Relationship between age and likelihood of lymph node metastases in patients with intermediate thickness melanoma (1.01-4.00 mm): A National Cancer Database study

Sentinel lymph node biopsy is unreliable in predicting melanoma mortality for both younger and older patients

BACKGROUND

Melanoma disease patterns vary with patient age.

AIM

To evaluate sentinel lymph node biopsy (SLNB) in managing melanoma at differing patient ages.

METHODS

Online prediction tools were applied to compare SLNB positivity (SLNB+) and survival risk at patient ages 20-80. Tübingen melanoma data were used to determine variations in the hazard ratio of SLNB+ for mortality at different patient ages.

RESULTS

Regardless of tumour thickness, predicted SLNB+ rates were markedly higher than mortality rates for 20-year-old patients. For 80-year-old patients, it is the opposite.

DISCUSSION

If 1000 20-year-olds with a 0.4 mm thickness non-ulcerated melanoma underwent SLNB, 100 would likely be positive. If all 100 were to be offered adjuvant drug therapy (ADT), fewer than three more melanoma deaths in those 1000 patients would be avoided. In total, 97 patients would have received medication they may never have needed. If 1000 80-year-olds with a 3 mm thickness non-ulcerated melanoma underwent SLNB, only 40 would likely be positive. In total, 274 patients would be predicted to die of melanoma, 245 being SLNB negative and 29 SLNB+. ADT linked to SLNB+ could deny treatment to 89% of these high-risk patients.

LIMITATIONS

The authors relied on published risk data.

CONCLUSION

SLNB has poor specificity at predicting mortality in young melanoma patients and poor sensitivity in older patients. SLNB is not indicated in managing cutaneous melanoma for patients under 40 or over 60 years of age. Many such patients could be managed with wide local excision alone in their clinician's office-based practice. For all cutaneous melanoma patients at all ages, linking ADT to BAUSSS biomarker, (an algorithm of Breslow thickness, age, ulceration, subtype, sex and Site) rather than SLNB+ is likely more appropriate. BAUSSS provides a more accurate melanoma-specific mortality risk assessment for patients without burdening them with added surgery, hospitalization, costs or morbidity risk.

Deep learning-based pathology signature could reveal lymph node status and act as a novel prognostic marker across multiple cancer types

BACKGROUND

Identifying lymph node metastasis (LNM) relies mainly on indirect radiology. Current studies omitted the quantified associations with traits beyond cancer types, failing to provide generalisation performance across various tumour types.

METHODS

4400 whole slide images across 11 cancer types were collected for training, cross-verification, and external validation of the pan-cancer lymph node metastasis (PC-LNM) model. We proposed an attention-based weakly supervised neural network based on self-supervised cancer-invariant features for the prediction task.

RESULTS

PC-LNM achieved a test area under the curve (AUC) of 0.732 (95% confidence interval: 0.717-0.746, P < 0.0001) in fivefold cross-validation of multiple cancer types, which also demonstrated good generalisation in the external validation cohort with AUC of 0.699 (95% confidence interval: 0.658-0.737, P < 0.0001). The interpretability results derived from PC-LNM revealed that the regions with the highest attention scores identified by the model generally correspond to tumours with poorly differentiated morphologies. PC-LNM achieved superior performance over previously reported methods and could also act as an independent prognostic factor for patients across multiple tumour types.

DISCUSSION

We presented an automated pan-cancer model for predicting the LNM status from primary tumour histology, which could act as a novel prognostic marker across multiple cancer types.

Sentinel lymph node biopsy status improves adjuvant therapy decision-making in patients with clinical stage IIB/C melanoma: A population-based analysis

BACKGROUND

Given the results of the recent KEYNOTE-716 trial, the performance of sentinel lymph node (SLN) biopsy for patients with clinical stage IIB/C melanoma has been questioned.

OBJECTIVE

Determine the utility of SLN status in guiding the recommendations for adjuvant therapy.

