Modelling the Survival Outcomes of Immuno-Oncology Drugs in Economic Evaluations: A Systematic Approach to Data Analysis and Extrapolation

Male Skin Neoplasms Cost-Benefit Analysis 610 Kaplan-Meier Estimate Disease-Free Survival 03 medical and health sciences Antineoplastic Agents, Immunological 0302 clinical medicine Antineoplastic Combined Chemotherapy Protocols Humans Original Research Article Neoplasm Metastasis Melanoma Aged Randomized Controlled Trials as Topic Antibodies, Monoclonal Middle Aged Models, Theoretical Ipilimumab Survival Analysis 3. Good health Survival Rate Nivolumab Female
DOI: 10.1007/s40273-017-0558-5 Publication Date: 2017-09-02T12:21:36Z
ABSTRACT
New immuno-oncology (I-O) therapies that harness the immune system to fight cancer call for a re-examination of the traditional parametric techniques used to model survival from clinical trial data. More flexible approaches are needed to capture the characteristic I-O pattern of delayed treatment effects and, for a subset of patients, the plateau of long-term survival.Using a systematic approach to data management and analysis, the study assessed the applicability of traditional and flexible approaches and, as a test case of flexible methods, investigated the suitability of restricted cubic splines (RCS) to model progression-free survival (PFS) in I-O therapy.The goodness of fit of each survival function was tested on data from the CheckMate 067 trial of monotherapy versus combination therapy (nivolumab/ipilimumab) in metastatic melanoma using visual inspection and statistical tests. Extrapolations were validated using long-term data for ipilimumab.Modelled PFS estimates using traditional methods did not provide a good fit to the Kaplan-Meier (K-M) curve. RCS estimates fit the K-M curves well, particularly for the plateau phase. RCS with six knots provided the best overall fit, but RCS with one knot performed best at the plateau phase and was preferred on the grounds of parsimony.RCS models represent a valuable addition to the range of flexible approaches available to model survival when assessing the effectiveness and cost-effectiveness of I-O therapy. A systematic approach to data analysis is recommended to compare the suitability of different approaches for different diseases and treatment regimens.
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