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Assessing the cumulative effects of exposure to selected benzodiazepines on the risk of fall-related injuries in the elderly

Published online by Cambridge University Press:  08 November 2011

Marie-Pierre Sylvestre
Affiliation:
Research Centre of the CHUM, Montréal and Department of Social and Preventive Medicine, Université de Montréal, Montreal, Quebec, Canada
Michal Abrahamowicz*
Affiliation:
Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
Radan Čapek
Affiliation:
Department of Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
Robyn Tamblyn
Affiliation:
Departments of Medicine and of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
*
Correspondence should be addressed to: Michal Abrahamowicz, Department of Epidemiology and Biostatistics, McGill University, 687 Pine Avenue West, V-Pavilion, Montreal, QC H3A 1A1, Canada. Phone: +1 514-934-1934 ext. 44712; Fax: +1 514-934-8293. Email: michal.abrahamowicz@mcgill.ca.

Abstract

Background: The use of benzodiazepines is associated with increased risk of fall-related injuries in the elderly. However, it is unclear if the risks vary across the products and how they depend on the pattern of use and dosage. Specifically, the possibility of cumulative effects of past benzodiazepine use has not been thoroughly investigated.

Methods: We used the administrative database for a cohort of 23,765 new users of benzodiazepines, aged 65 years and older, in Quebec, Canada, between 1990 and 1994. The associations between the use of seven benzodiazepines and the risk of fall-related injuries were assessed using several statistical models, including a novel weighted cumulative exposure model. That model assigns to each dose taken in the past a weight that represents the importance of that dose in explaining the current risk of fall.

Results: For flurazepam, the best-fitting model indicated a cumulative effect of doses taken in the last two weeks. Uninterrupted use of flurazepam in the past months was associated with a highly significant increase in the risk of fall-related injuries (HR = 2.83, 95% CI: 1.45–4.34). The cumulative effect of a 30-day exposure to alprazolam was 1.27 (1.13–1.42). For temazepam, the results suggested a potential withdrawal effect.

Conclusions: Mechanisms affecting the risk of falls differ across benzodiazepines, and may include cumulative effects of use in the previous few weeks. Thus, benzodiazepine-specific analyses that account for individual patterns of use should be preferred over simpler analyses that group different benzodiazepines together and limit exposure to current use or current dose.

Type
Research Article
Copyright
Copyright © International Psychogeriatric Association 2011

