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

被引:206
作者
Schneeweiss, Sebastian [1 ,2 ]
机构
[1] Brigham & Womens Hosp, Div Pharmacoepidemiol & Pharmacoecon, Dept Med, Boston, MA 02120 USA
[2] Harvard Univ, Sch Med, Boston, MA 02120 USA
关键词
healthcare databases; cohort study; incident user design; propensity scores; pharmacoepidemiology; Sentinel System; ACUTE MYOCARDIAL-INFARCTION; UNMEASURED CONFOUNDERS; CLAIMS DATA; RISK; ADJUSTMENT; PHARMACOEPIDEMIOLOGY; THERAPEUTICS; INFORMATION; MODELS; TRIALS;
D O I
10.1002/pds.1926
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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. Copyright (C) 2010 John Wiley & Sons, Ltd.
引用
收藏
页码:858 / 868
页数:11
相关论文
共 39 条
[1]  
[Anonymous], 1997, Clinical trials: a methodologic perspective
[2]  
Austin PC, 2008, STAT MED, V27, P2037, DOI 10.1002/sim.3150
[3]   Managing Drug-Risk Information - What to Do with All Those New Numbers [J].
Avorn, Jerry ;
Schneeweiss, Sebastian .
NEW ENGLAND JOURNAL OF MEDICINE, 2009, 361 (07) :647-649
[4]   Variable selection for propensity score models [J].
Brookhart, M. Alan ;
Schneeweiss, Sebastian ;
Rothman, Kenneth J. ;
Glynn, Robert J. ;
Avorn, Jerry ;
Sturmer, Til .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2006, 163 (12) :1149-1156
[5]   Evaluating short-term drug effects using a physician-specific prescribing preference as an instrumental variable [J].
Brookhart, MA ;
Wang, PS ;
Solomon, DH ;
Schneeweiss, S .
EPIDEMIOLOGY, 2006, 17 (03) :268-275
[6]   Observational Studies Analyzed Like Randomized Experiments An Application to Postmenopausal Hormone Therapy and Coronary Heart Disease [J].
Hernan, Miguel A. ;
Alonso, Alvaro ;
Logan, Roger ;
Grodstein, Francine ;
Michels, Karin B. ;
Willett, Walter C. ;
Manson, JoAnn E. ;
Robins, James M. .
EPIDEMIOLOGY, 2008, 19 (06) :766-779
[7]   Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: Estimating positive predictive value on the basis of review of hospital records [J].
Kiyota, Y ;
Schneeweiss, S ;
Glynn, RJ ;
Cannuscio, CC ;
Avorn, J ;
Solomon, DH .
AMERICAN HEART JOURNAL, 2004, 148 (01) :99-104
[8]   Results of multivariable logistic regression, propensity matching, propensity adjustment, and propensity-based weighting under conditions of nonuniform effect [J].
Kurth, T ;
Walker, AM ;
Glynn, RJ ;
Chan, KA ;
Gaziano, JM ;
Berger, K ;
Robins, JM .
AMERICAN JOURNAL OF EPIDEMIOLOGY, 2006, 163 (03) :262-270
[9]   The challenge of subgroup analyses - Reporting without distorting [J].
Lagakos, SW .
NEW ENGLAND JOURNAL OF MEDICINE, 2006, 354 (16) :1667-1669
[10]   Causal effects in clinical and epidemiological studies via potential outcomes: Concepts and analytical approaches [J].
Little, RJ ;
Rubin, DB .
ANNUAL REVIEW OF PUBLIC HEALTH, 2000, 21 :121-145