Bayesian single-arm phase II trial designs with time-to-event endpoints

A single-arm study design with non-inferiority and superiority time-to-event endpoints: a tool for proof-of-concept and de-intensification strategies in breast cancer

De-escalation trials in oncology evaluate therapies that aim to improve the quality of life of patients with low-risk cancer by avoiding overtreatment. Non-inferiority randomized trials are commonly used to investigate de-intensified regimens with similar efficacy to that of standard regimens but with fewer adverse effects (ESMO evidence tier A). In cases where it is not feasible to recruit the number of patients needed for a randomized trial, single-arm prospective studies with a hypothesis of non-inferiority can be conducted as an alternative. Single-arm studies are also commonly used to evaluate novel treatment strategies (ESMO evidence tier B). A single-arm design that includes both non-inferiority and superiority primary objectives will enable the ranking of clinical activity and other parameters such as safety, pharmacokinetics, and pharmacodynamics data. Here, we describe the statistical principles and procedures to support such a strategy. The non-inferiority margin is calculated using the fixed margin method. Sample size and statistical analyses are based on the maximum likelihood method for exponential distributions. We present example analyses in metastatic and adjuvant settings to illustrate the usefulness of our methodology. We also explain its implementation with nonparametric methods. Single-arm designs with non-inferiority and superiority analyses are optimal for proof-of-concept and de-escalation studies in oncology.

Evaluation of two-stage designs of Phase 2 single-arm trials in glioblastoma: a systematic review

BACKGROUND

Due to economical and ethical reasons, the two-stage designs have been widely used for Phase 2 single-arm trials in oncology because the designs allow us to stop the trial early if the proposed treatment is likely to be ineffective. Nonetheless, none has examined the usage for published articles that had applied the two-stage designs in Phase 2 single-arm trials in brain tumor. A complete systematic review and discussions for overcoming design issues might be important to better understand why oncology trials have shown low success rates in early phase trials.

METHODS

We systematically reviewed published single-arm two-stage Phase 2 trials for patients with glioblastoma and high-grade gliomas (including newly diagnosed or recurrent). We also sought to understand how these two-stage trials have been implemented and discussed potential design issues which we hope will be helpful for investigators who work with Phase 2 clinical trials in rare and high-risk cancer studies including Neuro-Oncology. The systematic review was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)-statement. Searches were conducted using the electronic database of PubMed, Google Scholar and ClinicalTrials.gov for potentially eligible publications from inception by two independent researchers up to May 26, 2022. The followings were key words for the literature search as index terms or free-text words: "phase II trials", "glioblastoma", and "two-stage design". We extracted disease type and setting, population, therapeutic drug, primary endpoint, input parameters and sample size results from two-stage designs, and historical control reference, and study termination status.

RESULTS

Among examined 29 trials, 12 trials (41%) appropriately provided key input parameters and sample size results from two-stage design implementation. Among appropriately implemented 12 trials, discouragingly only 3 trials (10%) explained the reference information of historical control rates. Most trials (90%) used Simon's two-stage designs. Only three studies have been completed for both stages and two out of the three completed studies had shown the efficacy.

CONCLUSIONS

Right implementation for two-stage design and sample size calculation, transparency of historical control and experimental rates, appropriate selection on primary endpoint, potential incorporation of adaptive designs, and utilization of Phase 0 paradigm might help overcoming the challenges on glioblastoma therapeutic trials in Phase 2 trials.

Optimal sample size determination for single-arm trials in pediatric and rare populations with Bayesian borrowing

In many therapeutic areas with unmet medical needs, such as pediatric oncology and rare diseases, one of the deterrent factors for clinical trial interpretability is the limited sample size with less-than-ideal operating characteristics. Single arm is usually the only viable design due to feasibility and ethical concerns. For the trial results to be more interpretable and conclusive, the evaluation of operating characteristics, such as type I error rate and power, and the appropriate utilization of prior information for study design, shall be prespecified and fully investigated during the trial planning phase. So far, very few existing literature addressed optimal sample size determination issues for the planning of pediatric and rare population trials, with majority of research focusing on analysis perspective with focus on Bayesian borrowing. In practice, when a single-arm trial is designed for rare population, it is not uncommon that the only information available is from an earlier trial and/or a few clinical publications based on observational studies, often constituting mixed or uncertain conclusions. In light of this, an optimal Bayesian sample size determination method for single-arm trial with binary or continuous endpoint is proposed, where conflicting prior beliefs can be readily incorporated. Prior effective sample size can be calculated to assess the robustness as well as the prior information borrowed. Moreover, due to the lack of closed-form posterior distributions in general, an alternative approach for calculating Bayesian power is described. Simulation studies are provided to demonstrate the utility of the proposed methods. In addition, a case study in pediatric patients with leukemia is included to illustrate the proposed method with the existing approaches.