Survival analyses of COVID-19 data has its own unique features, in particular, the existence of two distinct events: death and release from the hospital within a very short period of time. This multiple-event situation belongs to a type where the occurrence of the first event prevents the second event to happen, and vice versa. We carried out two cause-specific univariate Cox regression survival analyses, one for time-to-death and another for time-to-release. Each survival analysis is further split into one for onset of symptom to event time and another for hospitalization to event time. We have also carried out a case-control (death vs. release) analysis without considering the time to event information. We observed that risk factors can be detected by either case-control or survival analysis, even though the goal of the two is quite different. We also observed that the two survival analyses may not both reveal a factor being a risk factor, but only one of them does. We prefer this two rounds of Cox regressions over mixture cure model which is only focused on time-to-death events which usually are sample size limited. By utilizing time-to-release events may greatly increase the sample size needed for revealing risk factors for COVID-19. Doi: 10.28991/SciMedJ-2021-03-SI-1 Full Text: PDF
CITATION STYLE
Cetin, S., Ulgen, A., Balci, P. O., Sivgin, H., Cetin, M., Sivgin, S., & Li, W. (2021). Survival Analyses of COVID-19 Patients in a Turkish Cohort: Comparison between Using Time to Death and Time to Release. SciMedicine Journal, 3, 1–9. https://doi.org/10.28991/scimedj-2021-03-si-1
Mendeley helps you to discover research relevant for your work.