METHODS

Patients with clinical stage IIB/C cutaneous melanoma who underwent wide local excision and SLN biopsy between 2004 and 2011 were identified from the Surveillance, Epidemiology, and End Results database. Two prognostic models, with and without SLN status, were developed predicting risk of melanoma-specific death (MSD). The primary outcome was net benefit at treatment thresholds of 20% to 40% risk of 5-year MSD.

RESULTS

For the 4391 patients included, the 5-year MSD rate was 46%. The model estimating 5-year MSD risk that included SLN status provided greater net benefit at treatment thresholds from 30% to 78% compared to the model without SLN status. The added net benefit for the SLN biopsy-containing model persisted in subgroup analysis of patients in different age groups and with various T stages.

LIMITATIONS

Retrospective study.

CONCLUSIONS

A prognostic model with SLN status estimating patient risk for 5-year MSD provides superior net benefit compared to a model with primary tumor staging factors alone for threshold mortality rates ≥30%.

Sentinel lymph node biopsy in patients with T1a cutaneous malignant melanoma: A multicenter cohort study

BACKGROUND

Sentinel lymph node biopsy is not routinely recommended for T1a cutaneous melanoma due to the overall low risk of positivity. Prognostic factors for positive sentinel lymph node (SLN⁺) in this population are poorly characterized.

OBJECTIVE

To determine factors associated with SLN⁺ in patients with T1a melanoma.

METHODS

Patients with pathologic T1a (<0.80 mm, nonulcerated) cutaneous melanoma from 5 high-volume melanoma centers from 2001 to 2020 who underwent wide local excision with sentinel lymph node biopsy were included in the study. Patient and tumor characteristics associated with SLN⁺ were analyzed by univariate and multivariable logistic regression analyses. Age was dichotomized into ≤42 (25% quartile cutoff) and >42 years.

RESULTS

Of the 965 patients identified, the overall SLN⁺ was 4.4% (N = 43). Factors associated with SLN⁺ were age ≤42 years (7.5% vs 3.7%; odds ratio [OR], 2.14; P = .03), head/neck primary tumor location (9.2% vs 4%; OR, 2.75; P = .04), lymphovascular invasion (21.4% vs 4.2%; OR, 5.64; P = .01), and ≥2 mitoses/mm² (8.2% vs 3.4%; OR, 2.31; P = .03). Patients <42 years with ≥2 mitoses/mm² (N = 38) had a SLN⁺ rate of 18.4%.

LIMITATIONS

Retrospective study.

CONCLUSION

SLN⁺ is low in patients with T1a melanomas, but younger age, lymphovascular invasion, mitogenicity, and head/neck primary site appear to confer a higher risk of SLN⁺.

Age and Melanocytic Lesions

Age plays a dynamic role in incidence, presentation, and extent of disease for cutaneous melanoma. Even within the spectrum of juvenile melanoma, there exists a range of spitzoid and nonspitzoid melanocytic and melanoma lesions. Spitzoid melanomas, a more favorable disease in juvenile patients, are malignant lesions and require treatment as such. Lymph node metastases in melanoma occur at lower rates in older patients compared with younger counterparts, yet the rate of metastases is still high. Age appears to play an important role in the development and progression of melanoma, and understanding the differences across age populations is important when counseling patients.

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours

AIM

Sentinel lymph node status is a central prognostic factor for melanomas. However, the surgical excision involves some risks for affected patients. In this study, we therefore aimed to develop a digital biomarker that can predict lymph node metastasis non-invasively from digitised H&E slides of primary melanoma tumours.

METHODS

A total of 415 H&E slides from primary melanoma tumours with known sentinel node (SN) status from three German university hospitals and one private pathological practice were digitised (150 SN positive/265 SN negative). Two hundred ninety-one slides were used to train artificial neural networks (ANNs). The remaining 124 slides were used to test the ability of the ANNs to predict sentinel status. ANNs were trained and/or tested on data sets that were matched or not matched between SN-positive and SN-negative cases for patient age, ulceration, and tumour thickness, factors that are known to correlate with lymph node status.

