Optimal Bayesian predictive probability for delayed response in single-arm clinical trials with binary efficacy outcome
Takuya Yoshimoto, Satoru Shinoda, Kouji Yamamoto, Kouji Tahata

TL;DR
This paper proposes a Bayesian method to incorporate delayed binary efficacy responses in single-arm oncology trials, enabling timely interim decisions despite delayed outcome confirmation.
Contribution
It introduces a generalized Bayesian approach to handle delayed responses, improving decision-making speed in phase II oncology trials.
Findings
The method accurately identified promising treatments in simulations.
It facilitated timely interim decisions despite response delays.
The approach outperformed traditional methods in decision accuracy.
Abstract
In oncology, phase II or multiple expansion cohort trials are crucial for clinical development plans. This is because they aid in identifying potent agents with sufficient activity to continue development and confirm the proof of concept. Typically, these clinical trials are single-arm trials, with the primary endpoint being short-term treatment efficacy. Despite the development of several well-designed methodologies, there may be a practical impediment in that the endpoints may be observed within a sufficient time such that adaptive go/no-go decisions can be made in a timely manner at each interim monitoring. Specifically, Response Evaluation Criteria in Solid Tumors guideline defines a confirmed response and necessitates it in non-randomized trials, where the response is the primary endpoint. However, obtaining the confirmed outcome from all participants entered at interim monitoring…
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Taxonomy
TopicsStatistical Methods in Clinical Trials · Advanced Causal Inference Techniques · Statistical Methods and Inference
