Literature DB >> 20681003

A basic study design for expedited safety signal evaluation based on electronic healthcare data.

Sebastian Schneeweiss1.   

Abstract

Active drug safety monitoring based on longitudinal electronic healthcare databases (a Sentinel System), as outlined in recent FDA-commissioned reports, consists of several interlocked processes, including signal generation, signal strengthening, and signal evaluation. Once a signal of a potential drug safety issue is generated, signal strengthening and signal evaluation have to follow in short sequence in order to quickly provide as much information about the triggering drug-event association as possible. This paper proposes a basic study design based on the incident user cohort design for expedited signal evaluation in longitudinal healthcare databases. It will not resolve all methodological issues nor will it fit all study questions arising within the framework of a Sentinel System. It should rather be seen as a guidance that will fit the majority of situations and serve as a starting point for adaptations to specific studies. Such an approach will expedite and structure the process of study development and highlight specific assumptions, which is particularly valuable in a Sentinel System where signals are by definition preliminary and evaluation of signals is time critical. 2010 John Wiley & Sons, Ltd.

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 20681003      PMCID: PMC2917262          DOI: 10.1002/pds.1926

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


  33 in total

1.  Results of multivariable logistic regression, propensity matching, propensity adjustment, and propensity-based weighting under conditions of nonuniform effect.

Authors:  Tobias Kurth; Alexander M Walker; Robert J Glynn; K Arnold Chan; J Michael Gaziano; Klaus Berger; James M Robins
Journal:  Am J Epidemiol       Date:  2005-12-21       Impact factor: 4.897

2.  Estimability and estimation in case-referent studies.

Authors:  O Miettinen
Journal:  Am J Epidemiol       Date:  1976-02       Impact factor: 4.897

Review 3.  A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003.

Authors:  Peter C Austin
Journal:  Stat Med       Date:  2008-05-30       Impact factor: 2.373

4.  Increasing levels of restriction in pharmacoepidemiologic database studies of elderly and comparison with randomized trial results.

Authors:  Sebastian Schneeweiss; Amanda R Patrick; Til Stürmer; M Alan Brookhart; Jerry Avorn; Malcolm Maclure; Kenneth J Rothman; Robert J Glynn
Journal:  Med Care       Date:  2007-10       Impact factor: 2.983

5.  Managing drug-risk information--what to do with all those new numbers.

Authors:  Jerry Avorn; Sebastian Schneeweiss
Journal:  N Engl J Med       Date:  2009-07-27       Impact factor: 91.245

Review 6.  The risk of infection associated with tumor necrosis factor alpha antagonists: making sense of epidemiologic evidence.

Authors:  Daniel H Solomon; Mark Lunt; Sebastian Schneeweiss
Journal:  Arthritis Rheum       Date:  2008-04

7.  The case-crossover design: a method for studying transient effects on the risk of acute events.

Authors:  M Maclure
Journal:  Am J Epidemiol       Date:  1991-01-15       Impact factor: 4.897

8.  An application of propensity score methods to estimate the treatment effect of corticosteroids in patients with severe cutaneous adverse reactions.

Authors:  P Sekula; A Caputo; A Dunant; J-C Roujeau; M Mockenhaupt; A Sidoroff; M Schumacher
Journal:  Pharmacoepidemiol Drug Saf       Date:  2010-01       Impact factor: 2.890

9.  Evaluating medication effects outside of clinical trials: new-user designs.

Authors:  Wayne A Ray
Journal:  Am J Epidemiol       Date:  2003-11-01       Impact factor: 4.897

10.  Overadjustment bias and unnecessary adjustment in epidemiologic studies.

Authors:  Enrique F Schisterman; Stephen R Cole; Robert W Platt
Journal:  Epidemiology       Date:  2009-07       Impact factor: 4.822

View more
  93 in total

1.  Applying propensity scores estimated in a full cohort to adjust for confounding in subgroup analyses.

Authors:  Jeremy A Rassen; Robert J Glynn; Kenneth J Rothman; Soko Setoguchi; Sebastian Schneeweiss
Journal:  Pharmacoepidemiol Drug Saf       Date:  2011-12-08       Impact factor: 2.890

2.  Antidepressant agents and suicide death among US Department of Veterans Affairs patients in depression treatment.

Authors:  Marcia Valenstein; Hyungjin Myra Kim; Dara Ganoczy; Daniel Eisenberg; Paul N Pfeiffer; Karen Downing; Katherine Hoggatt; Mark Ilgen; Karen L Austin; Kara Zivin; Frederic C Blow; John F McCarthy
Journal:  J Clin Psychopharmacol       Date:  2012-06       Impact factor: 3.153

3.  High-dimensional versus conventional propensity scores in a comparative effectiveness study of coxibs and reduced upper gastrointestinal complications.

Authors:  E Garbe; S Kloss; M Suling; I Pigeot; S Schneeweiss
Journal:  Eur J Clin Pharmacol       Date:  2012-07-05       Impact factor: 2.953

4.  Counterpoint: the treatment decision design.

Authors:  M Alan Brookhart
Journal:  Am J Epidemiol       Date:  2015-10-26       Impact factor: 4.897

5.  Model Misspecification When Excluding Instrumental Variables From PS Models in Settings Where Instruments Modify the Effects of Covariates on Treatment.

Authors:  Richard Wyss; Alan R Ellis; Mark Lunt; M Alan Brookhart; Robert J Glynn; Til Stürmer
Journal:  Epidemiol Methods       Date:  2014-12

6.  Empirical performance of a new user cohort method: lessons for developing a risk identification and analysis system.

Authors:  Patrick B Ryan; Martijn J Schuemie; Susan Gruber; Ivan Zorych; David Madigan
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

7.  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
Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

8.  Risk of death and hospital admission for major medical events after initiation of psychotropic medications in older adults admitted to nursing homes.

Authors:  Krista F Huybrechts; Kenneth J Rothman; Rebecca A Silliman; M Alan Brookhart; Sebastian Schneeweiss
Journal:  CMAJ       Date:  2011-03-28       Impact factor: 8.262

9.  Plasmode simulation for the evaluation of pharmacoepidemiologic methods in complex healthcare databases.

Authors:  Jessica M Franklin; Sebastian Schneeweiss; Jennifer M Polinski; Jeremy A Rassen
Journal:  Comput Stat Data Anal       Date:  2014-04       Impact factor: 1.681

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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.