Literature DB >> 17909369

Evaluating the validity of an instrumental variable study of neuroleptics: can between-physician differences in prescribing patterns be used to estimate treatment effects?

M Alan Brookhart1, Jeremy A Rassen, Philip S Wang, Colin Dormuth, Helen Mogun, Sebastian Schneeweiss.   

Abstract

BACKGROUND: Postmarketing studies of prescription drugs are challenging because prognostic variables that determine treatment choices are often unmeasured. In this setting, instrumental variable (IV) methods that exploit differences in prescribing patterns between physicians may be used to estimate treatment effects; however, IV methods require strong assumptions to yield consistent estimates. We sought to explore the validity of physician-level IV in a comparative study of short-term mortality risk among elderly users of conventional versus atypical antipsychotic medications (APM).
METHODS: We studied a cohort of patients initiating APMs in Pennsylvania who were eligible for Medicare and a state-funded pharmaceutical benefit plan. The IV was defined as the type of the APM prescription written by each physician before the index prescription. To evaluate whether the IV was related to other therapeutic decisions that could affect mortality, we explored the association between the instrument and 2 types of potentially hazardous coprescriptions: a tricyclic antidepressant (TCA) not recommended for use in the elderly or a long-acting benzodiazepine. To insure that the IV analysis was not biased by case-mix differences between physicians, we examined the associations between the observed patient characteristics and the IV.
RESULTS: The cohort consisted of 15,389 new users of APMs. Our multivariable model indicated that physicians who had most recently prescribed a conventional APM were not significantly more or less likely to coprescribe a potentially hazardous TCA [odds ratio (OR), 0.78; 95% confidence interval (CI), 0.58-1.02] but were less likely to prescribe a long-acting benzodiazepine (OR, 0.57; 95% CI, 0.45-0.72) with their current APM prescription. The association between long-acting benzodiazepine prescribing and APM preference was no longer significant when the analysis was restricted to primary care physicians (OR, 0.84; 95% CI, 0.62-1.15). Multivariable regression indicated that important medical comorbidities (eg, cancer, hypertension, stroke) were unrelated to the IV.
CONCLUSIONS: The previous APM prescription written by the physician was unassociated with major medical comorbidities in the current patient, suggesting that the IV estimates were not biased by case-mix differences between physicians. However, we did find that the IV was associated with the use of long-acting benzodiazepines. This association disappeared when the study was restricted to the patients treated by primary care physicians. Our study illustrates how internal validation approaches may be used to improve the design of quasi-experimental studies.

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Year:  2007        PMID: 17909369     DOI: 10.1097/MLR.0b013e318070c057

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  15 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.  Potentially Inappropriate Medication and Health Care Outcomes: An Instrumental Variable Approach.

Authors:  Chi-Chen Chen; Shou-Hsia Cheng
Journal:  Health Serv Res       Date:  2015-11-25       Impact factor: 3.402

3.  Association of Physician Variation in Use of Manual Aspiration Thrombectomy With Outcomes Following Primary Percutaneous Coronary Intervention for ST-Elevation Myocardial Infarction: The National Cardiovascular Data Registry CathPCI Registry.

Authors:  Eric A Secemsky; Enrico G Ferro; Sunil V Rao; Ajay Kirtane; Hector Tamez; Pearl Zakroysky; Daniel Wojdyla; Steven M Bradley; David J Cohen; Robert W Yeh
Journal:  JAMA Cardiol       Date:  2019-02-01       Impact factor: 14.676

4.  Phosphate binder use and mortality among hemodialysis patients in the Dialysis Outcomes and Practice Patterns Study (DOPPS): evaluation of possible confounding by nutritional status.

Authors:  Antonio Alberto Lopes; Lin Tong; Jyothi Thumma; Yun Li; Douglas S Fuller; Hal Morgenstern; Jürgen Bommer; Peter G Kerr; Francesca Tentori; Takashi Akiba; Brenda W Gillespie; Bruce M Robinson; Friedrich K Port; Ronald L Pisoni
Journal:  Am J Kidney Dis       Date:  2012-03-03       Impact factor: 8.860

5.  Longer dialysis session length is associated with better intermediate outcomes and survival among patients on in-center three times per week hemodialysis: results from the Dialysis Outcomes and Practice Patterns Study (DOPPS).

Authors:  Francesca Tentori; Jinyao Zhang; Yun Li; Angelo Karaboyas; Peter Kerr; Rajiv Saran; Juergen Bommer; Friedrich Port; Takashi Akiba; Ronald Pisoni; Bruce Robinson
Journal:  Nephrol Dial Transplant       Date:  2012-03-19       Impact factor: 5.992

6.  Drug Enforcement Agency 2014 Hydrocodone Rescheduling Rule and Opioid Dispensing after Surgery.

Authors:  Mark D Neuman; Sean Hennessy; Dylan S Small; Craig Newcomb; Lakisha Gaskins; Colleen M Brensinger; Duminda N Wijeysundera; Brian T Bateman; Hannah Wunsch
Journal:  Anesthesiology       Date:  2020-05       Impact factor: 7.892

Review 7.  Use of instrumental variable in prescription drug research with observational data: a systematic review.

Authors:  Yong Chen; Becky A Briesacher
Journal:  J Clin Epidemiol       Date:  2010-12-16       Impact factor: 6.437

8.  Blood pressure levels and mortality risk among hemodialysis patients in the Dialysis Outcomes and Practice Patterns Study.

Authors:  Bruce M Robinson; Lin Tong; Jinyao Zhang; Robert A Wolfe; David A Goodkin; Roger N Greenwood; Peter G Kerr; Hal Morgenstern; Yun Li; Ronald L Pisoni; Rajiv Saran; Francesca Tentori; Tadao Akizawa; Shunichi Fukuhara; Friedrich K Port
Journal:  Kidney Int       Date:  2012-06-20       Impact factor: 10.612

9.  Instrumental variables I: instrumental variables exploit natural variation in nonexperimental data to estimate causal relationships.

Authors:  Jeremy A Rassen; M Alan Brookhart; Robert J Glynn; Murray A Mittleman; Sebastian Schneeweiss
Journal:  J Clin Epidemiol       Date:  2009-04-08       Impact factor: 6.437

10.  Instrumental variables II: instrumental variable application-in 25 variations, the physician prescribing preference generally was strong and reduced covariate imbalance.

Authors:  Jeremy A Rassen; M Alan Brookhart; Robert J Glynn; Murray A Mittleman; Sebastian Schneeweiss
Journal:  J Clin Epidemiol       Date:  2009-04-05       Impact factor: 6.437

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