median proportion of melanoma cases in the registry undergoing SLNB. Histologic type was grouped in categories for the major melanoma histologic types (superficial spreading, nodular, desmoplastic, lentigo maligna, not otherwise specified, and other). Age and Breslow thickness were considered as continuous variables. They were separately also stratified into categories, with stratification of Breslow thickness based on the American Joint Committee on Cancer TNM classification system, and age categories 18 to 44, 45 to 54, 55 to 64, 65 to 74, and 75 to 84 years.

The initial data analysis evaluated treatment selection, focusing on whether SLNB was performed. To control for confounding factors and minimize bias in the initial treatment selection from influencing the observed outcome, the 2 cohorts were matched using propensity scores calculated by logistic regression using the covariates discussed herein. A greedy nearest-neighbor matching algorithm with calipers set at 0.1 SD of the logit of the propensity score was used to create matched pairs. In addition, cases were required to be matched exactly within age categories, defined as 18 to 44, 45 to 54, 55 to 64, 65 to 74, and 75 to 84 years. This requirement created perfect balance between the control and treatment groups within each age category. The balance of the matched model was assessed, and further refinements of the matching model were made iteratively. The standardized difference of the means for each covariate, as well as for interaction terms of the covariates, were computed. Some authors suggest that a difference of more than 25% be used to represent meaningful imbalance among the treatment groups; others suggest using more than 10% as a balancing measure.^32,33 Dot plots of the propensity score and standardized differences of covariates were generated for comparisons. The balance was also checked through statistical tests, including Hansen-Bower omnibus imbalance test statistic,³⁴ or a comparison of the L₁ balance measure prematching and postmatching, which is calculated by an automatic binning of all covariates and comparing frequencies in a multivariate contingency table of the treatment vs nontreatment groups.³⁵ The propensity score modeling and matching was repeated for subsequent cohorts based on Breslow thickness, defined as thin (>0.75-1.00 mm), intermediate (>1.00-4.00 mm), and thick (> 4.00 mm) (hereinafter, thin, intermediate, and thick cohorts). The propensity score calculation and matching were performed with the software extension Propensity Score Matching for SPSS, version 3.02 (SPSS Inc, an IBM Co),³⁶ which uses the R software programs Matchit, RItools, and CEM.^34,35,37-39

The baseline covariates were analyzed for the overall study population, and the treatment groups before and after matching, comparing prevalence for categorical variables and the means (SDs) for continuous variables. Survival was the main outcome measure, which was assessed only once the treatment groups had been matched and balanced optimally. Survival estimates were created by the Kaplan-Meier method and compared using the log-rank test. Assessment of the effect of covariates on survival was accomplished on the paired data using a Cox proportional hazards model using a robust sandwich variance estimator to compare the matched pair survival durations. Formal sensitivity analysis was performed as described elsewhere.⁴⁰ Statistical analyses were performed using SPSS software, SAS software (version 9.3; SAS Institute Inc), and R (http://www.R-project.org/).

A total of 7266 patients with HNM were initially identified from the SEER database and met the study criteria (Table 1). Of these patients, 46% did not undergo SLNB, and 54% did. When stratified based on intervention with SLNB or not, the treatment groups were significantly different from one another for every variable under consideration. Propensity scores for undergoing SLNB were calculated by logistic regression on 10 covariates, and 1:1 matching of observation and treatment cases was completed, resulting in 2551 matched pairs (Figure 1). Covariate balance within the groups was achieved, as demonstrated by the improvement in all standardized differences for each covariate, and all absolute values of the standardized differences of the covariates being less than 0.1 (Figure 2). The characteristics of the observation and treatment groups and standardized differences were compared after matching (Table 1). In addition, the distributions for the continuous variables age and Breslow thickness were compared (eFigure 1 and eFigure 2 in the Supplement). Bower-Hansen omnibus balance statistic suggested no significant imbalance between the treatment cohort (χ² = 5.09; P = .99), and the L₁ measure decreased before and after matching (from 0.850 to 0.847).

However, because of remaining differences in the percentage of SLNB in each of the Breslow thickness categories, and the known differences in survival based on Breslow thickness, each Breslow category separately underwent propensity score matching and analysis, as for the overall study group. The thin, intermediate, and thick cohorts were each well balanced on all of the remaining covariates following the matching procedure, and the characteristics of each separate cohort were analyzed (for data on the intermediate cohort, see the eTable in the Supplement).

