Recurrence Patterns and Survival Outcomes in Clinical Stage IIB/IIC Melanoma: Can We Stratify Patients for Consideration of Neoadjuvant Immunotherapy?

Background: Interest in evaluating neoadjuvant immunotherapy for stage IIB/IIC melanoma is growing, but studies assessing long-term outcomes generally report data based on pathologic stage after sentinel lymph node microstaging. This study therefore aimed to characterize real-world recurrence patterns and survival specifically in clinical stage IIB/IIC melanoma to contextualize outcomes for selection of patients to undergo neoadjuvant immunotherapy.

Methods: This single-institution retrospective cohort study included patients who received a diagnosis of American Joint Committee on Cancer eighth-edition clinical stage IIB/IIC cutaneous melanoma from 2006 to 2019. Factors associated with recurrence were analyzed using univariable analysis and multivariable Cox proportional hazards analysis. Recurrence-free survival (RFS), melanoma-specific survival (MSS), and overall survival (OS) were analyzed using the Kaplan-Meier method.

Results: The inclusion criteria were met by 229 patients, of whom 152 (66%) were male and 208 (91%) were white. The median follow-up time was 64 months (interquartile range [IQR] 29-105 months). Overall, 101 (44%) patients experienced a recurrence, with a median time-to-recurrence of 15.3 months (IQR 8-31 months). The estimated 2-year RFS, MSS, and OS were 69%, 91%, and 87%, respectively. The presence of pre-surgical lymphovascular invasion (hazard ratio [HR] 1.764; p = 0.018) was associated with increased risk of recurrence.

Conclusion: This single-institution retrospective cohort study of patients with clinical stage IIB/IIC melanoma found a 2-year RFS of 69%. The presence of pre-surgical lymphovascular invasion was significantly associated with recurrence in this population. These data can help guide clinicians and researchers in the design and assessment of future studies evaluating neoadjuvant therapy in clinical stage IIB/IIC melanoma and in optimizing patient selection.