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Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study
BACKGROUND: Non-proportional hazards are common with time-to-event data but the majority of randomised clinical trials (RCTs) are designed and analysed using approaches which assume the treatment effect follows proportional hazards (PH). Recent advances in oncology treatments have identified two for...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399795/ https://www.ncbi.nlm.nih.gov/pubmed/34454428 http://dx.doi.org/10.1186/s12874-021-01372-0 |
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author | Jachno, Kim Heritier, Stephane Wolfe, Rory |
author_facet | Jachno, Kim Heritier, Stephane Wolfe, Rory |
author_sort | Jachno, Kim |
collection | PubMed |
description | BACKGROUND: Non-proportional hazards are common with time-to-event data but the majority of randomised clinical trials (RCTs) are designed and analysed using approaches which assume the treatment effect follows proportional hazards (PH). Recent advances in oncology treatments have identified two forms of non-PH of particular importance - a time lag until treatment becomes effective, and an early effect of treatment that ceases after a period of time. In sample size calculations for treatment effects on time-to-event outcomes where information is based on the number of events rather than the number of participants, there is crucial importance in correct specification of the baseline hazard rate amongst other considerations. Under PH, the shape of the baseline hazard has no effect on the resultant power and magnitude of treatment effects using standard analytical approaches. However, in a non-PH context the appropriateness of analytical approaches can depend on the shape of the underlying hazard. METHODS: A simulation study was undertaken to assess the impact of clinically plausible non-constant baseline hazard rates on the power, magnitude and coverage of commonly utilized regression-based measures of treatment effect and tests of survival curve difference for these two forms of non-PH used in RCTs with time-to-event outcomes. RESULTS: In the presence of even mild departures from PH, the power, average treatment effect size and coverage were adversely affected. Depending on the nature of the non-proportionality, non-constant event rates could further exacerbate or somewhat ameliorate the losses in power, treatment effect magnitude and coverage observed. No single summary measure of treatment effect was able to adequately describe the full extent of a potentially time-limited treatment benefit whilst maintaining power at nominal levels. CONCLUSIONS: Our results show the increased importance of considering plausible potentially non-constant event rates when non-proportionality of treatment effects could be anticipated. In planning clinical trials with the potential for non-PH, even modest departures from an assumed constant baseline hazard could appreciably impact the power to detect treatment effects depending on the nature of the non-PH. Comprehensive analysis plans may be required to accommodate the description of time-dependent treatment effects. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01372-0. |
format | Online Article Text |
id | pubmed-8399795 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83997952021-08-30 Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study Jachno, Kim Heritier, Stephane Wolfe, Rory BMC Med Res Methodol Research BACKGROUND: Non-proportional hazards are common with time-to-event data but the majority of randomised clinical trials (RCTs) are designed and analysed using approaches which assume the treatment effect follows proportional hazards (PH). Recent advances in oncology treatments have identified two forms of non-PH of particular importance - a time lag until treatment becomes effective, and an early effect of treatment that ceases after a period of time. In sample size calculations for treatment effects on time-to-event outcomes where information is based on the number of events rather than the number of participants, there is crucial importance in correct specification of the baseline hazard rate amongst other considerations. Under PH, the shape of the baseline hazard has no effect on the resultant power and magnitude of treatment effects using standard analytical approaches. However, in a non-PH context the appropriateness of analytical approaches can depend on the shape of the underlying hazard. METHODS: A simulation study was undertaken to assess the impact of clinically plausible non-constant baseline hazard rates on the power, magnitude and coverage of commonly utilized regression-based measures of treatment effect and tests of survival curve difference for these two forms of non-PH used in RCTs with time-to-event outcomes. RESULTS: In the presence of even mild departures from PH, the power, average treatment effect size and coverage were adversely affected. Depending on the nature of the non-proportionality, non-constant event rates could further exacerbate or somewhat ameliorate the losses in power, treatment effect magnitude and coverage observed. No single summary measure of treatment effect was able to adequately describe the full extent of a potentially time-limited treatment benefit whilst maintaining power at nominal levels. CONCLUSIONS: Our results show the increased importance of considering plausible potentially non-constant event rates when non-proportionality of treatment effects could be anticipated. In planning clinical trials with the potential for non-PH, even modest departures from an assumed constant baseline hazard could appreciably impact the power to detect treatment effects depending on the nature of the non-PH. Comprehensive analysis plans may be required to accommodate the description of time-dependent treatment effects. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01372-0. BioMed Central 2021-08-28 /pmc/articles/PMC8399795/ /pubmed/34454428 http://dx.doi.org/10.1186/s12874-021-01372-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Jachno, Kim Heritier, Stephane Wolfe, Rory Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study |
title | Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study |
title_full | Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study |
title_fullStr | Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study |
title_full_unstemmed | Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study |
title_short | Impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study |
title_sort | impact of a non-constant baseline hazard on detection of time-dependent treatment effects: a simulation study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399795/ https://www.ncbi.nlm.nih.gov/pubmed/34454428 http://dx.doi.org/10.1186/s12874-021-01372-0 |
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