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References

Abrahamowicz, M. and Tamblyn, R. (2005). Drug utilization patterns. In Colton, Armitage, editors, Encyclopedia of Biostatistics (pp. 12351247). Chichester: John Wiley & Sons Ltd.Google Scholar
Abrahamowicz, M., MacKenzie, T. and Esdaile, J. (1996). Time-dependent hazard ratio: modeling and hypothesis testing with application in lupus nephritis. Journal of the American Statistical Society, 91, 14321439.Google Scholar
Abrahamowicz, M., Bartlett, G., Tamblyn, R. and du Berger, R. (2006). Modeling cumulative dose and exposure duration provided insights regarding the associations between benzodiazepines and injuries. Journal of Clinical Epidemiology, 59, 393403.Google Scholar
Bartlett, G., Abrahamowicz, M., Tamblyn, R., Grad, R., Čapek, R., and du Berger, R. (2004). Longitudinal patterns of new benzodiazepine use in the elderly. Pharmacoepidemiology and Drug Safety 13, 669682.Google Scholar
Catterson, M. L., Preskorn, S. H. and Martin, R. L. (1997). Pharmacodynamic and pharmacokinetic considerations in geriatric psychopharmacology. Psychiatric Clinics of North America, 20, 205228.Google Scholar
Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society Series B (Methodological), 34, 187220.Google Scholar
Cumming, R. G. et al. (1991). Medications and multiple falls in elderly people: the St Louis OASIS study. Age and Ageing, 20,455461.Google Scholar
Csajka, C. and Verotta, D. (2006). Pharmacokinetic-pharmacodynamic modelling: history and perspectives. Journal of Pharmacokinetics and Pharmacodynamics, 33, 227279.CrossRefGoogle Scholar
Efron, B. and Tibshirani, R. (1993). An Introduction to the Bootstrap. Chapman Hall.Google Scholar
Hauptmann, M., Wellmann, J., Lubin, J., Rosenberg, P. S. and Kreienbrock, L. (2000). Analysis of exposure-time-response relationships using a spline weight function. Biometrics, 56, 11051108.Google Scholar
Herings, R., Stricker, B., de Boer, A., Bakker, A. and Sturmans, F. (1995). Benzodiazepines and the risk of falling leading to femur fractures: dosage more important than elimination half-life. Archives of Internal Medicine, 155, 18011807.Google Scholar
Isacson, D. (1997). Long-term benzodiazepine use: factors of importance and the development of individual use patterns over time-a 13-year follow-up in a Swedish community. Social Science & Medicine, 44, 18711880.Google Scholar
Neutel, C., Hirdes, J., Maxwell, C. and Patten, S. B. (1996). New evidence on benzodiazepine use and falls: the time factor. Age and Ageing, 25, 273278.Google Scholar
Passaro, A., Volpato, S., Romagnoni, F., Manzoli, N., Zuliani, G. and Fellin, R. (2000). Benzodiazepines with different half-life and falling in a hospitalized population: The GIFA study. Gruppo Italiano di Farmacovigilanza nell'Anziano. Journal of Clinical Epidemiology, 53, 12221229.CrossRefGoogle Scholar
Pierfitte, C. et al. (2001). Benzodiazepines and hip fractures in elderly people: case-control study. BMJ, 322, 704708.Google Scholar
Ray, W., Grin, M. and Downey, W. (1989). Benzodiazepines of long and short elimination half-life and the risk of hip fracture. JAMA, 262, 33033307.Google Scholar
Ray, W., Thapa, P. and Gideon, P. (2002). Misclassification of current benzodiazepine exposure by use of a single baseline measurement and its effects upon studies of injuries. Pharmacoepidemiology and Drug Safety, 11, 663669.Google Scholar
Schneeweiss, S. and Avorn, J. (2005). A review of uses of health care utilization databases for epidemiologic research on therapeutics. Journal of Clinical Epidemiology, 58, 323337.CrossRefGoogle ScholarPubMed
Sgadari, A., Lapane, K., Mor, V., Landi, F., Bernabei, R. and Gambassi, G. (2000). Oxidative and nonoxidative benzodiazepines and the risk of femur fracture. The Systematic Assessment of Geriatric Drug Use Via Epidemiology Study Group. Journal of Clinical Psychopharmacology, 20, 234239.CrossRefGoogle ScholarPubMed
Sylvestre, M. P. and Abrahamowicz, M. (2009). Flexible modeling of the cumulative effects of time-dependent exposures on the hazard. Statistics in Medicine, 28, 34373453.CrossRefGoogle ScholarPubMed
Sylvestre, M. P., Huszti, E. and Hanley, J. A. (2006). Do Oscar winners live longer than less successful peers? A reanalysis of the evidence. Annals of Internal Medicine, 145, 361363.Google Scholar
Tamblyn, R., Lavoie, G., Petrella, L. and Monette, J. (1995). The use of prescription claims databases in pharmacoepidemiological research: the accuracy and comprehensiveness of the prescription claims database in Quebec. Journal of Clinical Epidemiology, 48, 9991009.Google Scholar
Tamblyn, R., Abrahamowicz, M., du Berger, R., McLeod, P. and Bartlett, G. (2005). A 5-year prospective assessment of the risk associated with individual benzodiazepines and doses in new elderly users. Journal of the American Geriatrics Society, 53, 233241.Google Scholar
Tu, K., Mamdani, M., Hux, J., and Tu, J.B. (2001). Progressive trends in the prevalence of benzodiazepine prescribing in older people in Ontario, Canada. Journal of the American Geriatrics Society, 49, 13411345.Google Scholar
Vacek, P. (1997). Assessing the effect of intensity when exposure varies over time. Statistics in Medicine, 16, 505513.Google Scholar
van Hulten, R., Leufkens, H. and Bakker, A. (1998). Usage patterns of benzodiazepines in a Dutch community: a 10-year follow-up. Pharmacy World & Science, 78–82.Google Scholar
Volinsky, C. and Raftery, A. (2000). Bayesian information criterion for censored survival models. Biometrics, 56, 256262.CrossRefGoogle ScholarPubMed
Walker, A. M. (1996). Confounding by indication. Epidemiology, 7, 335336.Google ScholarPubMed
West, S., Strom, B. and Poole, C. (2002). Validity of pharmacoepidemiology drug and diagnosis data. In Strom, B.L. (ed.), Pharmacoepidemiology (3rd edn). Chichester: John Wiley & Sons.Google Scholar
WHO Collaborating Centre for Drug Statistics Methodology (2000). Anatomical Therapeutic Chemical Classification Index with Defined Daily Doses. Oslo: World Health Organization.Google Scholar