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. 2020 Aug 31;20(1):220.
doi: 10.1186/s12874-020-01101-z.

Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients

Shesh N Rai  1   2 , Chen Qian  3   4 , Jianmin Pan  3 , Anand Seth  5 , Deo Kumar Srivastava  6 , Aruni Bhatnagar  7
Affiliations

Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients

Shesh N Rai et al. BMC Med Res Methodol. .

Abstract

Background: Because of unknown features of the COVID-19 and the complexity of the population affected, standard clinical trial designs on treatments may not be optimal in such patients. We propose two independent clinical trials designs based on careful grouping of patient and outcome measures.

Methods: Using the World Health Organization ordinal scale on patient status, we classify treatable patients (Stages 3-7) into two risk groups. Patients in Stages 3, 4 and 5 are categorized as the intermediate-risk group, while patients in Stages 6 and 7 are categorized as the high-risk group. To ensure that an intervention, if deemed efficacious, is promptly made available to vulnerable patients, we propose a group sequential design incorporating four factors stratification, two interim analyses, and a toxicity monitoring rule for the intermediate-risk group. The primary response variable (binary variable) is based on the proportion of patients discharged from hospital by the 15th day. The goal is to detect a significant improvement in this response rate. For the high-risk group, we propose a group sequential design incorporating three factors stratification, and two interim analyses, with no toxicity monitoring. The primary response variable for this design is 30 day mortality, with the goal of detecting a meaningful reduction in mortality rate.

Results: Required sample size and toxicity boundaries are calculated for each scenario. Sample size requirements for designs with interim analyses are marginally greater than ones without. In addition, for both the intermediate-risk group and the high-risk group, the required sample size with two interim analyses is almost identical to analyses with just one interim analysis.

Conclusions: We recommend using a binary outcome with composite endpoints for patients in Stage 3, 4 or 5 with a power of 90% to detect an improvement of 20% in the response rate, and a 30 day mortality rate outcome for those in Stage 6 or 7 with a power of 90% to detect 15% (effect size) reduction in mortality rate. For the intermediate-risk group, two interim analyses for efficacy evaluation along with toxicity monitoring are encouraged. For the high-risk group, two interim analyses without toxicity monitoring is advised.

Keywords: COVID-19; Composite outcomes; Efficacy; Hospitalization; Interim analysis; Intubation; Mortality; Power; Sample size; Toxicity monitoring.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of Two Parallel Clinical Trials with Key Design Components
See this image and copyright information in PMC

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