RESULTS

The best accuracy was achieved by an ANN that was trained and tested on unmatched cases (61.8% ± 0.2%) area under the receiver operating characteristic (AUROC). In contrast, ANNs that were trained and/or tested on matched cases achieved (55.0% ± 3.5%) AUROC or less.

CONCLUSION

Our results indicate that the image classifier can predict lymph node status to some, albeit so far not clinically relevant, extent. It may do so by mostly detecting equivalents of factors on histological slides that are already known to correlate with lymph node status. Our results provide a basis for future research with larger data cohorts.

Sentinel lymph node biopsy in melanoma: beyond histologic factors

Sentinel lymph node (SLN) biopsy should be performed with the technical expertise required to correctly identify the sentinel node, in the context of understanding both the likelihood of positivity in a given patient and the prognostic significance of a positive or negative result. National Comprehensive Cancer Network guidelines recommend SLN biopsy for all cutaneous melanoma patients with primary tumor thickness greater than 1 mm and in select patients with thickness between 0.8 and 1 mm, yet admit a lack of consistent clarity in its utility for prognosis and therapeutic value in tumors < 1 mm and leave the decision for undergoing the procedure up to the patient and treating physician. Recent studies have evaluated specific patient populations, tumor histopathologic characteristics, and gene expression profiling and their use in predicting SLN positivity. These data have given insight into improving the physician's ability to potentially predict SLN positivity, shedding light on if and when omission of SLN biopsy in specific patients based on clinicopathological characteristics might be appropriate. This review provides discussion and insight into these recent advancements.

Relationship of patient age to tumor factors and outcomes among patients undergoing sentinel node biopsy for melanoma

INTRODUCTION

Patient age has been intermittently associated with demographics and outcomes in cutaneous melanoma. We looked at the association of age and patient demographics, tumor features, and melanoma-related outcomes in patients undergoing sentinel lymph node (SLN) biopsy for melanoma.

METHODS

We reviewed demographics (age, gender), tumor features (mean Breslow thickness, ulceration, SLN positivity rates), and outcomes (all-site relapse, progression to stage IV, death from melanoma, complications) from a university-based prospective database of 1633 patients. Patients were grouped by decade of age and the impact of age was examined by univariable and multivariable analyses.

RESULTS

Increasing age was directly associated with number of patients referred for SLN biopsy, male gender, head and neck (H&N) tumor location, mean Breslow thickness, tumor ulceration, and with all -site relapse, progression to stage IV, death from melanoma and complication rates. Increasing age was indirectly associated with SLN positivity rates. Comparing ages <30 with ages >60, these trends reached statistical significance for male gender, H&N location, SLN positivity, all-site relapse, progression to stage IV (development of metastases) and death from melanoma.

CONCLUSIONS

Referrals for SLN biopsy increase with increasing patient age, yet increasing age is associated with lower SLN positivity rates. This occurs despite the fact that older patients have thicker, more ulcerated tumors, and higher melanoma-related relapse and death rates.

Model Combining Tumor Molecular and Clinicopathologic Risk Factors Predicts Sentinel Lymph Node Metastasis in Primary Cutaneous Melanoma

PURPOSE

More than 80% of patients who undergo sentinel lymph node (SLN) biopsy have no nodal metastasis. Here we describe a model that combines clinicopathologic and molecular variables to identify patients with thin and intermediate thickness melanomas who may forgo the SLN biopsy procedure due to their low risk of nodal metastasis.

PATIENTS AND METHODS

Genes with functional roles in melanoma metastasis were discovered by analysis of next generation sequencing data and case control studies. We then used PCR to quantify gene expression in diagnostic biopsy tissue across a prospectively designed archival cohort of 754 consecutive thin and intermediate thickness primary cutaneous melanomas. Outcome of interest was SLN biopsy metastasis within 90 days of melanoma diagnosis. A penalized maximum likelihood estimation algorithm was used to train logistic regression models in a repeated cross validation scheme to predict the presence of SLN metastasis from molecular, clinical and histologic variables.

