Literature DB >> 15073755

Case-crossover and case-time-control designs as alternatives in pharmacoepidemiologic research.

S Schneeweiss1, T Stürmer, M Maclure.   

Abstract

Standard cohort and case-control designs are suited to the study of cumulative effects of chronic exposures, but they are prone to confounding by indication. Case-crossover and case-time-control studies are especially useful for studying intermittent exposures with transient effects, and are less susceptible to confounding by indication. Each design has its strengths and weaknesses. Despite the increasing availability of automated databases, cohort studies are usually time consuming and expensive, and therefore not preferred for time-critical decisions. In case-control studies, the selection of appropriate controls can be difficult and time consuming, and sometimes impractical when the exposure is rare. Case-crossover studies use the exposure history of each case as his or her own control to examine the effect of transient exposures on acute events. It further allows to study the time relationship of immediate effects to the exposure. This design eliminates between-person confounding by constant characteristics, including chronic indications. Because exposure data for the case and control periods are provided by the same person, the problems of differential recall may be reduced in many but not all case-crossover studies. Bias can result from temporal changes in prescribing or within-person confounding, including transient indication or changes in disease severity. The case-time-control design is an elaboration of the case-crossover design, which uses exposure history data from a traditional control group to estimate and adjust for the bias from temporal changes in prescribing. This paper will present a structured decision table of when to use which design in pharmacoepidemiologic research. In conclusion, case-crossover and case-time-control studies are the designs of choice when separating acute effects from chronic effects of transient exposures and if confounding by indication is an outstanding problem. Copyright 1997 John Wiley & Sons, Ltd.

Entities:  

Year:  1997        PMID: 15073755     DOI: 10.1002/(SICI)1099-1557(199710)6:3+<S51::AID-PDS301>3.0.CO;2-S

Source DB:  PubMed          Journal:  Pharmacoepidemiol Drug Saf        ISSN: 1053-8569            Impact factor:   2.890


  27 in total

1.  Interactive Cohort Identification of Sleep Disorder Patients Using Natural Language Processing and i2b2.

Authors:  W Chen; R Kowatch; S Lin; M Splaingard; Y Huang
Journal:  Appl Clin Inform       Date:  2015-05-27       Impact factor: 2.342

2.  Evaluation of the Case-Crossover (CCO) Study Design for Adverse Drug Event Detection.

Authors:  Zachary Burningham; Tao He; Chia-Chen Teng; Xi Zhou; Jonathan Nebeker; Brian C Sauer
Journal:  Drug Saf       Date:  2017-09       Impact factor: 5.606

3.  Use of Negative Control Exposure Analysis to Evaluate Confounding: An Example of Acetaminophen Exposure and Attention-Deficit/Hyperactivity Disorder in Nurses' Health Study II.

Authors:  Zeyan Liew; Marianthi-Anna Kioumourtzoglou; Andrea L Roberts; Éilis J O'Reilly; Alberto Ascherio; Marc G Weisskopf
Journal:  Am J Epidemiol       Date:  2019-04-01       Impact factor: 4.897

4.  Nonsteroidal Anti-Inflammatory Drugs and Risk of First Hospitalization for Heart Failure in Patients with No History of Heart Failure: A Population-Based Case-Crossover Study.

Authors:  Sung-Po Huang; Yao-Chun Wen; Shih-Tsung Huang; Chih-Wan Lin; Tzung-Dau Wang; Fei-Yuan Hsiao
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

Review 5.  Methods to control for unmeasured confounding in pharmacoepidemiology: an overview.

Authors:  Md Jamal Uddin; Rolf H H Groenwold; Mohammed Sanni Ali; Anthonius de Boer; Kit C B Roes; Muhammad A B Chowdhury; Olaf H Klungel
Journal:  Int J Clin Pharm       Date:  2016-04-18

6.  Case-crossover design and its implementation in R.

Authors:  Zhongheng Zhang
Journal:  Ann Transl Med       Date:  2016-09

7.  Newly initiated opioid treatment and the risk of fall-related injuries. A nationwide, register-based, case-crossover study in Sweden.

Authors:  Karin C Söderberg; Lucie Laflamme; Jette Möller
Journal:  CNS Drugs       Date:  2013-02       Impact factor: 5.749

8.  Risk of acute kidney injury associated with the use of fluoroquinolones.

Authors:  Steven T Bird; Mahyar Etminan; James M Brophy; Abraham G Hartzema; Joseph A C Delaney
Journal:  CMAJ       Date:  2013-06-03       Impact factor: 8.262

9.  Polypharmacy and patterns of prescription medication use among cancer survivors.

Authors:  Caitlin C Murphy; Hannah M Fullington; Carlos A Alvarez; Andrea C Betts; Simon J Craddock Lee; David A Haggstrom; Ethan A Halm
Journal:  Cancer       Date:  2018-04-12       Impact factor: 6.860

10.  Cholinesterase inhibitors and hospitalization for bradycardia: a population-based study.

Authors:  Laura Y Park-Wyllie; Muhammad M Mamdani; Ping Li; Sudeep S Gill; Andreas Laupacis; David N Juurlink
Journal:  PLoS Med       Date:  2009-09-29       Impact factor: 11.069

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.