Informative Censoring-A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data.
Lin Hung-Mo, Liu Sean T H, Levin Matthew A, Williamson John, Bouvier Nicole M, Aberg Judith A, Reich David, Egorova Natalia
Life (Basel, Switzerland) · 2023 · PMID 36676159 · 인용 12
(1)
Background: Several retrospective observational analyzed treatment outcomes for COVID-19; (2)
Methods: Inverse probability of censoring weighting (IPCW) was applied to correct for bias due to informative censoring in database of hospitalized patients who did and did not receive convalescent plasma; (3)
Results: When compared with an IPCW analysis, overall mortality was overestimated using an unadjusted Kaplan-Meier curve, and hazard ratios for the older age group compared to the youngest were underestimated using the Cox proportional hazard models and 30-day mortality; (4)
Conclusions: An IPCW analysis provided stabilizing weights by hospital admission.