Meta-analyses of phase I dose-finding studies: Application for the development of protein kinase inhibitors in oncology.

IF 5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Research Synthesis Methods Pub Date : 2024-11-01 Epub Date: 2024-08-05 DOI:10.1002/jrsm.1747
Laura Caquelin, Pauline Badra, Lucas Poulain, Bruno Laviolle, Moreno Ursino, Clara Locher
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Abstract

This study aimed to assess the feasibility of applying two recent phase I meta-analyses methods to protein kinase inhibitors (PKIs) developed in oncology and to identify situations where these methods could be both feasible and useful. This ancillary study used data from a systematic review conducted to identify dose-finding studies for PKIs. PKIs selected for meta-analyses were required to have at least five completed dose-finding studies involving cancer patients, with available results, and dose escalation guided by toxicity assessment. To account for heterogeneity caused by various administration schedules, some studies were divided into study parts, considered as separate entities in the meta-analyses. For each PKI, two Bayesian random-effects meta-analysis methods were applied to model the toxicity probability distribution of the recommended dose and to estimate the maximum tolerated dose (MTD). Meta-analyses were performed for 20 PKIs including 96 studies corresponding to 115 study parts. The median posterior probability of toxicity probability was below the toxicity thresholds of 0.20 for 70% of the PKIs, even if the resulting credible intervals were very wide. All approved doses were below the MTD estimated for the minimum toxicity threshold, except for one, for which the approved dose was above the MTD estimated for the maximal threshold. The application of phase I meta-analysis methods has been feasible for the majority of PKI; nevertheless, their implementation requires multiple conditions. However, meta-analyses resulted in estimates with large uncertainty, probably due to limited patient numbers and/or between-study variability. This calls into question the reliability of the recommended doses.

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I 期剂量测定研究的元分析:应用于肿瘤学蛋白激酶抑制剂的开发。
本研究旨在评估将两种最新的I期荟萃分析方法应用于肿瘤学领域开发的蛋白激酶抑制剂(PKIs)的可行性,并确定这些方法在哪些情况下既可行又有用。这项辅助研究使用了为确定 PKIs 剂量试验而进行的系统综述中的数据。被选中进行荟萃分析的 PKIs 必须至少完成五项涉及癌症患者的剂量试验研究,并有可用的结果,以及在毒性评估指导下进行的剂量升级。为了考虑到不同给药方案造成的异质性,一些研究被划分为不同的研究部分,在荟萃分析中被视为独立的实体。对于每种 PKI,都采用了两种贝叶斯随机效应荟萃分析方法来模拟推荐剂量的毒性概率分布,并估算最大耐受剂量(MTD)。对 20 项 PKI 进行了元分析,其中包括 96 项研究,对应 115 个研究部分。在 70% 的 PKI 中,毒性概率的中位后验概率低于 0.20 的毒性阈值,即使由此得出的可信区间非常宽。除一项研究的批准剂量高于最大阈值估计的 MTD 外,所有批准剂量均低于最小毒性阈值估计的 MTD。对大多数 PKI 来说,应用 I 期元分析方法是可行的;不过,其实施需要多种条件。然而,荟萃分析得出的估计值具有很大的不确定性,这可能是由于患者人数有限和/或研究间的变异性造成的。这让人怀疑推荐剂量的可靠性。
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来源期刊
Research Synthesis Methods
Research Synthesis Methods MATHEMATICAL & COMPUTATIONAL BIOLOGYMULTID-MULTIDISCIPLINARY SCIENCES
CiteScore
16.90
自引率
3.10%
发文量
75
期刊介绍: Research Synthesis Methods is a reputable, peer-reviewed journal that focuses on the development and dissemination of methods for conducting systematic research synthesis. Our aim is to advance the knowledge and application of research synthesis methods across various disciplines. Our journal provides a platform for the exchange of ideas and knowledge related to designing, conducting, analyzing, interpreting, reporting, and applying research synthesis. While research synthesis is commonly practiced in the health and social sciences, our journal also welcomes contributions from other fields to enrich the methodologies employed in research synthesis across scientific disciplines. By bridging different disciplines, we aim to foster collaboration and cross-fertilization of ideas, ultimately enhancing the quality and effectiveness of research synthesis methods. Whether you are a researcher, practitioner, or stakeholder involved in research synthesis, our journal strives to offer valuable insights and practical guidance for your work.
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