nach oben

Drug Safety

Erschienen in:

01.10.2013 | Original Research Article

Variation in Choice of Study Design: Findings from the Epidemiology Design Decision Inventory and Evaluation (EDDIE) Survey

verfasst von: Paul E. Stang, Patrick B. Ryan, J. Marc Overhage, Martijn J. Schuemie, Abraham G. Hartzema, Emily Welebob

Erschienen in: Drug Safety | Sonderheft 1/2013

Einloggen, um Zugang zu erhalten

Abstract

Background

Researchers using observational data to understand drug effects must make a number of analytic design choices that suit the characteristics of the data and the subject of the study. Review of the published literature suggests that there is a lack of consistency even when addressing the same research question in the same database.

Objective

To characterize the degree of similarity or difference in the method and analysis choices made by observational database research experts when presented with research study scenarios.

Research Design

On-line survey using research scenarios on drug-effect studies to capture method selection and analysis choices that follow a dependency branching based on response to key questions.

Subjects

Voluntary participants experienced in epidemiological study design solicited for participation through registration on the Observational Medical Outcomes Partnership website, membership in particular professional organizations, or links in relevant newsletters.

Measures

Description (proportion) of respondents selecting particular methods and making specific analysis choices based on individual drug-outcome scenario pairs. The number of questions/decisions differed based on stem questions of study design, time-at-risk, outcome definition, and comparator.

Results

There is little consistency across scenarios, by drug or by outcome of interest, in the decisions made for design and analyses in scenarios using large healthcare databases. The most consistent choice was the cohort study design but variability in the other critical decisions was common.

Conclusions

There is great variation among epidemiologists in the design and analytical choices that they make when implementing analyses in observational healthcare databases. These findings confirm that it will be important to generate empiric evidence to inform these decisions and to promote a better understanding of the impact of standardization on research implementation.

Nur mit Berechtigung zugänglich

Strom B, editor. Pharmacoepidemiology. 4th ed. Sussex: John Wiley & Sons, Ltd; 2005.

Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol. 2005;58(4):323–37.PubMedCrossRef

Farrington CP, Nash J, Miller E. Case series analysis of adverse reactions to vaccines: a comparative evaluation. Am J Epidemiol. 1996;143(11):1165–73.PubMedCrossRef

Wessinger S, Kaplan M, Choi L, Williams M, Lau C, Sharp L, et al. Increased use of selective serotonin reuptake inhibitors in patients admitted with gastrointestinal haemorrhage: a multicentre retrospective analysis. Aliment Pharmacol Ther. 2006;23(7):937–44.PubMedCrossRef

Guyatt GH, Sackett DL, Sinclair JC, Hayward R, Cook DJ, Cook RJ. Users’ guides to the medical literature. IX. A method for grading health care recommendations. Evidence-Based Medicine Working Group. J Am Med Assoc. 1995;274(22):1800–4.CrossRef

Ryan PB, Madigan D, Stang PE, Marc Overhage J, Racoosin JA, Hartzema AG, et al. Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership. Stat Med. 2012;31(30):4401–15.PubMedCrossRef

Stang PE, Ryan PB, Dusetzina SB, Hartzema AG, Reich C, Overhage JM, et al. Health outcomes of interest in Observational Data: issues in identifying definitions in the literature. Health Outcome Res Med. 2012;3(1):e37–44.CrossRef

Ryan PB, Schuemie MJ, Welebob E, Duke J, Valentine S, Hartzema AG. Defining a reference set to support methodological research in drug safety. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0097-8

Trifiro G, Pariente A, Coloma PM, Kors JA, Polimeni G, Miremont-Salame G, et al. Data mining on electronic health record databases for signal detection in pharmacovigilance: which events to monitor? Pharmacoepidemiol Drug Saf 2009;18(12):1176–84.PubMedCrossRef

10.

Madigan DB, Ryan PB, Schuemie MJ. Does design matter? Systematic evaluation of the impact of analytical choices on effect estimates in observational studies. Ther Adv Drug Saf. 2013;4(2):53–62.CrossRef

11.

Ryan PB, Stang PE, Overhage JM, Suchard MA, Hartzema AG, DuMouchel W, et al. A comparison of the empirical performance of methods for a risk identification system. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0108-9

12.

Reich CG, Ryan PB, Schuemie MJ. Alternative outcome definitions and their effect on the performance of methods for observational outcome studies. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0111-1

13.

Gould AL. Accounting for multiplicity in the evaluation of “signals” obtained by data mining from spontaneous report adverse event databases. Biometrical J Biometrische Zeitschrift. 2007;49(1):151–65.CrossRef

14.

Schuemie MJ, Madigan D, Ryan PB. Empirical performance of Longitudinal Gamma Poisson Shrinker (LGPS) and Longitudinal Evaluation of Observational Profiles of Adverse events Related to Drugs (LEOPARD): lessons for developing a risk identification and analysis system. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0107-x

15.

Norén GN, Bergvall T, Ryan PB, Juhlin K, Schuemie MJ, Madigan D. Empirical performance of the calibrated self-controlled cohort analysis within temporal pattern discovery: lessons for developing a risk identification and analysis system. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0095-x

16.

