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

• Main Authors: Damien Drubay, Laurence Collette, Xavier Paoletti
• Format: Article
• Language: English
• Published: Elsevier 2020-03-01
• Series: Contemporary Clinical Trials Communications
• Online Access: http://www.sciencedirect.com/science/article/pii/S2451865420300132

Background: Data 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. Methods: We 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). Results: WAIC 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. Conclusions: Designs based on PO for dose should be a useful tool for drug with low expected digestive or general disorder toxicity dose-related incidence. Keywords: Dose finding, Multidimensional data, Proportional odds, Targeted agent