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An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk
INTRODUCTION: Competing risks arise when subjects are exposed to multiple mutually exclusive failure events, and the occurrence of one failure hinders the occurrence of other failure events. In the presence of competing risks, it is important to use methods accounting for competing events because fa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471619/ https://www.ncbi.nlm.nih.gov/pubmed/32913916 http://dx.doi.org/10.1016/j.conctc.2020.100639 |
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author | Haushona, Ndamonaonghenda Esterhuizen, Tonya M. Thabane, Lehana Machekano, Rhoderick |
author_facet | Haushona, Ndamonaonghenda Esterhuizen, Tonya M. Thabane, Lehana Machekano, Rhoderick |
author_sort | Haushona, Ndamonaonghenda |
collection | PubMed |
description | INTRODUCTION: Competing risks arise when subjects are exposed to multiple mutually exclusive failure events, and the occurrence of one failure hinders the occurrence of other failure events. In the presence of competing risks, it is important to use methods accounting for competing events because failure to account for these events might result in misleading inferences. METHODS AND OBJECTIVE: Using data from a multisite retrospective observational longitudinal study done in Ethiopia, we performed sensitivity analyses using Fine-Gray model, Cause-specific Cox (Cox-CSH) model, Cause-specific Accelerated Failure Time (CS-AFT) model, accounting for death as a competing risk to determine baseline covariates that are associated with a composite of unfavourable retention in care outcomes in people living with Human Immune Virus who were on both Isoniazid preventive therapy (IPT) and antiretroviral therapy (ART). Non-cause specific (non-CSH) model that does not account for competing risk was also performed. The composite outcome comprises of loss to follow-up, stopped treatment and death. Age, World Health Organisation (WHO) stage, gender, and CD4 count were the considered baseline covariates. RESULTS: We included 3578 patients in our analysis. WHO stage III-or-IV was significantly associated with the composite of unfavourable outcomes, Sub-hazard ratio (SHR) = 1.31, 95% confidence interval (CI):1.04–1.65 for the sub-distribution hazard model, hazard ratio [HR] = 1.31, 95% CI:1.05–1.65, for the Cox-CSH model, and HR = 0.81, 95% CI:0.69–0.96, for the CS-AFT model. Gender and WHO stage were found to be significantly associated with the composite of unfavourable outcomes, HR = 1.56, 95% CI:1.27–1.90, HR = 1.28, 95% CI: 1.06–1.55 for males and WHO stage III-or-IV, respectively for the non-CSH model. CONCLUSIONS: Results show that WHO stage III-or-IV is significantly associated with unfavourable outcomes. The results from competing risk models were consistent. However, results obtained from the non-CSH model were inconsistent with those obtained from competing risk analysis models. |
format | Online Article Text |
id | pubmed-7471619 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-74716192020-09-09 An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk Haushona, Ndamonaonghenda Esterhuizen, Tonya M. Thabane, Lehana Machekano, Rhoderick Contemp Clin Trials Commun Article INTRODUCTION: Competing risks arise when subjects are exposed to multiple mutually exclusive failure events, and the occurrence of one failure hinders the occurrence of other failure events. In the presence of competing risks, it is important to use methods accounting for competing events because failure to account for these events might result in misleading inferences. METHODS AND OBJECTIVE: Using data from a multisite retrospective observational longitudinal study done in Ethiopia, we performed sensitivity analyses using Fine-Gray model, Cause-specific Cox (Cox-CSH) model, Cause-specific Accelerated Failure Time (CS-AFT) model, accounting for death as a competing risk to determine baseline covariates that are associated with a composite of unfavourable retention in care outcomes in people living with Human Immune Virus who were on both Isoniazid preventive therapy (IPT) and antiretroviral therapy (ART). Non-cause specific (non-CSH) model that does not account for competing risk was also performed. The composite outcome comprises of loss to follow-up, stopped treatment and death. Age, World Health Organisation (WHO) stage, gender, and CD4 count were the considered baseline covariates. RESULTS: We included 3578 patients in our analysis. WHO stage III-or-IV was significantly associated with the composite of unfavourable outcomes, Sub-hazard ratio (SHR) = 1.31, 95% confidence interval (CI):1.04–1.65 for the sub-distribution hazard model, hazard ratio [HR] = 1.31, 95% CI:1.05–1.65, for the Cox-CSH model, and HR = 0.81, 95% CI:0.69–0.96, for the CS-AFT model. Gender and WHO stage were found to be significantly associated with the composite of unfavourable outcomes, HR = 1.56, 95% CI:1.27–1.90, HR = 1.28, 95% CI: 1.06–1.55 for males and WHO stage III-or-IV, respectively for the non-CSH model. CONCLUSIONS: Results show that WHO stage III-or-IV is significantly associated with unfavourable outcomes. The results from competing risk models were consistent. However, results obtained from the non-CSH model were inconsistent with those obtained from competing risk analysis models. Elsevier 2020-08-14 /pmc/articles/PMC7471619/ /pubmed/32913916 http://dx.doi.org/10.1016/j.conctc.2020.100639 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Haushona, Ndamonaonghenda Esterhuizen, Tonya M. Thabane, Lehana Machekano, Rhoderick An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk |
title | An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk |
title_full | An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk |
title_fullStr | An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk |
title_full_unstemmed | An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk |
title_short | An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk |
title_sort | empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471619/ https://www.ncbi.nlm.nih.gov/pubmed/32913916 http://dx.doi.org/10.1016/j.conctc.2020.100639 |
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