Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data
(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 plas...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Life |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1729/13/1/210 |
| _version_ | 1797439621490016256 |
|---|---|
| author | Hung-Mo Lin Sean T. H. Liu Matthew A. Levin John Williamson Nicole M. Bouvier Judith A. Aberg David Reich Natalia Egorova |
| author_facet | Hung-Mo Lin Sean T. H. Liu Matthew A. Levin John Williamson Nicole M. Bouvier Judith A. Aberg David Reich Natalia Egorova |
| author_sort | Hung-Mo Lin |
| collection | DOAJ |
| description | (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. |
| first_indexed | 2024-03-09T11:55:44Z |
| format | Article |
| id | doaj.art-9ab274f5164e47fa9720a54a8cd3c3fd |
| institution | Directory Open Access Journal |
| issn | 2075-1729 |
| language | English |
| last_indexed | 2024-03-09T11:55:44Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Life |
| spelling | doaj.art-9ab274f5164e47fa9720a54a8cd3c3fd2023-11-30T23:09:31ZengMDPI AGLife2075-17292023-01-0113121010.3390/life13010210Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital DataHung-Mo Lin0Sean T. H. Liu1Matthew A. Levin2John Williamson3Nicole M. Bouvier4Judith A. Aberg5David Reich6Natalia Egorova7Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USADivision of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USADepartment of Anesthesiology, Perioperative and Pain Medicine, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USADivision of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, GA 30333, USADivision of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USADivision of Infectious Diseases, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USADepartment of Anesthesiology, Perioperative and Pain Medicine, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USADepartment of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA(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.https://www.mdpi.com/2075-1729/13/1/210censoringCOVID-19convalescent plasma |
| spellingShingle | Hung-Mo Lin Sean T. H. Liu Matthew A. Levin John Williamson Nicole M. Bouvier Judith A. Aberg David Reich Natalia Egorova Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data Life censoring COVID-19 convalescent plasma |
| title | Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data |
| title_full | Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data |
| title_fullStr | Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data |
| title_full_unstemmed | Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data |
| title_short | Informative Censoring—A Cause of Bias in Estimating COVID-19 Mortality Using Hospital Data |
| title_sort | informative censoring a cause of bias in estimating covid 19 mortality using hospital data |
| topic | censoring COVID-19 convalescent plasma |
| url | https://www.mdpi.com/2075-1729/13/1/210 |
| work_keys_str_mv | AT hungmolin informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata AT seanthliu informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata AT matthewalevin informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata AT johnwilliamson informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata AT nicolembouvier informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata AT judithaaberg informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata AT davidreich informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata AT nataliaegorova informativecensoringacauseofbiasinestimatingcovid19mortalityusinghospitaldata |