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Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods

BACKGROUND: Days alive without life support (DAWOLS) and similar outcomes that seek to summarise mortality and non-mortality experiences are increasingly used in critical care research. The use of these outcomes is challenged by different definitions and non-normal outcome distributions that complic...

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Autores principales: Granholm, Anders, Kaas-Hansen, Benjamin Skov, Lange, Theis, Munch, Marie Warrer, Harhay, Michael O., Zampieri, Fernando G., Perner, Anders, Møller, Morten Hylander, Jensen, Aksel Karl Georg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266319/
https://www.ncbi.nlm.nih.gov/pubmed/37316785
http://dx.doi.org/10.1186/s12874-023-01963-z
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author Granholm, Anders
Kaas-Hansen, Benjamin Skov
Lange, Theis
Munch, Marie Warrer
Harhay, Michael O.
Zampieri, Fernando G.
Perner, Anders
Møller, Morten Hylander
Jensen, Aksel Karl Georg
author_facet Granholm, Anders
Kaas-Hansen, Benjamin Skov
Lange, Theis
Munch, Marie Warrer
Harhay, Michael O.
Zampieri, Fernando G.
Perner, Anders
Møller, Morten Hylander
Jensen, Aksel Karl Georg
author_sort Granholm, Anders
collection PubMed
description BACKGROUND: Days alive without life support (DAWOLS) and similar outcomes that seek to summarise mortality and non-mortality experiences are increasingly used in critical care research. The use of these outcomes is challenged by different definitions and non-normal outcome distributions that complicate statistical analysis decisions. METHODS: We scrutinized the central methodological considerations when using DAWOLS and similar outcomes and provide a description and overview of the pros and cons of various statistical methods for analysis supplemented with a comparison of these methods using data from the COVID STEROID 2 randomised clinical trial. We focused on readily available regression models of increasing complexity (linear, hurdle-negative binomial, zero–one-inflated beta, and cumulative logistic regression models) that allow comparison of multiple treatment arms, adjustment for covariates and interaction terms to assess treatment effect heterogeneity. RESULTS: In general, the simpler models adequately estimated group means despite not fitting the data well enough to mimic the input data. The more complex models better fitted and thus better replicated the input data, although this came with increased complexity and uncertainty of estimates. While the more complex models can model separate components of the outcome distributions (i.e., the probability of having zero DAWOLS), this complexity means that the specification of interpretable priors in a Bayesian setting is difficult. Finally, we present multiple examples of how these outcomes may be visualised to aid assessment and interpretation. CONCLUSIONS: This summary of central methodological considerations when using, defining, and analysing DAWOLS and similar outcomes may help researchers choose the definition and analysis method that best fits their planned studies. TRIAL REGISTRATION: COVID STEROID 2 trial, ClinicalTrials.gov: NCT04509973, ctri.nic.in: CTRI/2020/10/028731. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-01963-z.
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spelling pubmed-102663192023-06-14 Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods Granholm, Anders Kaas-Hansen, Benjamin Skov Lange, Theis Munch, Marie Warrer Harhay, Michael O. Zampieri, Fernando G. Perner, Anders Møller, Morten Hylander Jensen, Aksel Karl Georg BMC Med Res Methodol Research BACKGROUND: Days alive without life support (DAWOLS) and similar outcomes that seek to summarise mortality and non-mortality experiences are increasingly used in critical care research. The use of these outcomes is challenged by different definitions and non-normal outcome distributions that complicate statistical analysis decisions. METHODS: We scrutinized the central methodological considerations when using DAWOLS and similar outcomes and provide a description and overview of the pros and cons of various statistical methods for analysis supplemented with a comparison of these methods using data from the COVID STEROID 2 randomised clinical trial. We focused on readily available regression models of increasing complexity (linear, hurdle-negative binomial, zero–one-inflated beta, and cumulative logistic regression models) that allow comparison of multiple treatment arms, adjustment for covariates and interaction terms to assess treatment effect heterogeneity. RESULTS: In general, the simpler models adequately estimated group means despite not fitting the data well enough to mimic the input data. The more complex models better fitted and thus better replicated the input data, although this came with increased complexity and uncertainty of estimates. While the more complex models can model separate components of the outcome distributions (i.e., the probability of having zero DAWOLS), this complexity means that the specification of interpretable priors in a Bayesian setting is difficult. Finally, we present multiple examples of how these outcomes may be visualised to aid assessment and interpretation. CONCLUSIONS: This summary of central methodological considerations when using, defining, and analysing DAWOLS and similar outcomes may help researchers choose the definition and analysis method that best fits their planned studies. TRIAL REGISTRATION: COVID STEROID 2 trial, ClinicalTrials.gov: NCT04509973, ctri.nic.in: CTRI/2020/10/028731. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-023-01963-z. BioMed Central 2023-06-14 /pmc/articles/PMC10266319/ /pubmed/37316785 http://dx.doi.org/10.1186/s12874-023-01963-z Text en © The Author(s) 2023 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
Granholm, Anders
Kaas-Hansen, Benjamin Skov
Lange, Theis
Munch, Marie Warrer
Harhay, Michael O.
Zampieri, Fernando G.
Perner, Anders
Møller, Morten Hylander
Jensen, Aksel Karl Georg
Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods
title Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods
title_full Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods
title_fullStr Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods
title_full_unstemmed Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods
title_short Use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods
title_sort use of days alive without life support and similar count outcomes in randomised clinical trials – an overview and comparison of methodological choices and analysis methods
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10266319/
https://www.ncbi.nlm.nih.gov/pubmed/37316785
http://dx.doi.org/10.1186/s12874-023-01963-z
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