Development of a bayesian toxo-equivalence model between docetaxel and paclitaxel

Summary

Members of the taxane class of chemotherapies, staples of cancer treatment since the 1990s, can induce chemotherapy-induced peripheral neuropathy (CIPN), a potentially irreversible outcome related to cumulative exposure. Switching between taxanes is often clinically necessary; however, different taxanes have different efficacies, toxicities, and dosing strategies, necessitating an evidence-based schema focused on toxicity. We performed a systematic review and meta-analysis of the literature on docetaxel and paclitaxel, extracting cumulative dose, rates of CIPN, and subject demographics, thereby establishing their dose-toxo-equivalence relationship through a Bayesian meta-analysis model, calculating doses of the two drugs that are expected to have comparable rates of CIPN, along with credible intervals. Our final model, based on 169 studies, produces credible interval widths that provide guidance within one treatment cycle. In practice, this model provides a framework under which oncologists can make treatment switching and dosing decisions, hopefully reducing patient risk of CIPN.

Graphical abstract

Highlights

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  We created a dosing framework for oncologists using published clinical trials

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  Our approach leverages existing publicly available data via Bayesian meta-analysis

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  This framework uses a toxicity outcome rather than more common efficacy outcomes

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  The output range of equivalent doses provides guidance within one treatment cycle

Abstract

Medicine; Toxicology; Pharmaceutical science; Bioinformatics;