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

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. METH...

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Detalles Bibliográficos
Autores principales: Rai, Shesh N., Qian, Chen, Pan, Jianmin, Seth, Anand, Srivastava, Deo Kumar, Bhatnagar, Aruni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456751/
https://www.ncbi.nlm.nih.gov/pubmed/32867708
http://dx.doi.org/10.1186/s12874-020-01101-z
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author Rai, Shesh N.
Qian, Chen
Pan, Jianmin
Seth, Anand
Srivastava, Deo Kumar
Bhatnagar, Aruni
author_facet Rai, Shesh N.
Qian, Chen
Pan, Jianmin
Seth, Anand
Srivastava, Deo Kumar
Bhatnagar, Aruni
author_sort Rai, Shesh N.
collection PubMed
description 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 15(th) 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.
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spelling pubmed-74567512020-08-31 Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients Rai, Shesh N. Qian, Chen Pan, Jianmin Seth, Anand Srivastava, Deo Kumar Bhatnagar, Aruni BMC Med Res Methodol Research Article 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 15(th) 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. BioMed Central 2020-08-31 /pmc/articles/PMC7456751/ /pubmed/32867708 http://dx.doi.org/10.1186/s12874-020-01101-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Rai, Shesh N.
Qian, Chen
Pan, Jianmin
Seth, Anand
Srivastava, Deo Kumar
Bhatnagar, Aruni
Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients
title Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients
title_full Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients
title_fullStr Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients
title_full_unstemmed Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients
title_short Statistical design of Phase II/III clinical trials for testing therapeutic interventions in COVID-19 patients
title_sort statistical design of phase ii/iii clinical trials for testing therapeutic interventions in covid-19 patients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456751/
https://www.ncbi.nlm.nih.gov/pubmed/32867708
http://dx.doi.org/10.1186/s12874-020-01101-z
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