Assessment-schedule matching in unanchored indirect treatment comparisons of progression-free survival in cancer studies

Murtuza Bharmal, Head, Oncology Brands & Life Cycle Management, Global Evidence & Value Development, EMD Serono, Inc. and Venediktos Kapetanakis, Director, Principal Statistician, Evidence Synthesis, Modeling & Communication, Evidera, discuss their paper “Assessment-schedule matching in unanchored indirect treatment comparisons of progression-free survival in cancer studies” published in PharmacoEconomics. In the video, Murtuza and Venediktos describe a new methodology, assessment schedule matching, aimed at improving the analyses of indirect treatment comparisons of progression-free survival from clinical trials for novel cancer treatments, and ultimately informing clinical decision making.

To access the R code the authors have made available to implement this method, please visit the supplementary material within the original publication.

About the authors:

Murtuza Bharmal, PhD, MS, B.Pharm, is a globally experienced leader having held senior positions within multinational biopharmaceutical and consulting environments with over 20 years of experience within R&D and Commercial organizations. Demonstrating his expertise in using scientific tools to inform decision making at various levels in healthcare, Murtuza has authored over 150 original research articles and presentations in a variety of international journals and professional conferences. Murtuza has lived and worked in the US, Germany, China and India with an appreciation of cross-cultural leadership. Testimony to his thought leadership in the field of outcomes research, Murtuza also serves as a co-editor of a leading international journal, Value & Outcomes Spotlight of ISPOR—The Professional Society for Health Economics and Outcomes Research.

Venediktos Kapetanakis, PhD, is a Director, Principal Statistician, with the Modeling and Simulation team at Evidera, a PPD business, in London. He has 14 years’ experience over a wide range of statistical methodologies (e.g., survival analysis, population-adjusted indirect comparisons, network meta-analysis, treatment switching, generalized linear regression, mixed effects models, surrogate endpoint validation, Bayesian methods, and multiple imputation for missing data), and he conceptualized and led the development of the assessment schedule matching (ASM) method. Additionally, he has experience in developing health economic models including patient-level simulations for health technology assessments. Dr. Kapetanakis has co-authored over 25 peer-reviewed publications and has worked in a range of disease areas including oncology, asthma, obesity, cardiovascular disease, diabetic retinopathy, myopia, and glaucoma. He completed his PhD on multi-state Markov models at the University of Cambridge.

Original publication:

Assessment-schedule matching in unanchored indirect treatment comparisons of progression-free survival in cancer studies

Venediktos Kapetanakis, Thibaud Prawitz, Michael Schlichting, K. Jack Ishak, Hemant Phatak, Mairead Kearney, John W. Stevens, Agnes Benedict & Murtuza Bharmal

PharmacoEconomics (2019) doi.org/10.1007/s40273-019-00831-3