OBJECTIVES: Time to next treatment (TNT) may be a patient-relevant endpoint by capturing durable response, post-progression benefit, and the time free of systemic anticancer therapy, which may be achieved with immune-checkpoint inhibitors (ICI). This study investigated TNT as a surrogate endpoint (SE) of overall survival (OS) in previously untreated advanced melanoma patients.

METHODS: Patient-level data from the 60-month results of the CheckMate-067 randomized clinical trial (RCT) (NCT01844505) were used. Analyses were performed for nivolumab monotherapy (NIVO) or nivolumab with ipilimumab (NIVO+IPI) versus ipilimumab monotherapy (IPI). The SE one-step validation method based on a joint frailty model was used where the country of residence was applied to define synthetic clusters. Kendall’s 𝜏 and the coefficient of determination (R²_trial) were estimated for respective measurements of association at the individual and cluster levels. Surrogate threshold effect (STE), the maximum threshold hazard ratio (HR) for TNT that would translate into OS benefit, was estimated. A leave-one-out cross-validation analysis was performed to evaluate model robustness and predictive accuracy.

RESULTS: Fifteen clusters were considered from 945 patients. For both nivolumab-containing arms, the association between TNT and OS was deemed acceptable at the individual level (Kendall’s 𝜏 >0.60) and strong at the cluster level, with R²_trial fairly close to 1, and narrow confidence intervals. The estimated STEs were 0.58 for NIVO versus IPI and 0.39 for NIVO+IPI versus IPI. Cross-validation results showed minimum variation of the correlation measures and modest predictive accuracy for the model. The observed and predicted HRs of OS were closer to each other in the comparison of NIVO+IPI versus IPI than with NIVO versus IPI.

CONCLUSIONS: Results suggest that TNT may be a valuable SE in previously untreated advanced melanoma patients treated with ICI. Surrogacy analyses considering multiple RCTs of ICI-treated melanoma patients are warranted for confirming these findings and for improving the accuracy of the predictions.