Highlights
- •Quantifying the effect of benzodiazepines on mortality is not straightforward.
- •Immortal time bias threatens the validity of benzodiazepine effect estimates.
- •A process of cloning, weighting, and censoring is used to avoid immortal time bias.
- •The observed benzodiazepine-related 30-day mortality was largely due to confounding.
Abstract
Background and Objectives
Methods
Results
Conclusion
Graphical abstract

Keywords
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Journal of Clinical EpidemiologyReferences
- Heart disease and stroke statistics-2017 update: a report from the American heart association.Circulation. 2017; 135: e146-e603
- Global burden of stroke.Semin Neurol. 2018; 38: 208-211
- Patterns of anticonvulsant use and adverse drug events in older adults.Pharmacoepidemiol Drug Saf. 2021; 30: 28-36
- American geriatrics society 2019 updated AGS beers criteria(R) for potentially inappropriate medication use in older adults.J Am Geriatr Soc. 2019; 67: 674-694
- Reduction of inappropriate benzodiazepine prescriptions among older adults through direct patient education: the EMPOWER cluster randomized trial.JAMA Intern Med. 2014; 174: 890-898
- Cognitive behavior therapy for generalized anxiety disorder among older adults in primary care: a randomized clinical trial.JAMA. 2009; 301: 1460-1467
- Potentially inappropriate medications at admission and discharge in older adults: a comparison of the Beers 2019 and 2015 criteria.Int J Clin Pharmacol Ther. 2020; 58: 299-309
- Benzodiazepine prescribing in older adults in U.S. Ambulatory clinics and emergency departments (2001-10).J Am Geriatr Soc. 2015; 63: 2074-2081
- Association between use of benzodiazepines and risk of fractures: a meta-analysis.Osteoporos Int. 2014; 25: 105-120
- Benzodiazepines and risk of death: results from two large cohort studies in France and UK.Eur Neuropsychopharmacol. 2015; 25: 1566-1577
- Disparate inclusion of older adults in clinical trials: priorities and opportunities for policy and practice change.Am J Public Health. 2010; 100: S105-S112
- The challenges of clinical trials in the exclusion zone: the case of the frail elderly.Australas J Ageing. 2008; 27: 61-66
- Geriatric drug evaluation: where are we now and where should we be in the future?.Arch Intern Med. 2011; 171: 937-940
- Clinical pharmacology in the geriatric patient.Fundam Clin Pharmacol. 2007; 21: 217-230
- How to estimate the effect of treatment duration on survival outcomes using observational data.BMJ. 2018; 360: k182
- With great data comes great responsibility: publishing comparative effectiveness research in epidemiology.Epidemiology. 2011; 22: 290-291
- Authors’ response, Part I: observational studies analyzed like randomized experiments: best of both worlds.Epidemiology. 2008; 19: 782-792
- Using big data to emulate a target trial when a randomized trial is not available.Am J Epidemiol. 2016; 183: 758-764
- Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses.J Clin Epidemiol. 2016; 79: 70-75
- Estimates of overall survival in patients with cancer receiving different treatment regimens: emulating hypothetical target trials in the surveillance, epidemiology, and end results (SEER)-Medicare linked database.JAMA Netw Open. 2020; 3: e200452
- Study designs for extending causal inferences from a randomized trial to a target population.Am J Epidemiol. 2021; 190: 1632-1642
- Methods to estimate the comparative effectiveness of clinical strategies that administer the same intervention at different times.Curr Epidemiol Rep. 2015; 2: 149-161
- Comparing the effectiveness of dynamic treatment strategies using electronic health records: an application of the parametric g-formula to anemia management strategies.Health Serv Res. 2018; 53: 1900-1918
- Calculating the benefits of a research patient data repository.AMIA Annu Symp Proc. 2006; 2006: 1044-1045
- The American Heart Association's Get with the Guidelines (GWTG)-Stroke development and impact on stroke care.Stroke Vasc Neurol. 2017; 2: 94-105
- Reliability and validity of estimating the NIH stroke scale score from medical records.Stroke. 1999; 30: 1534-1537
- Calculated Decisions: NIH stroke scale/score (NIHSS).Emerg Med Pract. 2020; 22: CD6-CD7
- Neurologist-associated reduction in PD-related hospitalizations and health care expenditures.Neurology. 2012; 79: 1774-1780
- Preadmission use of benzodiazepines and stroke outcomes: the Biostroke prospective cohort study.BMJ Open. 2019; 9: e022720
- How do potentially inappropriate medications and polypharmacy affect mortality in frail and non-frail cognitively impaired older adults? A cohort study.BMJ Open. 2019; 9: e026171
- Recognizing the problem of delayed entry in time-to-event studies: better late than never for clinical neuroscientists.Ann Neurol. 2015; 78: 839-844
- Association between benzodiazepine use with or without opioid use and all-cause mortality in the United States, 1999-2015.JAMA Netw Open. 2020; 3: e2028557
- Bias in observational studies of prevalent users: lessons for comparative effectiveness research from a meta-analysis of statins.Am J Epidemiol. 2012; 175: 250-262
- Observational studies analyzed like randomized experiments: an application to postmenopausal hormone therapy and coronary heart disease.Epidemiology. 2008; 19: 766-779
- Social inequality in chronic disease outcomes.Dan Med J. 2014; 61: B4943
