Time-Related Biases in Nonrandomized COVID-19–Era Studies Using Real-world Data | Hematology | JN Learning | AMA Ed Hub [Skip to Content]
[Skip to Content Landing]

Time-Related Biases in Nonrandomized COVID-19–Era Studies Using Real-world Data

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME

The urgent response to the COVID-19 pandemic has highlighted the importance of diverse, real-world data sources, such as electronic health records, insurance claims, and patient registries, to further inform evidence-based care amid an evolving public health crisis. Real-world data have the potential to provide a wealth of rapid, actionable information and inform ongoing work to evaluate the effectiveness and safety of potential therapies, vaccines, or diagnostics for COVID-19.

Sign in to take quiz and track your certificates

Buy This Activity

JN Learning™ is the home for CME and MOC from the JAMA Network. Search by specialty or US state and earn AMA PRA Category 1 CME Credit™ from articles, audio, Clinical Challenges and more. Learn more about CME/MOC

Article Information

Corresponding Author: Gregory S. Calip, PharmD, MPH, PhD, Flatiron Health, Inc, 233 Spring St, New York, NY 10013 (gregory.calip@flatiron.com).

Published Online: June 17, 2021. doi:10.1001/jamaoncol.2021.1715

Conflict of Interest Disclosures: Dr Calip reported receiving grants from Pfizer outside the submitted work. Drs Calip, Miksad, and Sarkar report current employment with Flatiron Health, Inc, which is an independent subsidiary of the Roche group, and stock ownership in Roche. Drs Miksad and Sarkar also reported equity ownership in Flatiron Health, Inc (initiated before acquisition by Roche in 2018).

References
1.
Thompson  MA , Henderson  JP , Shah  PK ,  et al; for the COVID-19 and Cancer Consortium.  Association of convalescent plasma therapy with survival in patients with hematologic cancers and COVID-19.   JAMA Oncol. Published online June 17, 2021. doi:10.1001/jamaoncol.2021.1799Google Scholar
2.
Luke  TC , Kilbane  EM , Jackson  JL , Hoffman  SL .  Meta-analysis: convalescent blood products for Spanish influenza pneumonia: a future H5N1 treatment?   Ann Intern Med. 2006;145(8):599-609. doi:10.7326/0003-4819-145-8-200610170-00139 PubMedGoogle ScholarCrossref
3.
Joyner  MJ , Carter  RE , Senefeld  JW ,  et al.  Convalescent plasma antibody levels and the risk of death from COVID-19.   N Engl J Med. 2021;384(11):1015-1027. doi:10.1056/NEJMoa2031893 PubMedGoogle ScholarCrossref
4.
Chai  KL , Valk  SJ , Piechotta  V ,  et al.  Convalescent plasma or hyperimmune immunoglobulin for people with COVID-19: a living systematic review.   Cochrane Database Syst Rev. 2020;10:CD013600. doi:10.1002/14651858.CD013600.pub3PubMedGoogle Scholar
5.
Kaiser  P , Arnold  AM , Benkeser  D ,  et al.  Comparing methods to address bias in observational data: statin use and cardiovascular events in a US cohort.   Int J Epidemiol. 2018;47(1):246-254. doi:10.1093/ije/dyx179 PubMedGoogle ScholarCrossref
6.
Arbogast  PG , Ray  WA .  Performance of disease risk scores, propensity scores, and traditional multivariable outcome regression in the presence of multiple confounders.   Am J Epidemiol. 2011;174(5):613-620. doi:10.1093/aje/kwr143 PubMedGoogle ScholarCrossref
7.
Safety, tolerability, and efficacy of anti-spike (S) SARS-CoV-2 monoclonal antibodies for hospitalized adult patients with COVID-19. ClinicalTrials.gov identifier: NCT04426695. Accessed April 23, 2021. https://clinicaltrials.gov/ct2/show/NCT04426695
8.
Chubak  J , Boudreau  DM , Wirtz  HS , McKnight  B , Weiss  NS .  Threats to validity of nonrandomized studies of postdiagnosis exposures on cancer recurrence and survival.   J Natl Cancer Inst. 2013;105(19):1456-1462. doi:10.1093/jnci/djt211 PubMedGoogle ScholarCrossref
9.
Suissa  S .  Immortal time bias in pharmaco-epidemiology.   Am J Epidemiol. 2008;167(4):492-499. doi:10.1093/aje/kwm324PubMedGoogle ScholarCrossref
10.
Robins  JM , Hernán  MA , Brumback  B .  Marginal structural models and causal inference in epidemiology.   Epidemiology. 2000;11(5):550-560. doi:10.1097/00001648-200009000-00011 PubMedGoogle ScholarCrossref
If you are not a JN Learning subscriber, you can either:
Subscribe to JN Learning for one year
Buy this activity
jn-learning_Modal_Multimedia_LoginSubscribe_Purchase
Close
If you are not a JN Learning subscriber, you can either:
Subscribe to JN Learning for one year
Buy this activity
jn-learning_Modal_Multimedia_LoginSubscribe_Purchase
Close
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right
Close

Name Your Search

Save Search
Close
With a personal account, you can:
  • Track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
jn-learning_Modal_SaveSearch_NoAccess_Purchase
Close

Lookup An Activity

or

Close

My Saved Searches

You currently have no searches saved.

Close
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right
Close