P40: Frequency and Predictors of Metastatic Disease in Sentinel Node Positive Malignant Melanoma

ePoster Presenter(s)

Christina S. Boutros, DO

Surgery Resident
University Hospitals Cleveland Medical Center/ Case Western Reserve University
University Heights, Ohio, United States

Submitter(s)

Christina S. Boutros, DO

Surgery Resident
University Hospitals Cleveland Medical Center/ Case Western Reserve University
University Heights, Ohio, United States

Author(s)

Christina S. Boutros, DO

Surgery Resident
University Hospitals Cleveland Medical Center/ Case Western Reserve University
University Heights, Ohio, United States
HK

Hanna Kakish, MD

Clinical Research Fellow
University Hospitals Cleveland Medical Center, United States
AL

Alexander W. Loftus, MD

Surgery Resident
University Hospitals Cleveland Medical Center, United States
LR

Luke D. Rothermel, MD MPH

Surgeon
University Hospitals Cleveland Medical Center, United States
Richard S. Hoehn, MD

Surgeon
University Hospitals Cleveland Medical Center
Cleveland, Ohio, United States

Introduction:

The NCCN considers “baseline staging” (whole body PET scan +/- brain MRI) for all asymptomatic melanoma patients with a positive sentinel lymph node biopsy (SLNB). Metastatic workups are increasingly used for node-negative patients with high-risk tumors that may benefit from adjuvant systemic therapies. The true yield of actionable findings from these workups is unknown.

Methods:

We created cohorts of adult malignant melanoma patients, T2-4, using the National Cancer Database (NCDB, 2012-2020) to mimic three common clinical scenarios: (1) clinically node negative, with positive sentinel lymph node(s) (cN0pN+); (2) clinically node negative, with negative sentinel lymph node(s) (cN0pN-); (3) clinically node positive (cN+). Demographic and clinical characteristics were compared by univariable analysis. Multivariable regression identified independent predictors of metastasis in each cohort. Supervised decision trees classified the rates of metastasis based on key clinical variables.

Results:

12,083 patients were cN0pN+, 65,939 were cN0pN-, and 10,771 were cN+. Rates of any metastatic disease and brain-only metastases across cohorts were as follows: (1) 169 (1.4%) / 37 (0.3%); (2) 203 (0.3%) / 26 (< 0.1%); (3) 325 (10.5%) / 49 (1.6%) (p < 0.001). There was a significant increase in rates of metastases with increased T stage for cohorts 1 and 2 ( p < 0.001). T4 tumors (OR 2.5, p < 0.001, CI 1.59-4.87), ulceration (OR 1.5, p = 0.026, CI 1.05 – 2.09), and lymphovascular invasion (OR 1.7, p. = 0.008, CI 1.14 – 2.42) associated with greater risk of metastatic disease for both cN0pN+ and cN0pN- patients on multivariable regression. For cN+ patients, only lesions found on the lower limb as well as nodular and lentigo maligna subtype associated with greater risk of metastases on multivariable regression. Supervised decision tree to classify the rates of any metastasis for cN0SNBpN+ patients is shown in Figure 1. The only groups with >2% risk of metastatic disease were T4 tumors or T2/T3 tumors with ulceration AND lymphovascular invasion. Most groups had a negligible risk (< 0.1%) of brain-only metastases.

Conclusions: This is the first analysis to guide pragmatic use of metastatic imaging for patients following melanoma excision and SLNB. Among cN0 patients, metastatic disease is uncommon and brain-only metastases are exceedingly rare. Further investigation could promote a tailored and value-based approach to metastatic workups guided by individual risk factors.

Learning Objectives:
Upon completion, participant will be able to cite the rates of metastatic disease for melanoma across 3 common clinical scenarios.
Upon completion, participant will be able to use clinical factors to assess the risk of melanoma based on our supervised decision tree
Upon completion, participant will be able to elucidate who is high risk for metastatic disease and who is low risk