Revisiting the washout period in the incident user study design: Why 6-12 months may not be sufficient

Journal of Comparative Effectiveness Research

Volumn 4, Issue 1, 2015, Pages 27-35

  Roberts, Andrew W ^a,b   Dusetzina, Stacie B ^a,b,c   Farley, Joel F ^a  

^a University of North Carolina   (United States)

^b UNIVERSITY OF NORTH CAROLINA   (United States)

^c IL   (United States)

Author keywords

comparative effectiveness research; incident user design; methods; pharmacoepidemiology; research design; secondary databases; selection bias

Indexed keywords

ALPHA GLUCOSIDASE INHIBITOR; AMFEBUTAMONE; BILE ACID SEQUESTRANT; DIPEPTIDYL PEPTIDASE IV INHIBITOR; EZETIMIBE; FIBRIC ACID DERIVATIVE; GLITAZONE DERIVATIVE; HYDROXYMETHYLGLUTARYL COENZYME A REDUCTASE INHIBITOR; INCRETIN; INSULIN; MAPROTILINE; MEGLITINIDE; METFORMIN; MONOAMINE OXIDASE INHIBITOR; NICOTINIC ACID; OMEGA 3 ACID ETHYL ESTER; SEROTONIN ANTAGONIST; SEROTONIN NORADRENALIN REUPTAKE INHIBITOR; SEROTONIN UPTAKE INHIBITOR; SULFONYLUREA DERIVATIVE; TRICYCLIC ANTIDEPRESSANT AGENT; ANTIDEPRESSANT AGENT; ANTIDIABETIC AGENT; ANTILIPEMIC AGENT;

ADULT; ARTICLE; BILLING AND CLAIMS; COHORT ANALYSIS; COMPARATIVE EFFECTIVENESS; CONTROLLED STUDY; CRITERION VARIABLE; DEPRESSION; DIABETES MELLITUS; DRUG MARKETING; DRUG USE; HEALTH INSURANCE; HUMAN; HYPERLIPIDEMIA; MAJOR CLINICAL STUDY; OBSERVATIONAL STUDY; RETROSPECTIVE STUDY; SAMPLE SIZE; TREATMENT DURATION; TREATMENT WITHDRAWAL; ADOLESCENT; FACTUAL DATABASE; FEMALE; INSURANCE; MALE; METHODOLOGY; MIDDLE AGED; PHARMACOEPIDEMIOLOGY; PROCEDURES; TIME;

ADOLESCENT; ADULT; ANTIDEPRESSIVE AGENTS; COMPARATIVE EFFECTIVENESS RESEARCH; DATABASES, FACTUAL; FEMALE; HUMANS; HYPOGLYCEMIC AGENTS; HYPOLIPIDEMIC AGENTS; INSURANCE CLAIM REVIEW; MALE; MIDDLE AGED; PHARMACOEPIDEMIOLOGY; RESEARCH DESIGN; TIME FACTORS;

EID: 84920829972     PISSN: 20426305     EISSN: 20426313     Source Type: Journal    
DOI: 10.2217/cer.14.53     Document Type: Article

References (26)

1. Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J. Clin. Epidemiol. 58(4), 323-337 (2005).
2. Patient-Centered Outcomes Research Institute. National Priorities for Research and Research Agenda. (2012). www.pcori.org
3. Cox E, Martin BC, Van Staa T, Garbe E, Siebert U, Johnson ML. Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retrospective Database Analysis Task Force Report-Part II. Value Health 12(8), 1053-1061 (2009).
4. Brookhart MA, Sturmer T, Glynn RJ, Rassen J, Schneeweiss S. Confounding control in healthcare database research: challenges and potential approaches. Med. Care 48(6) (Suppl.), S114-S120 (2010).
5. Ray WA. Evaluating medication effects outside of clinical trials: new-user designs. Am. J. Epidemiol. 158(9), 915-920 (2003).
6. Danaei G, Tavakkoli M, Hernan MA. Bias in observational studies of prevalent users: lessons for comparative effectiveness research from a meta-Analysis of statins. Am. J. Epidemiol. 175(4), 250-262 (2012).
7. Maciejewski ML, Bryson CL, Wang V, Perkins M, Liu CF. Potential bias in medication adherence studies of prevalent users. Health Serv. Res. 48(4), 1468-1486 (2013).
8. Schneeweiss S, Patrick AR, Sturmer T et al. Increasing levels of restriction in pharmacoepidemiologic database studies of elderly and comparison with randomized trial results. Med. Care 45(10) (Suppl. 2), S131-S142 (2007).
9. Perrio M, Waller PC, Shakir SA. An analysis of the exclusion criteria used in observational pharmacoepidemiological studies. Pharmacoepidemiol. Drug Saf. 16(3), 329-336 (2007).
10. Brunelli SM, Gagne JJ, Huybrechts KF et al. Estimation using all available covariate information versus a fixed look-back window for dichotomous covariates. Pharmacoepidemiol. Drug Saf. 22(5), 542-550 (2013).
11. Johnson ES, Bartman BA, Briesacher BA et al. The incident user design in comparative effectiveness research. Pharmacoepidemiol. Drug Saf. 22(1), 1-6 (2013).
12. Ray WA, Stein CM, Daugherty JR, Hall K, Arbogast PG, Griffin MR. COX-2 selective non-steroidal antiinflammatory drugs and risk of serious coronary heart disease. Lancet 360 (9339), 1071-1073 (2002).
13. Abbas S, Ihle P, Koster I, Schubert I. Estimation of disease incidence in claims data dependent on the length of followup: a methodological approach. Health Serv. Res. 47(2), 746-755 (2012).
14. Gardarsdottir H, Heerdink ER, Egberts AC. Potential bias in pharmacoepidemiological studies due to the length of the drug free period: a study on antidepressant drug use in adults in the Netherlands. Pharmacoepidemiol. Drug Saf. 15(5), 338-343 (2006).
15. Kessler RC, Berglund P, Demler O et al. The epidemiology of major depressive disorder. results from the National Comorbidity Survey Replication (NCS-R). JAMA 289(23), 3095-3105 (2003).
16. Nathan DM, Buse JB, Davidson MB et al. Medical management of hyperglycemia in type 2 diabetes. a consensus algorithm for the initiation and adjustment of therapy: a consensus statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 32(1), 193-203 (2009).
17. National Cholesterol Education Program Expert Panel on Detection E, Treatment of High Blood Cholesterol In Adults. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 106(25), 3143-3421 (2002).
18. Satyanarayana S, Enns MW, Cox BJ, Sareen J. Prevalence and correlates of chronic depression in the Canadian community health survey: mental health and well-being. Can. J. Psychiatry 54(6), 389-398 (2009).
19. Schneeweiss S, Patrick AR, Solomon DH et al. Variation in the risk of suicide attempts and completed suicides by antidepressant agent in adults: a propensity score-Adjusted analysis of 9 years' data. Arch. Gen. Psychiatry 67(5), 497-506 (2010).
20. Truven Health Analytics. Better Understand Health Economics and Treatment Outcomes: Data Databases and Online Tools. (2013). http://truvenhealth.com
21. Last AR, Ference JD, Falleroni J. Pharmacologic treatment of hyperlipidemia. Am. Fam. Physician 84(5), 551-558 (2011).
22. Garber AJ, Abrahamson MJ, Barzilay JI et al. AACE comprehensive diabetes management algorithm 2013. Endocr. Pract. 19(2), 327-336 (2013).
23. American Psychiatric Association. Practice Guidelines for the Treatment of Patients With Major Depressive Disorder (3rd Edition). (2010). http://psychiatryonline.org
24. Berger VW. Pros and cons of permutation tests in clinical trials. Stat. Med. 19(10), 1319-1328 (2000).
25. Grimes DA, Schulz KF. Bias and causal associations in observational research. Lancet 359(9302), 248-252 (2002).
26. Sommers BD. Loss of health insurance among non-elderly adults in Medicaid. J. Gen. Intern. Med. 24(1), 1-7 (2009).