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

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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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Author information

Authors and Affiliations

  1. Pharmacoeconomics Research Unit, Cancer Care Ontario, Toronto, ON, Canada

    Jaclyn Beca

  2. Institute of Health Economics, 1200, 10405 Jasper Avenue, Edmonton, AB, T5J 3N4, Canada

    Don Husereau

  3. School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada

    Don Husereau

  4. Sunnybrook Odette Cancer Centre, University of Toronto, Toronto, ON, Canada

    Kelvin K. W. Chan

  5. Canadian Centre for Applied Research in Cancer Control, Toronto, Canada

    Kelvin K. W. Chan

  6. The University of Glasgow, Glasgow, Scotland, UK

    Neil Hawkins

  7. The University of California, Davis, Davis, CA, USA

    Jeffrey S. Hoch

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  4. Neil Hawkins
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Contributions

JB and JSH provided the original inspiration and key content for this work. DH led the writing of the manuscript including the drafting of the outline and manuscript and is the guarantor of this work. All authors approved the outline of the work, helped to write and revise the manuscript, and read and approved the final version of the manuscript.

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Correspondence to Don Husereau.

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No funding was received for the preparation of this work. All authors provided in-kind contributions.

Conflict of interest

All authors have signed conflict of interest forms and read information regarding disclosure of potential conflict of interest at http://www.springer.com/us/authors-editors/journal-author/journal-author-helpdesk/before-you-start and declare the following: accepting consulting fees from medical device and pharmaceutical companies who may have interest in the work (DH, NH); no other relationships or activities that could appear to have influenced the submitted work (JB, KKWC, JSH). All authors declare a significant interest in improving the state of the art of oncology health technology assessment.

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Beca, J., Husereau, D., Chan, K.K.W. et al. Oncology Modeling for Fun and Profit! Key Steps for Busy Analysts in Health Technology Assessment. PharmacoEconomics 36, 7–15 (2018). https://doi.org/10.1007/s40273-017-0583-4

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  • DOI: https://doi.org/10.1007/s40273-017-0583-4

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