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Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews

BACKGROUND: Systematic reviews and meta-analysis of time-to-event outcomes are frequently published within the Cochrane Database of Systematic Reviews (CDSR). However, these outcomes are handled differently across meta-analyses. They can be analysed on the hazard ratio (HR) scale or can be dichotomi...

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Autores principales: Salika, Theodosia, Turner, Rebecca M., Fisher, David, Tierney, Jayne F., White, Ian R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934481/
https://www.ncbi.nlm.nih.gov/pubmed/35307005
http://dx.doi.org/10.1186/s12874-022-01541-9
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author Salika, Theodosia
Turner, Rebecca M.
Fisher, David
Tierney, Jayne F.
White, Ian R.
author_facet Salika, Theodosia
Turner, Rebecca M.
Fisher, David
Tierney, Jayne F.
White, Ian R.
author_sort Salika, Theodosia
collection PubMed
description BACKGROUND: Systematic reviews and meta-analysis of time-to-event outcomes are frequently published within the Cochrane Database of Systematic Reviews (CDSR). However, these outcomes are handled differently across meta-analyses. They can be analysed on the hazard ratio (HR) scale or can be dichotomized and analysed as binary outcomes using effect measures such as odds ratios (OR) or risk ratios (RR). We investigated the impact of reanalysing meta-analyses from the CDSR that used these different effect measures. METHODS: We extracted two types of meta-analysis data from the CDSR: either recorded in a binary form only (“binary”), or in binary form together with observed minus expected and variance statistics (“OEV”). We explored how results for time-to-event outcomes originally analysed as “binary” change when analysed using the complementary log–log (clog-log) link on a HR scale. For the data originally analysed as HRs (“OEV”), we compared these results to analysing them as binary on a HR scale using the clog-log link or using a logit link on an OR scale. RESULTS: The pooled HR estimates were closer to 1 than the OR estimates in the majority of meta-analyses. Important differences in between-study heterogeneity between the HR and OR analyses were also observed. These changes led to discrepant conclusions between the OR and HR scales in some meta-analyses. Situations under which the clog-log link performed better than logit link and vice versa were apparent, indicating that the correct choice of the method does matter. Differences between scales arise mainly when event probability is high and may occur via differences in between-study heterogeneity or via increased within-study standard error in the OR relative to the HR analyses. CONCLUSIONS: We identified that dichotomising time-to-event outcomes may be adequate for low event probabilities but not for high event probabilities. In meta-analyses where only binary data are available, the complementary log–log link may be a useful alternative when analysing time-to-event outcomes as binary, however the exact conditions need further exploration. These findings provide guidance on the appropriate methodology that should be used when conducting such meta-analyses. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01541-9.
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spelling pubmed-89344812022-03-23 Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews Salika, Theodosia Turner, Rebecca M. Fisher, David Tierney, Jayne F. White, Ian R. BMC Med Res Methodol Research BACKGROUND: Systematic reviews and meta-analysis of time-to-event outcomes are frequently published within the Cochrane Database of Systematic Reviews (CDSR). However, these outcomes are handled differently across meta-analyses. They can be analysed on the hazard ratio (HR) scale or can be dichotomized and analysed as binary outcomes using effect measures such as odds ratios (OR) or risk ratios (RR). We investigated the impact of reanalysing meta-analyses from the CDSR that used these different effect measures. METHODS: We extracted two types of meta-analysis data from the CDSR: either recorded in a binary form only (“binary”), or in binary form together with observed minus expected and variance statistics (“OEV”). We explored how results for time-to-event outcomes originally analysed as “binary” change when analysed using the complementary log–log (clog-log) link on a HR scale. For the data originally analysed as HRs (“OEV”), we compared these results to analysing them as binary on a HR scale using the clog-log link or using a logit link on an OR scale. RESULTS: The pooled HR estimates were closer to 1 than the OR estimates in the majority of meta-analyses. Important differences in between-study heterogeneity between the HR and OR analyses were also observed. These changes led to discrepant conclusions between the OR and HR scales in some meta-analyses. Situations under which the clog-log link performed better than logit link and vice versa were apparent, indicating that the correct choice of the method does matter. Differences between scales arise mainly when event probability is high and may occur via differences in between-study heterogeneity or via increased within-study standard error in the OR relative to the HR analyses. CONCLUSIONS: We identified that dichotomising time-to-event outcomes may be adequate for low event probabilities but not for high event probabilities. In meta-analyses where only binary data are available, the complementary log–log link may be a useful alternative when analysing time-to-event outcomes as binary, however the exact conditions need further exploration. These findings provide guidance on the appropriate methodology that should be used when conducting such meta-analyses. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01541-9. BioMed Central 2022-03-20 /pmc/articles/PMC8934481/ /pubmed/35307005 http://dx.doi.org/10.1186/s12874-022-01541-9 Text en © The Author(s) 2022 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
Salika, Theodosia
Turner, Rebecca M.
Fisher, David
Tierney, Jayne F.
White, Ian R.
Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews
title Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews
title_full Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews
title_fullStr Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews
title_full_unstemmed Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews
title_short Implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the Cochrane Database of Systematic Reviews
title_sort implications of analysing time-to-event outcomes as binary in meta-analysis: empirical evidence from the cochrane database of systematic reviews
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934481/
https://www.ncbi.nlm.nih.gov/pubmed/35307005
http://dx.doi.org/10.1186/s12874-022-01541-9
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