SynthesisJournal of clinical epidemiology2011
Use of instrumental variable in prescription drug research with observational data: a systematic review.
Synthesis in Journal of clinical epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Antidepressants and Psychosis Risk: Disentangling Causal Effects From Prognostic Signals.Acta psychiatrica Scandinavica · 2026Article
- Selective Serotonin Reuptake Inhibitor Treatment in Adolescence and Subsequent Risk of Nonaffective Psychosis: A Quasi-Experimental Study.Acta psychiatrica Scandinavica · 2026Article
- Methylphenidate Treatment and Risk of Psychotic Disorder.JAMA psychiatry · 2026Article
- Antidepressant treatment and risk of subsequent bipolar disorder in adolescents with unipolar depression.BMJ mental health · 2025Article
- Article
- Article
- Does treatment of adolescent depression reduce risk of later psychosis: A quasi-experimental study of selective serotonin reuptake inhibitor treatment in a total population cohort.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
- Causal inference with cross-temporal design.Biometrics · 2025Article
- Identifying opioid agonist treatment prescriber networks from health administrative data: A validation study.PloS one · 2025Article
- Frameworks for estimating causal effects in observational settings: comparing confounder adjustment and instrumental variables.BMC medical research methodology · 2023Review
- Implementation of Ticagrelor Reduced Mortality in Routine Clinical Care: Evidence From a Natural Experiment Including 109 995 Patients With Myocardial Infarction in Sweden.Journal of the American Heart Association · 2023Article
- Instrumental variable-based high-dimensional mediation analysis with unmeasured confounders for survival data in the observational epigenetic study.Frontiers in genetics · 2023Article
- Causal associations between sleep traits and four cardiac diseases: a Mendelian randomization study.ESC heart failure · 2022Article
- Real-World Midazolam Use and Outcomes With Out-of-Hospital Treatment of Status Epilepticus in the United States.Annals of emergency medicine · 2022Article
- Association between exenatide use and incidence of Alzheimer's disease.Alzheimer's & dementia (New York, N. Y.) · 2021Article
- Leveraging methylation to identify the potential causal genes associated with survival in lung adenocarcinoma and lung squamous cell carcinoma.Oncology letters · 2020Article
- Long-term use of hydrocodone vs. oxycodone in primary care.Drug and alcohol dependence · 2019Article
- Effectiveness of extended- versus normal-release nitrofurantoin for cystitis: an instrumental variable analysis.The Journal of antimicrobial chemotherapy · 2019Article
- Adjustment for unmeasured confounding through informative priors for the confounder-outcome relation.BMC medical research methodology · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
objectiveInstrumental variable (IV) analysis may offer a useful approach to the problem of unmeasured confounding in prescription drug research if the IV is: (1) strongly and unbiasedly associated to treatment assignment; and (2) uncorrelated with factors predicting the outcome (key assumptions). STUDY DESIGN AND
methodsWe conducted a systematic review of the use of IV methods in prescription drug research to identify the major types of IVs and the evidence for meeting IV assumptions. We searched MEDLINE, OVID, PsychoInfo, EconLit, and economic databases from 1961 to 2009.
resultsWe identified 26 studies. Most (n=16) were published after 2007. We identified five types of IVs: regional variation (n=8), facility-prescribing patterns (n=5), physician preference (n=8), patient history/financial status (n=3), and calendar time (n=4). Evidence supporting the validity of IV was inconsistent. All studies addressed the first IV assumption; however, there was no standard for demonstrating that the IV sufficiently predicted treatment assignment. For the second assumption, 23 studies provided explicit argument that IV was uncorrelated with the outcome, and 16 supported argument with empirical evidence.
conclusionsUse of IV methods is increasing in prescription drug research. However, we did not find evidence of a dominant IV. Future research should develop standards for reporting the validity and strength of IV according to key assumptions.
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