Literature DB >> 25265406

Immortal time bias in drug safety cohort studies: spontaneous abortion following nonsteroidal antiinflammatory drug exposure.

Sharon Daniel1, Gideon Koren2, Eitan Lunenfeld3, Amalia Levy4.   

Abstract

OBJECTIVE: Experimental research of drug safety in pregnancy is generally not feasible because of ethical issues. Therefore, most of the information about drug safety in general and teratogenicity in particular is obtained through observational studies, which require careful methodologic design to obtain unbiased results. Immortal time bias occurs when some cases do not "survive" sufficient time in the study, and as such, they have reduced chances of being defined as "exposed" simply because the durations of their follow-ups were shorter. For example, studies that examine the risk for spontaneous abortions in women exposed to a drug during pregnancy are susceptible to immortal time bias because the chance of drug exposure increases the longer a pregnancy lasts. Therefore, the drug tested may falsely be found protective against the outcome tested. The objective of the current study was to illustrate the extent of immortal time bias using a cohort study of pregnancies assessing the risk for spontaneous abortions following nonsteroidal antiinflammatory drug exposure. STUDY
DESIGN: We assembled 3 databases containing data on spontaneous abortions, births and drug dispensions to create the present study's cohort. The risk for spontaneous abortion was assessed using 2 statistical analysis methods that were compared for 2 definitions of exposure (dichotomous, exposed vs unexposed, regular Cox regression vs Cox regression with time-varying exposure).
RESULTS: Significant differences were found in the risk for spontaneous abortions between the 2 statistical methods, both for groups and for most specific nonsteroidal antiinflammatory drugs (nonselective Cox inhibitors - hazard ratio, 0.70; 95% confidence interval, 0.61-0.94 vs hazard ratio, 1.10; 95% confidence interval, 0.99-1.22 for dichotomous vs time-varying exposure analyses, respectively). Furthermore, a significant correlation was found between the median misclassified immortal time for each drug and the extent of the bias.
CONCLUSION: Immortal time bias can easily occur in cohort studies assessing the risk for adverse pregnancy outcomes following exposure to drugs. One way to prevent such a bias is by defining exposure only from the time of exposure during follow-up onward using a time-varying exposure analysis.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  NSAIDs; ibuprofen; immortal time bias; miscarriage; spontaneous abortions

Mesh:

Substances:

Year:  2014        PMID: 25265406     DOI: 10.1016/j.ajog.2014.09.028

Source DB:  PubMed          Journal:  Am J Obstet Gynecol        ISSN: 0002-9378            Impact factor:   8.661


  8 in total

1.  Constructing Causal Diagrams for Common Perinatal Outcomes: Benefits, Limitations and Motivating Examples with Maternal Antidepressant Use in Pregnancy.

Authors:  Gretchen Bandoli; Kristin Palmsten; Katrina F Flores; Christina D Chambers
Journal:  Paediatr Perinat Epidemiol       Date:  2016-05-10       Impact factor: 3.980

2.  Power in numbers.

Authors:  Evelyne Vinet; Eliza F Chakravarty; Megan E B Clowse
Journal:  Rheumatology (Oxford)       Date:  2018-07-01       Impact factor: 7.580

Review 3.  Ongoing Pharmacological Management of Chronic Pain in Pregnancy.

Authors:  Bengt Källén; Margareta Reis
Journal:  Drugs       Date:  2016-06       Impact factor: 9.546

4.  Invited Commentary: Influenza, Influenza Immunization, and Pregnancy-It's About Time.

Authors:  Jennifer A Hutcheon; David A Savitz
Journal:  Am J Epidemiol       Date:  2016-07-22       Impact factor: 4.897

5.  Risk of Preterm or Small-for-Gestational-Age Birth After Influenza Vaccination During Pregnancy: Caveats When Conducting Retrospective Observational Studies.

Authors:  Gabriela Vazquez-Benitez; Elyse O Kharbanda; Allison L Naleway; Heather Lipkind; Lakshmi Sukumaran; Natalie L McCarthy; Saad B Omer; Lei Qian; Stanley Xu; Michael L Jackson; Vinutha Vijayadev; Nicola P Klein; James D Nordin
Journal:  Am J Epidemiol       Date:  2016-07-22       Impact factor: 4.897

6.  Immortal Time Bias in Observational Studies of Time-to-Event Outcomes: Assessing Effects of Postmastectomy Radiation Therapy Using the National Cancer Database.

Authors:  Parul Agarwal; Erin Moshier; Meng Ru; Nisha Ohri; Ronald Ennis; Kenneth Rosenzweig; Madhu Mazumdar
Journal:  Cancer Control       Date:  2018 Jan-Dec       Impact factor: 3.302

7.  Educational note: addressing special cases of bias that frequently occur in perinatal epidemiology.

Authors:  Andreas M Neophytou; Marianthi-Anna Kioumourtzoglou; Dana E Goin; Kristin C Darwin; Joan A Casey
Journal:  Int J Epidemiol       Date:  2021-03-03       Impact factor: 7.196

Review 8.  Longitudinal Methods for Modeling Exposures in Pharmacoepidemiologic Studies in Pregnancy.

Authors:  Mollie E Wood; Angela Lupattelli; Kristin Palmsten; Gretchen Bandoli; Caroline Hurault-Delarue; Christine Damase-Michel; Christina D Chambers; Hedvig M E Nordeng; Marleen M H J van Gelder
Journal:  Epidemiol Rev       Date:  2022-01-14       Impact factor: 6.222

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.