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Proportional odds assumption for modeling longitudinal ordinal multiple toxicity outcomes in dose finding studies of targeted agents: A pooled analysis of 54 studies

机译:对靶向试剂的剂量发现研究中纵向序多种毒性结果的比例赔率假设:54项研究的汇总分析

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BackgroundData generated by phase I trials is richer than the classical binary DLT measured at the first cycle used as primary endpoints. Several works developed designs for more informative endpoints, e.g. ordinal toxicity grades and/or longitudinal data which relied however on strong assumptions, in particular the proportional odds (PO) assumption.MethodsWe evaluated this PO assumption for the dose and cycle on a large database of individual patient data from 54 phase I clinical trials of molecularly targeted agents. The PO model is a specific case of the continuation ratio logit model (CRLM) with null parameters. We compared the PO and CRLM models using the widely applicable information criterion (WAIC). We considered a longitudinal multivariate ordinal toxicity outcome (cutaneous, digestive, hematological, general disorders, and other toxicities).ResultsWAIC suggested that the CRLM model (WAIC?=?30911.58) outperformed the PO model (WAIC?=?31432.10). Deviance from PO assumption for dose was observed for digestive and general disorder toxicities. There was moderate cycle effect with slight deviance from PO assumption for the other type of toxicity.ConclusionsDesigns based on PO for dose should be a useful tool for drug with low expected digestive or general disorder toxicity dose-related incidence.
机译:由阶段I试验生成的BackgroundData比在用作主要端点的第一周期测量的经典二进制DLT更丰富。有几项工程开发了更多信息终点的设计,例如,依赖于强烈假设的序毒性等级和/或纵向数据,特别是比例赔率(PO)假设。在54阶段I临床试验中,对剂量和循环评估了该剂量和循环的这种PO假设分子靶向剂。 PO模型是具有空参数的连续比Logit模型(CRLM)的具体情况。我们使用广泛适用的信息标准(瓦米奇)比较了PO和CRLM模型。我们考虑了纵向多变量序毒性结果(皮肤,消化,血液学,一般疾病和其他毒性).Resultwaic表明CRLM型号(瓦米什?=?30911.58)表现优于PO模型(瓦米什?=?31432.10)。观察到消化和一般疾病的毒性对剂量的偏差。对于其他类型的毒性,有中度循环效果具有较小的偏差。基于Po的Dose的ConclusionsDesigns应该是具有低预期消化或一般疾病毒性剂量相关发病率的药物的有用工具。

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