RESULTS

Expression of genes with roles in epithelial-to-mesenchymal transition (glia derived nexin, growth differentiation factor 15, integrin β3, interleukin 8, lysyl oxidase homolog 4, TGFβ receptor type 1 and tissue-type plasminogen activator) and melanosome function (melanoma antigen recognized by T cells 1) were associated with SLN metastasis. The predictive ability of a model that only considered clinicopathologic or gene expression variables was outperformed by a model which included molecular variables in combination with the clinicopathologic predictors Breslow thickness and patient age; AUC, 0.82; 95% CI, 0.78-0.86; SLN biopsy reduction rate of 42% at a negative predictive value of 96%.

CONCLUSION

A combined model including clinicopathologic and gene expression variables improved the identification of melanoma patients who may forgo the SLN biopsy procedure due to their low risk of nodal metastasis.

High level of TILs is an independent predictor of negative sentinel lymph node in women but not in men

Factors that are most associated with positive lymph node status in melanoma are Breslow thickness and ulceration. However, there are other factors that have been little explored and could help in the identification of "at risk patients" harbouring occult metastasis. The objective of this study was to determine whether intensity of tumour-infiltrating lymphocytes (TILs) in a cohort study (N = 4133) is an independent predictor of sentinel lymph node (SLN) status in patients with primary cutaneous melanoma. Of the patients with cutaneous melanoma who resulted negative for nodal metastasis, 50.7% had moderate/marked TILs versus 27.7% among those patients who resulted positive for nodal metastasis. In the multivariate analysis, controlling for sex, age, mitotic rate, ulceration and Breslow, high levels of TILs in primary invasive melanoma was associated with a lower risk of developing SLN metastasis (OR 0.46; 95% CI 0.23-0.95, p = 0.037). When the analysis was stratified by sex, the protective effect of moderate/marked TIL remained only for women (OR 0.30; 95% CI 0.10-0.93, p = 0.037) but not for men (OR 0.51; 95% CI 0.19-1.34, p = 0.172). Other independent predictors of negative lymph node were low Breslow thickness (≤ 2.0 mm) and low mitotic rate. Besides predicting a negative lymph node response, TILs were also associated with a decreased risk of 10-year mortality among females with positive lymph node. Our findings suggest that high level of TILs is an independent predictor of negative SLN status among women. Further research is warranted to confirm our findings.

Practice Patterns and Prognostic Value of Sentinel Lymph Node Biopsy for Thick Melanoma: A National Cancer Database Study

BACKGROUND

Sentinel lymph node biopsy (SLNB) has been somewhat controversial for patients with a diagnosis of thick (> 4 mm) melanoma. This study aimed to characterize the national practice pattern in performing SLNB for this patient population and to determine the predictors and prognostic value of nodal positivity using population-level data.

METHODS

Patients with a diagnosis of clinically node-negative, thick melanoma (2010-2015) were identified using the National Cancer Database. Factors associated with performing regional nodal evaluation were characterized. Predictors of nodal positivity were determined using multivariable logistic regression. Overall survival (OS) was estimated using standard statistical methods.

RESULTS

Of 9847 study patients, 7513 (76.3%) underwent SLNB. The patients who underwent nodal evaluation were younger (median age, 66 vs 81 years; P < 0.001), less likely to have comorbid conditions (19.6% vs 26.0%; P < 0.001), more often privately insured (40.4% vs 16.4%; P < 0.001), and more frequently treated at an academic center (49.5% vs 43.9%; P < 0.001). Among those who underwent nodal evaluation, 25.5% had metastatic nodes. Multivariable regression identified age, Charlson-Deyo score, primary location, ulceration, mitoses, vertical growth phase, and lymphovascular invasion as independent predictors of nodal positivity, but with only moderate predictive accuracy (optimism-adjusted area under the curve, 0.684). Furthermore, compared with node negativity, node positivity was significantly associated with decreased OS (hazard ratio, 2.05; P < 0.001).

CONCLUSION

Although nodal status provides important prognostic information, at a national level, nearly one fourth of patients with clinically node-negative, thick melanoma do not undergo SLNB. Appropriate pathologic staging would allow these high-risk patients to be candidates for effective adjuvant therapy.