Heterogeneity in Survival with Immune Checkpoint Inhibitors and Its Implications for Survival Extrapolations: A Case Study in Advanced Melanoma.

Background: Survival heterogeneity and limited trial follow-up present challenges for estimating lifetime benefits of oncology therapies. This study used CheckMate 067 (NCT01844505) extended follow-up data to assess the predictive accuracy of standard parametric and flexible models in estimating the long-term overall survival benefit of nivolumab plus ipilimumab (an immune checkpoint inhibitor combination) in advanced melanoma. Methods: Six sets of survival models (standard parametric, piecewise, cubic spline, mixture cure, parametric mixture, and landmark response models) were independently fitted to overall survival data for treatments in CheckMate 067 (nivolumab plus ipilimumab, nivolumab, and ipilimumab) using successive data cuts (28, 40, 52, and 60 mo). Standard parametric models allow survival extrapolation in the absence of a complex hazard. Piecewise and cubic spline models allow additional flexibility in fitting the hazard function. Mixture cure, parametric mixture, and landmark response models provide flexibility by explicitly incorporating survival heterogeneity. Sixty-month follow-up data, external ipilimumab data, and clinical expert opinion were used to evaluate model estimation accuracy. Lifetime survival projections were compared using a 5% discount rate. Results: Standard parametric, piecewise, and cubic spline models underestimated overall survival at 60 mo for the 28-mo data cut. Compared with other models, mixture cure, parametric mixture, and landmark response models provided more accurate long-term overall survival estimates versus external data, higher mean survival benefit over 20 y for the 28-mo data cut, and more consistent 20-y mean overall survival estimates across data cuts. Conclusion: This case study demonstrates that survival models explicitly incorporating survival heterogeneity showed greater accuracy for early data cuts than standard parametric models did, consistent with similar immune checkpoint inhibitor survival validation studies in advanced melanoma. Research is required to assess generalizability to other tumors and disease stages. Highlights: Given that short clinical trial follow-up periods and survival heterogeneity introduce uncertainty in the health technology assessment of oncology therapies, this study evaluated the suitability of conventional parametric survival modeling approaches as compared with more flexible models in the context of immune checkpoint inhibitors that have the potential to provide lasting survival benefits.This study used extended follow-up data from the phase III CheckMate 067 trial (NCT01844505) to assess the predictive accuracy of standard parametric models in comparison with more flexible methods for estimating the long-term survival benefit of the immune checkpoint inhibitor combination of nivolumab plus ipilimumab in advanced melanoma.Mixture cure, parametric mixture, and landmark response models provided more accurate estimates of long-term overall survival versus external data than other models tested.In this case study with immune checkpoint inhibitor therapies in advanced melanoma, extrapolation models that explicitly incorporate differences in cancer survival between observed or latent subgroups showed greater accuracy with both early and later data cuts than other approaches did.

Cost-Utility Analysis of Nivolumab in Adjuvant Treatment of Melanoma in France.

INTRODUCTION: The aim of the current study is to estimate the cost-effectiveness of adjuvant treatment with nivolumab relative to clinically relevant comparators in adult patients with melanoma with lymph node involvement or metastatic disease who have undergone complete resection from a French societal perspective. METHODS: The comparators were observation, low-dose interferon and pembrolizumab. A subgroup analysis was carried out in patients with BRAF mutation, adding dabrafenib plus trametinib. A three-state partitioned survival model was developed to project costs and health benefits over a 20-year time horizon. Extrapolation for recurrence-free survival (RFS) and overall survival (OS) was carried out using spline-based models. Because of the immaturity of OS data in pivotal trials for nivolumab and pembrolizumab, a predictive model of OS treatment effect based on RFS effect was developed using a correlation equation. Health state utilities and adverse events disutilities were derived from the CheckMate 238 trial and literature. Costs were estimated in 2019 euros. The model's primary outcome was efficiency frontier. Deterministic and probabilistic sensitivity analyses were conducted to assess the robustness of results. RESULTS: Observation, low-dose interferon and nivolumab were on the efficiency frontier. The incremental cost-utility ratio of nivolumab versus low-dose interferon (closest therapy on the efficiency frontier) was €37,886/quality-adjusted life year (QALY). Probabilistic sensitivity analysis reported an 80% probability of nivolumab being a cost-effective strategy for a willingness-to-pay threshold of €52,000/QALY. In the subgroup with BRAF mutation, the efficiency frontier was not changed by the addition of dabrafenib plus trametinib. CONCLUSIONS: Nivolumab is a cost-effective strategy as adjuvant treatment in adult patients with surgically resected melanoma in France.