The Proper Use and Reporting of Survival Analysis and Cox Regression.


Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
05 2022
Historique:
received: 31 05 2021
accepted: 27 06 2021
entrez: 4 5 2022
pubmed: 5 5 2022
medline: 6 5 2022
Statut: ppublish

Résumé

Survival analyses are heavily used to analyze data in which the time to event is of interest. The purpose of this paper is to introduce some fundamental concepts for survival analyses in medical studies. We comprehensively review current survival methodologies, such as the nonparametric Kaplan-Meier method used to estimate survival probability, the log-rank test, one of the most popular tests for comparing survival curves, and the Cox proportional hazard model, which is used for building the relationship between survival time and specific risk factors. More advanced methods, such as time-dependent receiver operating characteristic, restricted mean survival time, and time-dependent covariates are also introduced. This tutorial is aimed toward covering the basics of survival analysis. We used a neurosurgical case series of surgically treated brain metastases from non-small cell lung cancer patients as an example. The survival time was defined from the date of craniotomy to the date of patient death. This work is an attempt to encourage more investigators/medical practitioners to use survival analyses appropriately in medical research. We highlight some statistical issues, make recommendations, and provide more advanced survival modeling in this aspect.

Sections du résumé

BACKGROUND
Survival analyses are heavily used to analyze data in which the time to event is of interest. The purpose of this paper is to introduce some fundamental concepts for survival analyses in medical studies.
METHODS
We comprehensively review current survival methodologies, such as the nonparametric Kaplan-Meier method used to estimate survival probability, the log-rank test, one of the most popular tests for comparing survival curves, and the Cox proportional hazard model, which is used for building the relationship between survival time and specific risk factors. More advanced methods, such as time-dependent receiver operating characteristic, restricted mean survival time, and time-dependent covariates are also introduced.
RESULTS
This tutorial is aimed toward covering the basics of survival analysis. We used a neurosurgical case series of surgically treated brain metastases from non-small cell lung cancer patients as an example. The survival time was defined from the date of craniotomy to the date of patient death.
CONCLUSIONS
This work is an attempt to encourage more investigators/medical practitioners to use survival analyses appropriately in medical research. We highlight some statistical issues, make recommendations, and provide more advanced survival modeling in this aspect.

Identifiants

pubmed: 35505548
pii: S1878-8750(21)00973-6
doi: 10.1016/j.wneu.2021.06.132
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

303-309

Informations de copyright

Copyright © 2021 Elsevier Inc. All rights reserved.

Auteurs

Pei-Fang Su (PF)

Department of Statistics, National Cheng Kung University, Tainan, Taiwan. Electronic address: pfsu@ncku.edu.tw.

Chou-Ching K Lin (CK)

Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.

Jo-Ying Hung (JY)

Department of Statistics, National Cheng Kung University, Tainan, Taiwan.

Jung-Shun Lee (JS)

Division of Neurosurgery, Department of Surgery, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan.

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