ArticleContemporary clinical trials communications2020
Proportional odds assumption for modeling longitudinal ordinal multiple toxicity outcomes in dose finding studies of targeted agents: A pooled analysis of 54 studies.
Article in Contemporary clinical trials communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 1 citations in OpenAlex.
- Optimizing endpoints in early phase clinical trials of acute respiratory distress syndrome.American journal of respiratory and critical care medicine · 2026Article
- Exposure-response modeling for nausea incidence for cotadutide using a Markov modeling approach.CPT: pharmacometrics & systems pharmacology · 2024Article
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3 authors at 2 institutions in 2 countries.
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Abstract
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.
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