Disease-specific survival was compared in each of the matched cohorts. In the intermediate cohort, which included 2808 patients, the 5-year DSS estimate was 89% vs 88% for SLNB vs observation, respectively (log-rank test P = .30). In each of the other cohorts analyzed, including for thin or thick melanoma, no significant difference in DSS was demonstrated either (P = .25 and .22, respectively) (Figure 3). The 5-year DSS estimate for thin melanoma was 96%, and for thick melanoma 70%.

The effect of SLNB on DSS was assessed in a Cox proportional hazards model in each matched pair cohort (Table 2). For the intermediate cohort, the hazard ratio (HR) of death from melanoma in the SLNB group was 0.87 (95% CI, 0.66-1.14; P = .31). Similarly, the disease-specific HR for the SLNB group in the thick cohort was 0.80 (95% CI, 0.56-1.15; P = .23). There was also no statistically significant association between SLNB and DSS in the overall group, or for thin melanomas (P = .50 and .24, respectively).

For the patients who underwent SLNB for HNM, 7.4% overall had microscopic nodal metastases identified (Table 3). This rate varied significantly by Breslow thickness, from 2.9% for thin melanomas, 7.1% for intermediate melanomas, and 11% for thick melanomas. The rate of positive nodes following SLNB also varied significantly by age category in the intermediate melanoma cohort, varying in frequency from 11% to 14% for ages 18 to 64 years, but decreasing to 6% for ages 65 to 74 years and to 4% for ages 75 to 84 years. The rate of positive nodes in the intermediate cohort were also significantly less for those with melanoma of the face; desmoplastic or lentigo maligna histologic findings; or who were married. Those who had a positive occult nodal metastasis identified by SLNB were more likely to be treated with a neck dissection in the intermediate and thick cohorts and more likely to receive radiation in the intermediate cohort but not the thick cohort. Having a positive SLNB result was associated with melanoma-specific death.

Quiz Ref IDOur findings based on propensity score–matched pair cohorts of patients with HNM suggest there is no significant association between SLNB and DSS for patients with HNM ages 18 to 84 years with Breslow thickness 0.76 mm or greater. The HRs of 0.87 for intermediate melanoma and 0.80 for thick melanoma indicates that undergoing SLNB may be associated with decreased odds of death from melanoma. However, there is no statistically significant relationship identified for either of these cohorts in this SEER analysis.

Quiz Ref IDOne interpretation of such HRs is that for 2 identical patients with an intermediate-thickness melanoma with baseline equal probability of dying, the patient undergoing nodal observation has a 54% chance of dying from melanoma before the one having an SLNB. However, death from melanoma is a relatively uncommon event in this population, occurring in only 88% at 5 years, as indicated by the Kaplan-Meier survival estimates. So, not only is no statistically significant association between DSS and SLNB seen in this analysis, but the estimated size of such an association is predicted to be a small change in the probability of an uncommon event, and therefore the clinical significance of such an association would be minimal.

Our results are consistent with those of previous studies. The Multicenter Selective Lymphadenectomy Trial-1 (MSLT-1),¹¹ an RCT comparing SLNB with observation in 1270 patients with melanoma with Breslow thicknesses of 1.2 to 3.5 mm of all body sites, recently published final results with 10-year survival data. Of patients in this study, 17% had HNM. In the main study outcome the investigators did not demonstrate a significant difference in melanoma DSS between the treatment arms. However, they did demonstrate a trend toward reduced risk of death from melanoma with SLNB, with an HR of 0.84, which is similar to the effect size seen in our analysis. We found a 5-year DSS for intermediate-thickness HNM similar to the 5-year DSS of 87% seen in the MSLT-1 trial.¹² It has been suggested that the MSLT-1 trial was underpowered to detect a small but clinically significant survival difference.¹³ Even though this study evaluated more cases than the MSLT-1 trial, based on the small estimated treatment effect, it is likely that it too is underpowered to identify a significant association. If we were to design an RCT to validate this small difference in survival between SLNB and observation in a similar design as the MSLT-I trial, with 5-year follow-up and a power of 90%, based on an estimated HR of 0.80, it would require randomization of 6500 patients (assigning 60% to SLNB and 40% to observation, as in the MSLT-1).

