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Published in: PharmacoEconomics 1/2018

01-01-2018 | Current Opinion

Oncology Modeling for Fun and Profit! Key Steps for Busy Analysts in Health Technology Assessment

Authors: Jaclyn Beca, Don Husereau, Kelvin K. W. Chan, Neil Hawkins, Jeffrey S. Hoch

Published in: PharmacoEconomics | Issue 1/2018

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Abstract

In evaluating new oncology medicines, two common modeling approaches are state transition (e.g., Markov and semi-Markov) and partitioned survival. Partitioned survival models have become more prominent in oncology health technology assessment processes in recent years. Our experience in conducting and evaluating models for economic evaluation has highlighted many important and practical pitfalls. As there is little guidance available on best practices for those who wish to conduct them, we provide guidance in the form of ‘Key steps for busy analysts,’ who may have very little time and require highly favorable results. Our guidance highlights the continued need for rigorous conduct and transparent reporting of economic evaluations regardless of the modeling approach taken, and the importance of modeling that better reflects reality, which includes better approaches to considering plausibility, estimating relative treatment effects, dealing with post-progression effects, and appropriate characterization of the uncertainty from modeling itself.
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Metadata
Title
Oncology Modeling for Fun and Profit! Key Steps for Busy Analysts in Health Technology Assessment
Authors
Jaclyn Beca
Don Husereau
Kelvin K. W. Chan
Neil Hawkins
Jeffrey S. Hoch
Publication date
01-01-2018
Publisher
Springer International Publishing
Published in
PharmacoEconomics / Issue 1/2018
Print ISSN: 1170-7690
Electronic ISSN: 1179-2027
DOI
https://doi.org/10.1007/s40273-017-0583-4

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