{"title":"Dose selection criteria to identify the optimal dose based on ranked efficacy-toxicity outcomes without reliance on clinical utilities.","authors":"Sydney Porter, Anne Eaton, Thomas A Murray","doi":"10.1177/09622802251327691","DOIUrl":null,"url":null,"abstract":"<p><p>Recently, targeted and immunotherapy cancer treatments have motivated dose-finding based on efficacy-toxicity trade-offs rather than toxicity alone. The EffTox and utility-based Bayesian optimal interval (U-BOIN) dose-finding designs were developed in response to this need, but may be sensitive to elicited subjective design parameters that reflect the trade-off between efficacy and toxicity. To ease elicitation and reduce subjectivity, we propose dose desirability criteria that only depend on a preferential ordering of the joint efficacy-toxicity outcomes. We propose two novel order-based criteria and compare them with utility-based and contour-based criteria when paired with the design framework and probability models of EffTox and U-BOIN. The proposed dose desirability criteria simplify implementation and improve robustness to the elicited subjective design parameters and perform similarly in simulation studies to the established EffTox and U-BOIN designs when the ordering of the joint outcomes is equivalent. We also propose an alternative dose admissibility criteria based on the joint efficacy and toxicity profile of a dose rather than its marginal toxicity and efficacy profile. We argue that this alternative joint criterion is more consistent with defining dose desirability in terms of efficacy-toxicity trade-offs than the standard marginal admissibility criteria. The proposed methods enhance the usability and robustness of dose-finding designs that account for efficacy-toxicity trade-offs to identify the optimal biological dose.</p>","PeriodicalId":22038,"journal":{"name":"Statistical Methods in Medical Research","volume":" ","pages":"9622802251327691"},"PeriodicalIF":1.6000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Methods in Medical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/09622802251327691","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Recently, targeted and immunotherapy cancer treatments have motivated dose-finding based on efficacy-toxicity trade-offs rather than toxicity alone. The EffTox and utility-based Bayesian optimal interval (U-BOIN) dose-finding designs were developed in response to this need, but may be sensitive to elicited subjective design parameters that reflect the trade-off between efficacy and toxicity. To ease elicitation and reduce subjectivity, we propose dose desirability criteria that only depend on a preferential ordering of the joint efficacy-toxicity outcomes. We propose two novel order-based criteria and compare them with utility-based and contour-based criteria when paired with the design framework and probability models of EffTox and U-BOIN. The proposed dose desirability criteria simplify implementation and improve robustness to the elicited subjective design parameters and perform similarly in simulation studies to the established EffTox and U-BOIN designs when the ordering of the joint outcomes is equivalent. We also propose an alternative dose admissibility criteria based on the joint efficacy and toxicity profile of a dose rather than its marginal toxicity and efficacy profile. We argue that this alternative joint criterion is more consistent with defining dose desirability in terms of efficacy-toxicity trade-offs than the standard marginal admissibility criteria. The proposed methods enhance the usability and robustness of dose-finding designs that account for efficacy-toxicity trade-offs to identify the optimal biological dose.
期刊介绍:
Statistical Methods in Medical Research is a peer reviewed scholarly journal and is the leading vehicle for articles in all the main areas of medical statistics and an essential reference for all medical statisticians. This unique journal is devoted solely to statistics and medicine and aims to keep professionals abreast of the many powerful statistical techniques now available to the medical profession. This journal is a member of the Committee on Publication Ethics (COPE)