Implementation of an Alternative Method for Assessing Competing Risks: Restricted Mean Time Lost.
In clinical and epidemiologic studies, hazard ratios are often applied to compare treatment effects between 2 groups for survival data. For competing-risks data, the corresponding quantities of interest are cause-specific hazard ratios and subdistribution hazard ratios. However, they both have some...
| Publicado en: | American Journal of Epidemiology Vol. 191; no. 1; pp. 163 - 173 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Oxford University Press / USA
Jan2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=154736383&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 154736383 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00029262 1X1 jtl: American Journal of Epidemiology issn: 00029262 maglogo: N pubinfo: dt: Jan2022 vid: 191 iid: 1 pid: 622 pub: Oxford University Press / USA artinfo: ui: 154736383 154736383 154736383 10.1093/aje/kwab235 154736383 ppf: 163 ppct: 10 formats: tig: atl: Implementation of an Alternative Method for Assessing Competing Risks: Restricted Mean Time Lost. aug: au: Wu, Hongji Yuan, Hao Yang, Zijing Hou, Yawen Chen, Zheng sug: subj: Survival Analysis Risk Assessment Cox Proportional Hazards Model Causality Sample Size Simulations Human Time Factors Hypothesis ab: In clinical and epidemiologic studies, hazard ratios are often applied to compare treatment effects between 2 groups for survival data. For competing-risks data, the corresponding quantities of interest are cause-specific hazard ratios and subdistribution hazard ratios. However, they both have some limitations related to model assumptions and clinical interpretation. Therefore, we recommend restricted mean time lost (RMTL) as an alternative measure that is easy to interpret in a competing-risks framework. Based on the difference in RMTL (RMTLd), we propose a new estimator, hypothetical test, and sample-size formula. Simulation results show that estimation of the RMTLd is accurate and that the RMTLd test has robust statistical performance (both type I error and statistical power). The results of 3 example analyses also verify the performance of the RMTLd test. From the perspectives of clinical interpretation, application conditions, and statistical performance, we recommend that the RMTLd be reported along with the hazard ratio in analyses of competing-risks data and that the RMTLd even be regarded as the primary outcome when the proportional hazards assumption fails. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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