Clinical Predictors of Survival in Patients With BRAFV600-Mutated Metastatic Melanoma Treated With Combined BRAF and MEK Inhibitors After Immune Checkpoint Inhibitors.
Adriana M KahnCurtis J PerryKatrina EttsHarriet KlugerMario SznolPublished in: The oncologist (2023)
Prospective and between trial comparisons indicate that first-line treatment with immune checkpoint inhibitors improves survival outcomes compared to first-line therapy with combined BRAF and MEK inhibitors in metastatic melanoma containing BRAFV600E/K mutations. Long-term outcomes for BRAF/MEK inhibition after progression on immunotherapy have not been reported. Moreover, clinical variables associated with outcome from treatment with combined BRAF/MEK inhibition were previously identified in the first-line setting but have not been investigated when targeted therapies are administered after progression on immune therapy. We performed a retrospective single institution analysis of 40 metastatic melanoma patients receiving combined BRAF/MEK inhibitors after progression on an anti-PD-1 or ipilimumab plus nivolumab to assess response rate by RECIST 1.1, progression-free and overall survival (PFS and OS). Pretreatment clinical variables were analyzed for association with OS. Ipilimumab/nivolumab was the first-line immunotherapy regimen in 39 patients (97.5%), and BRAFV600E/K mutations were present in 33 (83%) and 7 (17%) patients, respectively. The median OS from start of BRAF/MEK inhibitors was 20.3 months (1.73-106.4+, 95% CI of median 13.3-30.7). Clinical characteristics associated with worse survival prior to starting BRAF/MEK inhibitors included age > 60 years (median OS 14 vs. 28 months; HR 2.5; 95% CI 0.91-6.87, P = .023), ECOG-PS > 2 (median OS 7 vs. 33 months; HR 2.89; 95% CI 0.78-10.76, P = .018), and presence of bone metastases (median OS 9 vs. 52 months; HR 3.17; 95% CI 1.33-7.54, P = .002). These associations with shorter survival maintained their significance on multivariate analysis. If confirmed in larger cohorts, the identified prognostic variables can be used for stratification of patients in future randomized trials.