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Projecting Overall Survival with Immuno-Oncology Treatments

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Projecting Overall Survival with Immuno-Oncology

Projecting Overall Survival with Immuno-Oncology Treatments K. Jack Ishak, PhD Senior Research Leader, Modeling and Simulation; Executive Director, Center of Excellence for Statistics, Evidera Irina Proskorovsky, MSc Director, Principal Statistician, Modeling and Simulation, Evidera Noemi Muszbek, MA, MS, Senior Research Scientist, Modeling and Simulation, Evidera Introduction On February 4, 2016, the American Society of Clinical Oncology (ASCO) announced immunotherapy as the top cancer advance of the year. 1 As an alternative to traditional chemotherapies and targeted therapies, scientists and doctors are increasingly suggesting immunotherapies, including checkpoint inhibitors, transforming the clinical landscape and patients’ lives. Differing substantially from traditional chemotherapies, immunotherapies induce the patient’s immune system to produce an anti-tumor response. Checkpoint inhibitors block certain T-cell receptors, such as CTLA-4 (e.g., ipilimumab), PD-1 (e.g., pembrolizumab, nivolumab) and PD-L1 (e.g., atezolizumab, avelumab, and durvalumab), which act as “checkpoints” regulating T-cell activation. Inhibiting the action of these receptors promotes T-cell activation and anti-tumor response, possibly even tumor rejection. 2 As experience with immunotherapies in other oncology areas is growing, questions have emerged regarding challenges in the assessment of the value of these therapies. The most visible challenge is in extrapolating overall survival (OS). In some indications, the new checkpoint inhibitors, either as monotherapy or as K. Jack Ishak Irina Proskorovsky Noemi Muszbek combination therapy, provide substantial survival benefits, and the OS curve appears to plateau for an important proportion of patients (20-25% in previous trials for PD1 and PDL 1 inhibitors). 3,4 This suggests that many patients could potentially be cured of their disease (but of course, still subject to other mortality). This presents several difficulties, as the shape of the OS Kaplan-Meier curve often does not conform to the conventionally used distributions 5,6 and the proportional hazard assumptions required for conventional network meta-analyses (NMAs) do not hold. In addition, the follow-up in the trials is relatively short and there is no long-term experience with these therapies (the first checkpoint inhibitor, ipilimumab was approved in 2011 by the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA) in advanced melanoma. Thus extrapolation of OS presents new challenges. This article reviews different methods for the projection of OS, covering both standard approaches and extensions to deal with the expected challenges to model survival with immunotherapies. EVIDERA.COM THE EVIDENCE FORUM October 2016

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