Taylor & Francis Group
Browse
lbps_a_1744619_sm2398.docx (84.05 kB)

A dose-finding approach for genomic patterns in phase I trials

Download (84.05 kB)
journal contribution
posted on 2020-04-20, 19:25 authored by S Kaneko, A Hirakawa, Y Kakurai, C Hamada

Precision medicine is an emerging approach for disease treatment and prevention that accounts for individual variability in genes, environment, and lifestyle. Cancer is a genomic disease; therefore, the dose-efficacy and dose–toxicity relationships for molecularly targeted agents in cancer most likely differ, based on the genomic mutation pattern. The individualized optimal dose – the maximal efficacious dose with a clinically acceptable safety profile – may vary depending on the genomic mutation patterns and should be determined prior to the use of these agents in precision medicine. In addition, genes that influence the individualized optimal doses should be identified in early-phase development. In this study, we propose a novel dose-finding approach to identify the individualized optimal dose for molecularly targeted agents in phase I cancer trials. Individualized optimal dose determination and gene selection were conducted simultaneously based on L1 and L2 penalized regression. Similar to most reported dose-finding approaches, this study considers non-monotonic patterns for dose-efficacy and dose–toxicity relationships, as well as correlations between efficacy and toxicity outcomes based on multinomial distribution. Our dose-finding algorithm is based on the predictive probability calculated with an estimated penalized regression model. We compare the operating characteristics between the proposed and existing methods by simulation studies under various scenarios.

Funding

This work was partially supported by Japan Society for the Promotion of Science [grant 17K00045] (Grant-in-aid for scientific research C).

History