Literature DB >> 22262593

When should case-only designs be used for safety monitoring of medical products?

Malcolm Maclure1, Bruce Fireman, Jennifer C Nelson, Wei Hua, Azadeh Shoaibi, Antonio Paredes, David Madigan.   

Abstract

PURPOSE: To assess case-only designs for surveillance with administrative databases.
METHODS: We reviewed literature on two designs that are observational analogs to crossover experiments: the self-controlled case series (SCCS) and the case-crossover (CCO) design.
RESULTS: SCCS views the 'experiment' prospectively, comparing outcome risks in windows with different exposures. CCO retrospectively compares exposure frequencies in case and control windows. The main strength of case-only designs is they entail self-controlled analyses that eliminate confounding and selection bias by time-invariant characteristics not recorded in healthcare databases. They also protect privacy and are computationally efficient, as they require fewer subjects and variables. They are better than cohort designs for investigating transient effects of accurately recorded preventive agents, for example, vaccines. They are problematic if timing of self-administration is sporadic and dissociated from dispensing times, for example, analgesics. They tend to have less exposure misclassification bias and time-varying confounding if exposures are brief. Standard SCCS designs are bidirectional (using time both before and after the first exposure event), so they are more susceptible than CCOs to reverse-causality bias, including immortal-time bias. This is true also for sequence symmetry analysis, a simplified SCCS. Unidirectional CCOs use only time before the outcome, so they are less affected by reverse causality but susceptible to exposure-trend bias. Modifications of SCCS and CCO partially deal with these biases. The head-to-head comparison of multiple products helps to control residual biases.
CONCLUSION: The case-only analyses of intermittent users complement the cohort analyses of prolonged users because their different biases compensate for one another.
Copyright © 2012 John Wiley & Sons, Ltd.

Mesh:

Year:  2012        PMID: 22262593     DOI: 10.1002/pds.2330

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


  55 in total

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3.  A comparison of the empirical performance of methods for a risk identification system.

Authors:  Patrick B Ryan; Paul E Stang; J Marc Overhage; Marc A Suchard; Abraham G Hartzema; William DuMouchel; Christian G Reich; Martijn J Schuemie; David Madigan
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4.  Application of a self-controlled case series study to a database study in children.

Authors:  Hanae Ueyama; Shiro Hinotsu; Shiro Tanaka; Hisashi Urushihara; Masaki Nakamura; Yuji Nakamura; Koji Kawakami
Journal:  Drug Saf       Date:  2014-04       Impact factor: 5.606

5.  Comment on: "Desideratum for evidence-based epidemiology".

Authors:  Sean Hennessy; Charles E Leonard
Journal:  Drug Saf       Date:  2015-01       Impact factor: 5.606

6.  Concurrent use of benzodiazepines, antidepressants, and opioid analgesics with zolpidem and risk for suicide: a case-control and case-crossover study.

Authors:  Hi Gin Sung; Junquing Li; Jin Hyun Nam; Dae Yeon Won; BongKyoo Choi; Ju-Young Shin
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Authors:  Katsiaryna Bykov; Joshua J Gagne
Journal:  Drug Saf       Date:  2017-02       Impact factor: 5.606

Review 8.  Sequence symmetry analysis in pharmacovigilance and pharmacoepidemiologic studies.

Authors:  Edward Chia-Cheng Lai; Nicole Pratt; Cheng-Yang Hsieh; Swu-Jane Lin; Anton Pottegård; Elizabeth E Roughead; Yea-Huei Kao Yang; Jesper Hallas
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Authors:  Charles E Leonard; Colleen M Brensinger; Thanh Phuong Pham Nguyen; John R Horn; Sophie Chung; Warren B Bilker; Sascha Dublin; Samantha E Soprano; Ghadeer K Dawwas; David W Oslin; Douglas J Wiebe; Sean Hennessy
Journal:  Biomed Pharmacother       Date:  2020-07-30       Impact factor: 6.529

10.  An evaluation of the THIN database in the OMOP Common Data Model for active drug safety surveillance.

Authors:  Xiaofeng Zhou; Sundaresan Murugesan; Harshvinder Bhullar; Qing Liu; Bing Cai; Chuck Wentworth; Andrew Bate
Journal:  Drug Saf       Date:  2013-02       Impact factor: 5.606

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