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Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches
BACKGROUND: In clinical trials the study interest often lies in the comparison of a treatment to a control regarding a time to event endpoint. A composite endpoint allows to consider several time to event endpoints at once. Usually, only the time to the first occurring event for a patient is thereby...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818231/ https://www.ncbi.nlm.nih.gov/pubmed/35123397 http://dx.doi.org/10.1186/s12874-022-01511-1 |
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author | Ozga, Ann-Kathrin Rauch, Geraldine |
author_facet | Ozga, Ann-Kathrin Rauch, Geraldine |
author_sort | Ozga, Ann-Kathrin |
collection | PubMed |
description | BACKGROUND: In clinical trials the study interest often lies in the comparison of a treatment to a control regarding a time to event endpoint. A composite endpoint allows to consider several time to event endpoints at once. Usually, only the time to the first occurring event for a patient is thereby analyzed. However, an individual may experience more than one non-fatal event. Including all observed events in the analysis can increase the power and provides a more complete picture of the disease. Thus, analytical methods for recurrent events are required. A challenge is that the different event types belonging to the composite often are of different clinical relevance. In this case, weighting the event types according to their clinical relevance is an option. Different weight-based methods for composite time to event endpoints were proposed. So far, there exists no systematic comparison of these methods. METHODS: Within this work we provide a systematic comparison of three methods proposed for weighted composite endpoints in a recurrent event setting combining non-fatal and fatal events of different clinical relevance. We consider an extension of an approach proposed by Wei and Lachin, an approach by Rauch et al., and an approach by Bakal et al.. Comparison is done based on a simulation study and based on a clinical study example. RESULTS: For all three approaches closed formula test statistics are available. The Wei-Lachin approach and the approach by Rauch et al. show similar results in mean squared error. For the approach by Wei and Lachin confidence intervals are provided. The approach by Bakal et al. is not related to a quantifiable estimand. The relevance weights of the different approaches work on different level, i.e. either on cause-specific hazard ratios or on event count. CONCLUSION: The provided comparison and simulations can help to guide applied researchers to choose an adequate method for the analysis of composite endpoints combining (recurrent) events of different clinical relevance. The approach by Wei and Lachin and Rauch et al. can be recommended in scenarios where the composite effect is time-independent. The approach by Bakal et al. should be applied carefully. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12874-022-01511-1). |
format | Online Article Text |
id | pubmed-8818231 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88182312022-02-07 Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches Ozga, Ann-Kathrin Rauch, Geraldine BMC Med Res Methodol Research BACKGROUND: In clinical trials the study interest often lies in the comparison of a treatment to a control regarding a time to event endpoint. A composite endpoint allows to consider several time to event endpoints at once. Usually, only the time to the first occurring event for a patient is thereby analyzed. However, an individual may experience more than one non-fatal event. Including all observed events in the analysis can increase the power and provides a more complete picture of the disease. Thus, analytical methods for recurrent events are required. A challenge is that the different event types belonging to the composite often are of different clinical relevance. In this case, weighting the event types according to their clinical relevance is an option. Different weight-based methods for composite time to event endpoints were proposed. So far, there exists no systematic comparison of these methods. METHODS: Within this work we provide a systematic comparison of three methods proposed for weighted composite endpoints in a recurrent event setting combining non-fatal and fatal events of different clinical relevance. We consider an extension of an approach proposed by Wei and Lachin, an approach by Rauch et al., and an approach by Bakal et al.. Comparison is done based on a simulation study and based on a clinical study example. RESULTS: For all three approaches closed formula test statistics are available. The Wei-Lachin approach and the approach by Rauch et al. show similar results in mean squared error. For the approach by Wei and Lachin confidence intervals are provided. The approach by Bakal et al. is not related to a quantifiable estimand. The relevance weights of the different approaches work on different level, i.e. either on cause-specific hazard ratios or on event count. CONCLUSION: The provided comparison and simulations can help to guide applied researchers to choose an adequate method for the analysis of composite endpoints combining (recurrent) events of different clinical relevance. The approach by Wei and Lachin and Rauch et al. can be recommended in scenarios where the composite effect is time-independent. The approach by Bakal et al. should be applied carefully. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12874-022-01511-1). BioMed Central 2022-02-05 /pmc/articles/PMC8818231/ /pubmed/35123397 http://dx.doi.org/10.1186/s12874-022-01511-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Ozga, Ann-Kathrin Rauch, Geraldine Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches |
title | Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches |
title_full | Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches |
title_fullStr | Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches |
title_full_unstemmed | Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches |
title_short | Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches |
title_sort | weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818231/ https://www.ncbi.nlm.nih.gov/pubmed/35123397 http://dx.doi.org/10.1186/s12874-022-01511-1 |
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