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Comparison between continuous and discrete doses for model based designs in cancer dose finding

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  • Márcio Augusto Diniz
  • Mourad Tighiouart
  • André Rogatko

Abstract

Despite of an extensive statistical literature showing that discretizing continuous variables results in substantial loss of information, categorization of continuous variables has been a common practice in clinical research and in cancer dose finding (phase I) clinical trials. The objective of this study is to quantify the loss of information incurred by using a discrete set of doses to estimate the maximum tolerated dose (MTD) in phase I trials, instead of a continuous dose support. Escalation With Overdose Control and Continuous Reassessment Method were used because they are model-based designs where dose can be specified either as continuous or as a set of discrete levels. Five equally spaced sets of doses with different interval lengths and three sample sizes with sixteen scenarios were evaluated to compare the operating characteristics between continuous and discrete dose designs by Monte Carlo simulation. Loss of information was quantified by safety and efficiency measures. We conclude that if there is insufficient knowledge about the true MTD value, as commonly happens in phase I clinical trials, a continuous dose scheme minimizes information loss. If one is required to implement a design using discrete doses, then a scheme with 9 to 11 doses may yield similar results to the continuous dose scheme.

Suggested Citation

  • Márcio Augusto Diniz & Mourad Tighiouart & André Rogatko, 2019. "Comparison between continuous and discrete doses for model based designs in cancer dose finding," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-15, January.
  • Handle: RePEc:plo:pone00:0210139
    DOI: 10.1371/journal.pone.0210139
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    Cited by:

    1. Nancy Flournoy & José Moler & Fernando Plo, 2020. "Performance Measures in Dose‐Finding Experiments," International Statistical Review, International Statistical Institute, vol. 88(3), pages 728-751, December.
    2. Lennard L van Wanrooij & Marieke P Hoevenaar-Blom & Nicola Coley & Tiia Ngandu & Yannick Meiller & Juliette Guillemont & Anna Rosenberg & Cathrien R L Beishuizen & Eric P Moll van Charante & Hilkka So, 2020. "Pooling individual participant data from randomized controlled trials: Exploring potential loss of information," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-9, May.

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