Evaluation of Time-Varying Biomarkers in Mortality Outcome in COVID-19: an Application of Extended Cox Regression Model.
COVID-19 dataset
Cox PH model
LOWESS plot
Proportional hazard assumption
extended Cox model
Journal
Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH
ISSN: 0353-8109
Titre abrégé: Acta Inform Med
Pays: Bosnia and Herzegovina
ID NLM: 101147064
Informations de publication
Date de publication:
Dec 2022
Dec 2022
Historique:
received:
27
06
2022
accepted:
05
08
2022
entrez:
5
12
2022
pubmed:
6
12
2022
medline:
6
12
2022
Statut:
ppublish
Résumé
COVID-19 pandemic has created many challenges for clinicians. The monitoring trend for laboratory biomarkers is helpful to provide additional information to determine the role of those in the severity status and death outcome. This article aimed to evaluate the time-varying biomarkers by LOWESS Plot, check the proportional hazard assumption, and use to extended Cox model if it is violated. In the retrospective study, we evaluated a total of 1641 samples of confirmed patients with COVID-19 from October until March 2021 and referred them to the central hospital of Ayatollah Rohani Hospital affiliated with Babol University of medical sciences, Iran. We measured four biomarkers AST, LDH, NLR, and lymphocyte in over the hospitalization to find out the influence of those on the rate of death of COVID-19 patients. The standard Cox model suggested that all biomarkers were prognostic factors of death (AST: HR=2.89, P<0.001, Lymphocyte: HR=2.60, P=0.004, LDH: HR=2.60, P=0.006, NLR: HR=1.80, P<0.001). The additional evaluation showed that the PH assumption was not met for the NLR biomarker. NLR biomarkers had a significant time-varying effect, and its effect increase over time (HR(t)=exp (0.234+0.261×log(t)), p=0.001). While the main effect of NLR did not show any significant effect on death outcome (HR=1.26, P=0.097). The reversal of results between the Cox PH model and the extended Cox model provides insight into the value of considering time-varying covariates in the analysis, which can lead to misleading results otherwise.
Sections du résumé
Background
UNASSIGNED
COVID-19 pandemic has created many challenges for clinicians. The monitoring trend for laboratory biomarkers is helpful to provide additional information to determine the role of those in the severity status and death outcome.
Objective
UNASSIGNED
This article aimed to evaluate the time-varying biomarkers by LOWESS Plot, check the proportional hazard assumption, and use to extended Cox model if it is violated.
Methods
UNASSIGNED
In the retrospective study, we evaluated a total of 1641 samples of confirmed patients with COVID-19 from October until March 2021 and referred them to the central hospital of Ayatollah Rohani Hospital affiliated with Babol University of medical sciences, Iran. We measured four biomarkers AST, LDH, NLR, and lymphocyte in over the hospitalization to find out the influence of those on the rate of death of COVID-19 patients.
Results
UNASSIGNED
The standard Cox model suggested that all biomarkers were prognostic factors of death (AST: HR=2.89, P<0.001, Lymphocyte: HR=2.60, P=0.004, LDH: HR=2.60, P=0.006, NLR: HR=1.80, P<0.001). The additional evaluation showed that the PH assumption was not met for the NLR biomarker. NLR biomarkers had a significant time-varying effect, and its effect increase over time (HR(t)=exp (0.234+0.261×log(t)), p=0.001). While the main effect of NLR did not show any significant effect on death outcome (HR=1.26, P=0.097).
Conclusion
UNASSIGNED
The reversal of results between the Cox PH model and the extended Cox model provides insight into the value of considering time-varying covariates in the analysis, which can lead to misleading results otherwise.
Identifiants
pubmed: 36467324
doi: 10.5455/aim.2022.30.295-301
pii: AIM-30-295
pmc: PMC9665419
doi:
Types de publication
Journal Article
Langues
eng
Pagination
295-301Informations de copyright
© 2022 Zahra Geraili, Karimollah Hajian-Tilaki, Masomeh Bayani, Seyed Reza Hosseini, Soraya Khafri, Soheil Ebrahimpour, Mostafa Javanian, Arefeh Babazadeh, Mehran Shokri.
Déclaration de conflit d'intérêts
There are no conflicts of interest.
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