Madigan D, Schuemie MJ, Ryan PB. Empirical performance of the case-control method: lessons for developing a risk identification and analysis system. Drug Saf (in this supplement issue). doi: 10.1007/s40264-013-0105-z

17.

Ryan PB, Schuemie MJ, Gruber S, Zorych I, Madigan D. Empirical performance of a new user cohort method: lessons for developing a risk identification and analysis system. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0099-6

18.

Suchard MA, Zorych I, Simpson SE, Schuemie MJ, Ryan PB, Madigan D. Empirical performance of the self-controlled case series design: lessons for developing a risk identification and analysis system. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0100-4

19.

Ryan PB, Schuemie MJ, Madigan D. Empirical performance of the self-controlled cohort method: lessons for developing a risk identification and analysis system. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0101-3

20.

DuMouchel W, Ryan PB, Schuemie MJ, Madigan D. Evaluation of disproportionality safety signaling applied to health care databases. Drug Saf (in this supplement issue). doi:10.1007/s40264-013-0106-y

21.

Hernandez-Diaz S, Varas-Lorenzo C, Garcia Rodriguez LA. Non-steroidal antiinflammatory drugs and the risk of acute myocardial infarction. Basic Clin Pharmacol Toxicol. 2006;98(3):266–74.PubMedCrossRef

22.

Loke YK, Kwok CS, Singh S. Comparative cardiovascular effects of thiazolidinediones: systematic review and meta-analysis of observational studies. BMJ. 2011;342:d1309.PubMedCrossRef

23.

Green J, Czanner G, Reeves G, Watson J, Wise L, Beral V. Oral bisphosphonates and risk of cancer of oesophagus, stomach, and colorectum: case-control analysis within a UK primary care cohort. BMJ. 2010;341:c4444.PubMedCrossRef

24.

Cardwell CR, Abnet CC, Cantwell MM, Murray LJ. Exposure to oral bisphosphonates and risk of esophageal cancer. J Am Med Assoc. 2010;304(6):657–63.CrossRef

25.

The European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP). Guide on Methodological Standards in Pharmacoepidemiology (Revision 1). EMA/95098/2010 (cited 2013 January 23). Available from: http://www.encepp.eu/standards_and_guidances/documents/ENCePPGuideofMethStandardsinPE.pdf.

26.

Gagne JJ, Nelson JC, Fireman B, Seeger JD, Toh D, Gerhard T, et al. Taxonomy for monitoring methods within a medical product safety surveillance system: year two report of the Mini-Sentinel Taxonomy Project Workgroup (Workgroup) 2012 (cited 2012 October 29). Available from: http://www.mini-sentinel.org/work_products/Statistical_Methods/Mini-Sentinel_Methods_Taxonomy-Year-2-Report.pdf.

27.

Vessey MP, Doll R. Investigation of relation between use of oral contraceptives and thromboembolic disease. Br Med J. 1968;2(5599):199–205.PubMedCrossRef

28.

Vessey M. Learning how to control biases in studies to identify adverse effects of drugs. J R Soc Med. 2007;100(11):526–7.PubMedCrossRef

29.

Jick H, Vessey MP. Case-control studies in the evaluation of drug-induced illness. Am J Epidemiol. 1978;107(1):1–7.PubMed

30.

Hernán MA, Alonso A, Logan R, Grodstein F, Michels KB, Willett WC, et al. Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease. Epidemiology. 2008;19(6):766–79.PubMedCrossRef

31.

Perrio M, Waller PC, Shakir SA. An analysis of the exclusion criteria used in observational pharmacoepidemiological studies. Pharmacoepidemiol Drug saf. 2007;16(3):329–36.PubMedCrossRef

Titel: Variation in Choice of Study Design: Findings from the Epidemiology Design Decision Inventory and Evaluation (EDDIE) Survey
verfasst von: Paul E. Stang
Patrick B. Ryan
J. Marc Overhage
Martijn J. Schuemie
Abraham G. Hartzema
Emily Welebob
Publikationsdatum: 01.10.2013
Verlag: Springer International Publishing
Erschienen in: Drug Safety / Ausgabe Sonderheft 1/2013
Print ISSN: 0114-5916
Elektronische ISSN: 1179-1942
DOI: https://doi.org/10.1007/s40264-013-0103-1

Springer Medizin

Abstract

Background

Objective

Research Design

Subjects

Measures

Results

Conclusions

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Sonderheft 1/2013

The Impact of Drug and Outcome Prevalence on the Feasibility and Performance of Analytical Methods for a Risk Identification and Analysis System

Defining a Reference Set to Support Methodological Research in Drug Safety

Evaluation of Disproportionality Safety Signaling Applied to Healthcare Databases

Empirical Performance of a New User Cohort Method: Lessons for Developing a Risk Identification and Analysis System

Replication of the OMOP Experiment in Europe: Evaluating Methods for Risk Identification in Electronic Health Record Databases

Studying the Science of Observational Research: Empirical Findings from the Observational Medical Outcomes Partnership