Cargando…
Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials
A platform trial is a trial involving an innovative adaptive design with a single master protocol to efficiently evaluate multiple interventions. It offers flexible features such as dropping interventions for futility and adding new interventions to be evaluated during the course of a trial. Althoug...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137133/ https://www.ncbi.nlm.nih.gov/pubmed/37185413 http://dx.doi.org/10.3390/curroncol30040300 |
_version_ | 1785032386182905856 |
---|---|
author | Liu, Jialing Lu, Chengxing Jiang, Ziren Alemayehu, Demissie Nie, Lei Chu, Haitao |
author_facet | Liu, Jialing Lu, Chengxing Jiang, Ziren Alemayehu, Demissie Nie, Lei Chu, Haitao |
author_sort | Liu, Jialing |
collection | PubMed |
description | A platform trial is a trial involving an innovative adaptive design with a single master protocol to efficiently evaluate multiple interventions. It offers flexible features such as dropping interventions for futility and adding new interventions to be evaluated during the course of a trial. Although there is a consensus that platform trials can identify beneficial interventions with fewer patients, less time, and a higher probability of success than traditional trials, there remains debate on certain issues, one of which is whether (and how) the non-concurrent control (NCC) (i.e., patients in the control group recruited prior to the new interventions) can be combined with the current control (CC) in the analysis, especially if there is a change of standard of care during the trial. Methods: In this paper, considering time-to-event endpoints under the proportional hazard model assumption, we introduce a new concept of NCC concurrent observation time (NCC COT), and propose to borrow NCC COT through left truncation. This assumes that the NCC COT and CC are comparable. If the protocol does not prohibit NCC patients to change the standard of care while on study, NCC COT and CC likely will share the same standard of care. A simulated example is provided to demonstrate the approach. Results: Using exponential distributions, the simulated example assumes that NCC COT and CC have the same hazard, and the treatment group has a lower hazard. The estimated HR comparing treatment to the pooled control group is 0.744 (95% CI 0.575, 0.962), whereas the comparison to the CC group alone is 0.755 (95% CI 0.566, 1.008), with corresponding p-values of 0.024 versus 0.057, respectively. This suggests that borrowing NCC COT can improve statistical efficiency when the exchangeability assumption holds. Conclusion: This article proposes an innovative approach of borrowing NCC COT to enhance statistical inference in platform trials under appropriate scenarios. |
format | Online Article Text |
id | pubmed-10137133 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101371332023-04-28 Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials Liu, Jialing Lu, Chengxing Jiang, Ziren Alemayehu, Demissie Nie, Lei Chu, Haitao Curr Oncol Article A platform trial is a trial involving an innovative adaptive design with a single master protocol to efficiently evaluate multiple interventions. It offers flexible features such as dropping interventions for futility and adding new interventions to be evaluated during the course of a trial. Although there is a consensus that platform trials can identify beneficial interventions with fewer patients, less time, and a higher probability of success than traditional trials, there remains debate on certain issues, one of which is whether (and how) the non-concurrent control (NCC) (i.e., patients in the control group recruited prior to the new interventions) can be combined with the current control (CC) in the analysis, especially if there is a change of standard of care during the trial. Methods: In this paper, considering time-to-event endpoints under the proportional hazard model assumption, we introduce a new concept of NCC concurrent observation time (NCC COT), and propose to borrow NCC COT through left truncation. This assumes that the NCC COT and CC are comparable. If the protocol does not prohibit NCC patients to change the standard of care while on study, NCC COT and CC likely will share the same standard of care. A simulated example is provided to demonstrate the approach. Results: Using exponential distributions, the simulated example assumes that NCC COT and CC have the same hazard, and the treatment group has a lower hazard. The estimated HR comparing treatment to the pooled control group is 0.744 (95% CI 0.575, 0.962), whereas the comparison to the CC group alone is 0.755 (95% CI 0.566, 1.008), with corresponding p-values of 0.024 versus 0.057, respectively. This suggests that borrowing NCC COT can improve statistical efficiency when the exchangeability assumption holds. Conclusion: This article proposes an innovative approach of borrowing NCC COT to enhance statistical inference in platform trials under appropriate scenarios. MDPI 2023-03-31 /pmc/articles/PMC10137133/ /pubmed/37185413 http://dx.doi.org/10.3390/curroncol30040300 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Jialing Lu, Chengxing Jiang, Ziren Alemayehu, Demissie Nie, Lei Chu, Haitao Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials |
title | Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials |
title_full | Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials |
title_fullStr | Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials |
title_full_unstemmed | Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials |
title_short | Borrowing Concurrent Information from Non-Concurrent Control to Enhance Statistical Efficiency in Platform Trials |
title_sort | borrowing concurrent information from non-concurrent control to enhance statistical efficiency in platform trials |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137133/ https://www.ncbi.nlm.nih.gov/pubmed/37185413 http://dx.doi.org/10.3390/curroncol30040300 |
work_keys_str_mv | AT liujialing borrowingconcurrentinformationfromnonconcurrentcontroltoenhancestatisticalefficiencyinplatformtrials AT luchengxing borrowingconcurrentinformationfromnonconcurrentcontroltoenhancestatisticalefficiencyinplatformtrials AT jiangziren borrowingconcurrentinformationfromnonconcurrentcontroltoenhancestatisticalefficiencyinplatformtrials AT alemayehudemissie borrowingconcurrentinformationfromnonconcurrentcontroltoenhancestatisticalefficiencyinplatformtrials AT nielei borrowingconcurrentinformationfromnonconcurrentcontroltoenhancestatisticalefficiencyinplatformtrials AT chuhaitao borrowingconcurrentinformationfromnonconcurrentcontroltoenhancestatisticalefficiencyinplatformtrials |