Bayesian optimal phase II designs with dual‐criterion decision making

Abstract

The conventional phase II trial design paradigm is to make the go/no-go decision based on the hypothesis testing framework. Statistical significance itself alone, however, may not be sufficient to establish that the drug is clinically effective enough to warrant confirmatory phase III trials. We propose the Bayesian optimal phase II trial design with dual-criterion decision making (BOP2-DC), which incorporates both statistical significance and clinical relevance into decision making.Based on the posterior probability that the treatment effect reaches the lower reference value (statistical significance) and the clinically meaningful value (clinical significance), BOP2-DC allows for go/consider/no-go decisions, rather than a binary go/no-go decision. BOP2-DC is highly flexible and accommodates various types of endpoints, including binary, continuous, time-to-event, multiple, and coprimary endpoints, in single-arm and randomized trials. The decision rule of BOP2-DC is optimized to maximize the probability of a go decision when the treatment is effective or minimize the expected sample size when the treatment is futile. Simulation studies show that the BOP2-DC design yields desirable operating characteristics. The software to implement BOP2-DC is freely available at www.trialdesign.org.

A seamless phase II/III design with dose optimization for oncology drug development

“…Note that $$$ {s}_0,{s}_1,{\tau}_0 $$$, and $$$ {\tau}_1 $$$ are four crucial tuning parameters that need to be pre‐determined within the SDDO framework. These parameters should be carefully selected to align with the trial's specific requirements and concerns, 37 thereby maximizing the benefits of the SDDO framework. As a practical approach, we suggest setting $$$ {s}_0={s}_1=0.9 $$$ to ensure high confidence in decision‐making.…”

Systemic therapies in hepatocellular carcinoma: A revolution?

“…73 Finally, incorporation of different approaches in the clinical decisionmaking such as us go/consider/no-go decisions or Bayesian group sequential approach rather than a binary go/no-go decision. 74,75 FORTUNY ET AL.…”

“…This refers to the extent of patients successfully supported both in decision‐making partnerships about treatments and in their treatment taking 73 . Finally, incorporation of different approaches in the clinical decision‐making such as us go/consider/no‐go decisions or Bayesian group sequential approach rather than a binary go/no‐go decision 74,75 …”

A Bayesian phase II proof‐of‐concept design for clinical trials with longitudinal endpoints

“…Pulkstenis et al 11 proposed a flexible Bayesian quantitative decision‐making paradigm that evaluates evidence relative to achieving a multilevel target product profile. Zhao et al 12 extended BOP2 and proposed an optimal Bayesian design BOP2‐DC based on dual criteria of statistical significance and clinical relevance. Most of these existing designs focus on the trials with a single scalar endpoint (eg, the response rate).…”