- Utility of 90-day mortality vs 30-day mortality as a quality metric for transcatheter and surgical aortic valve replacement outcomes.JAMA Cardiol. 2020; 5: 156-165
- Relationship of national institutes of health stroke scale to 30-day mortality in medicare beneficiaries with acute ischemic stroke.J Am Heart Assoc. 2012; 1: 42-50
- Public reporting of 30-day mortality for patients hospitalized with acute myocardial infarction and heart failure.Circulation. 2008; 118: 1394-1397
- A standardized mean difference effect size for multiple baseline designs across individuals.Res Synth Methods. 2013; 4: 324-341
- Inferences on standardized mean difference: the generalized variable approach.Stat Med. 2007; 26: 945-953
- Uses and limitations of the restricted mean survival time: illustrative examples from cardiovascular outcomes and mortality trials in type 2 diabetes.Ann Intern Med. 2020; 172: 541-552
- Statistical considerations for sequential analysis of the restricted mean survival time for randomized clinical trials.Stat Biopharm Res. 2021; 13: 210-218
- Adjusted survival curves with inverse probability weights.Comput Methods Programs Biomed. 2004; 75: 45-49
- Marginal Structural Models.American Statistical Association, 1998: 1-14 (Available at)https://cdn1.sph.harvard.edu/wp-content/uploads/sites/343/2013/03/msm-web.pdfDate accessed: January 12, 2023
- Estimation of the causal effects of time- varying exposures.in: Fitzmaurice G.D.M. Verbeke G. Longitudinal Data Analysis. Chapman & Hall, Boca Raton, FL2009: 553-599
- Benzodiazepine use during hospitalization: automated identification of potential medication errors and systematic assessment of preventable adverse events.PLoS One. 2016; 11: e0163224
- Guidelines for the rational use of benzodiazepines. When and what to use.Drugs. 1994; 48: 25-40
- The pharmacological treatment of epilepsy in adults.Lancet Neurol. 2011; 10: 446-456
- Evidence-based guideline: management of an unprovoked first seizure in adults: report of the guideline development subcommittee of the American academy of neurology and the American epilepsy society.Neurology. 2015; 85: 1526-1527
Article info
Publication history
Footnotes
Study Funding: This work is was funded by the NIH (Award number NIA 1 R01 AG073410-01).
Conflicts of interest: The authors declare no conflict of interest.
CRediT author statement: Dr Lidia Moura: conceptualization, methodology, formal analysis, data curation, writing–original draft, writing–review & editing, funding acquisition, supervision. Dr Maria A Donahue: writing–original draft, writing–review & editing, visualization, project administration. Zhiyu Yan: software, validation, formal analysis, data curation, visualization. Louisa Smith: validation, formal analysis, writing–review & editing. Dr Hsu: writing–review & editing. Dr Schwamm: writing–review & editing. Dr Newhouse: writing–review & editing. Drs Haneuse: conceptualization, methodology, formal analysis, writing–review & editing. Dr Blacker: conceptualization, methodology, writing–review & editing. Dr Hernandez-Diaz: conceptualization, methodology, formal analysis, writing–review & editing, and supervision.
Sponsor's role: This work was done as part of the fulfillment of Dr Moura's doctoral degree in Population Health Sciences (Epidemiology) at the Harvard T.H. Chan School of Public Health.
Financial disclosures: L.M.V.R.M.: Support from the Centers for Diseases Control and Prevention (U48DP006377), the National Institutes of Health (NIH-NIA 5K08AG053380-02, NIH-NIA 5R01AG062282-02, NIH-NIA 2P01AG032952-11, NIH- NIA 3R01AG062282-03S1), and the Epilepsy Foundation of America and reports no conflict of interest. Z.Y., M.A.D. and L.H.S.: have no conflict of interest to disclose. J.P.N. receives funding from NIH (2P01- AG032952, T32-AG51108) and reports being a director of Aetna until May 2018 and holding equity in Aetna until November 2018. L.H.S.: Scientific consultant regarding trial design and conduct on late window thrombolysis and member of steering committee for Genentech (TIMELESS NCT03785678); user interface design and usability to LifeImage; stroke systems of care to the Massachusetts Dept of Public Health; member of a Data Safety Monitoring Board for Penumbra (MIND NCT03342664); Diffusion Pharma (PHAST-TSC NCT03763929); principal investigator, multicenter trial of stroke prevention for Medtronic (Stroke AF NCT02700945); principal investigator, StrokeNet Network NINDS (New England Regional Coordinating Center U24NS107243). J.H.: Support from the NIH (1R01AG062282-012, P01AG032952). J.P.N.: receives funding from NIH (2P01- AG032952, T32-AG51108) and reports being a director of Aetna until May 2018 and holding equity in Aetna until November 2018. S.H.: Support from the NIH (R01HD098421, R01NS104143, P50CA244433, 1R01DK128150-01, R01DK107972) and Gates Foundation (INV-003612) reports no conflict of interest. D.B.: Support from the NIH (5P30 AG062421-03, 2P01AG036694-11, 5U01AG032984-12, 1U24NS100591-04, 1R01AG058063-04, R01AG063975-03, 5R01AG062282-04, 3R01AG062282-03S1, 5R01AG066793-02, 1U19AG062682-03, 2P01AG032952-11, 2T32MH017119-34 Billing Agreement 010,289.0001, 3P01AG032952-12S3, 1U01AG068221-01, 1U01AG076478-01, 5R01AG048351-05) and 747,021.Blacker.2019 from President and Fellows of Harvard College reports no conflict of interest. S.H.D. receives funding from NIH (5R01HD088393-02) and reports grants to her institution from Takeda, and consulting for Bayer and UCB, all outside the submitted work.