To our knowledge, no other observational studies have used SEER to compare the survival of patients who undergo SLNB. Other than the aforementioned prospective RCT,¹¹ only 1 other study has specifically studied the survival effect of SLNB compared with nodal observation. A single-institution retrospective case series⁴¹ from Germany examined 673 primary melanoma patients with Breslow thickness greater than 1 mm, 377 treated prior to 2000 without SLNB and 296 after 2000 who underwent SLNB when the practice pattern at the institution changed. The measured patient characteristics across the time periods were reported to be otherwise similar; however, there was no other attempt to control for differences between the cohorts, except by the temporal separation of the patients into different treatment paradigms. For the cohort treated with SLNB, the investigators⁴¹ reported significantly improved recurrence-free survival, distant metastasis–free survival, and overall survival, and a trend toward improved melanoma DSS. Only 10% of the patients in that study had HNM.

We note that a previous study¹³ attempted to analyze the SEER data from 1998 to 2002 to determine the association of SLNB with survival for melanoma of all body sites.¹³ However, the study was not published owing to issues with the coding algorithm by which SEER indicated SLNB status. We likewise recognized there to be an issue with SEER-data from 1998 to 2002 and avoided the potential miscategorization of patients who underwent SLNB plus completion lymphadenectomy by excluding the patients treated from 1998 to 2002.

The critical assumption in using propensity-score matched observational data to make inferences about treatment effects is that one has accounted for all possible variables that influence treatment assignment.⁴² If this assumption is true, then after achieving evenly matched and balanced cohorts, one can attribute the difference in outcome to the intervention, as one would in a randomized controlled experiment. However, in reality it is improbable that every possible variable influencing the treatment assignment is measured and accounted for.

There could reasonably be many such factors that one could speculate might be confounding the results of this study: one would be treatment in a highly experienced center with specialists in the field; another might be access to adjuvant treatment in clinical trials, which incorporate performance of SLNB as inclusion criteria. Another possible confounder is comorbidity, which would influence the performance of a surgical procedure (eg, SLNB) and the aggressiveness of other treatments for melanoma. Comorbidity information is not collected in the SEER database, and its absence from inclusion in the propensity model is a limitation of this study.

There are several other limitations of our analysis based on SEER data. The presence of mitoses was not recorded in SEER during the period of the study, and this information might have helped stratify patients, especially in the cohort with Breslow thickness of 0.75 to 1 mm. In addition, the SEER data record staging only at diagnosis and initial treatment, so information is not available regarding subsequent development of lymph node metastasis. Finally, while the SEER registries have well-managed data collection systems and quality control practices, the accuracy and quality control for the clinical and pathologic source information is less well defined, and inaccuracies can enter the system at many different points.^43,44

The strengths of the current study include the large, geographically diverse sample likely to be representative of the US population; the inclusion of patients regardless of the type of institution at which they were treated; the well-established, high-quality data captured by SEER registries; and the carefully designed and conducted methodology to control for potential sources of bias impacting SLNB intervention through propensity score matching. To our knowledge, this study is the largest sample of patients with HNM to assess the association of SLNB on survival. With these strengths, this study has not identified a statistically significant association between treatment including SLNB and improved DSS for HNM; furthermore, we suggest that the size of the association is unlikely to be clinically relevant for patients. It is unlikely that another RCT with adequate power will ever be designed to answer this question. Therefore, observational data analyses, such as those presented herein, may remain the best level of evidence regarding this important clinical question for HNM. While the potential limitations associated with unmeasured confounders must be considered, our results do not provide evidence to warrant further study to assess the therapeutic survival benefit of SLNB for HNM.

This SEER propensity score–matched cohort analysis fails to demonstrate an association with improved survival for patients with HNM who undergo SLNB rather than nodal observation.

Corresponding Author: Nitin A. Pagedar, MD, MPH, Department of Otolaryngology–Head and Neck Surgery, University of Iowa, 200 Hawkins Dr, Iowa City, IA 52242 (nitin-pagedar@uiowa.edu).

Submitted for Publication: March 22, 2014; final revision received June 11, 2014; accepted July 10, 2014.

Published Online: October 16, 2014. doi:10.1001/jamaoto.2014.2530.

Author Contributions: Drs Sperry and Pagedar had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Sperry, Pagedar.

Acquisition, analysis, or interpretation of data: Sperry, Charlton.

Drafting of the manuscript: Sperry.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Sperry, Charlton, Pagedar.

Study supervision: Pagedar.

Conflict of Interest Disclosures: None reported.

Previous Presentation: The abstract for this article was presented at the 2014 American Head and Neck Society Annual Meeting and Fifth World Congress; July 27, 2014; New York, New York (Abstract 58306).