PCN258 Using Mixture Cure Models to Improve Survival Extrapolations from EARLY Follow-up DATA for Nivolumab in NSCLC

Abstract

Selecting appropriate parametric models to extrapolate long-term survival based on limited follow up trial data may improve the reliability of HTA evidence. Using data from two phase 3 trials in 2L NSCLC, we assess whether mixture cure models (MCMs) improve survival extrapolation relative to standard methods. The analyses were based on datasets with minimum of 5 years of follow up from trials comparing nivolumab versus docetaxel in patients with pretreated metastatic squamous (CheckMate-017) and non-squamous (CheckMate-057) NSCLC. MCMs assume a fraction of patients are cured by treatment, with uncured and cured patients subject to separate survival curves. We estimated MCMs on 1-3 year databases and assessed the survival extrapolations against the validated standard parametric models (SPM) using the 5-year dataset. Validation of models was facilitated by comparing the restricted mean survival time (RMST) over 20-years. Additional comparisons against SPMs from earlier datasets will be presented. For CheckMate-017, MCMs fitted to the 1-year (PFS) and 3-year (OS) datasets were the earliest datasets modeled to yield results comparable to the 5-year validated SPM. For CheckMate-057, the 2-year (PFS) and 3-year (OS) datasets were the earliest datasets modeled to yield results comparable to the 5-year validated SPM. For CheckMate-017, the 20-year RMST estimate for PFS from the 1-year data was 25.5 vs 22.9 months for the 5-year SPM, and the 3-year OS MCM was 30.2 vs 30.5 for the 5-year SPM. For CheckMate-057, the 20-year RMST for the 2-year PFS MCM was 23.6 vs 19.0 for the 5-year SPM, and the 3-year OS MCM was 27.5 vs 28.6 for the 5-year SPM We demonstrate that the use of MCMs for modeling survival with early follow-up in NSCLC patients could anticipate validated standard survival extrapolations with extended follow-up.