BACKGROUND AND OBJECTIVES: Accurate assessment of medication impact requires modeling cumulative effects of exposure duration and dose; however, postmarketing studies usually represent medication exposure by baseline or current use only. We propose new methods for modeling various aspects of medication use history and employment of them to assess the adverse effects of selected benzodiazepines. STUDY DESIGN AND SETTING: Time-dependent measures of cumulative dose or duration of use, with weighting of past exposures by recency, were proposed. These measures were then included in alternative versions of the multivariable Cox model to analyze the risk of fall related injuries among the elderly new users of three benzodiazepines (nitrazepam, temazepam, and flurazepam) in Quebec. Akaike's information criterion (AIC) was used to select the most predictive model for a given benzodiazepine. RESULTS: The best-fitting model included a combination of cumulative duration and current dose for temazepam, and cumulative dose for flurazepam and nitrazepam, with different weighting functions. The window of clinically relevant exposure was shorter for flurazepam than for the two other products. CONCLUSION: Careful modeling of the medication exposure history may enhance our understanding of the mechanisms underlying their adverse effects.
BACKGROUND AND OBJECTIVES: Accurate assessment of medication impact requires modeling cumulative effects of exposure duration and dose; however, postmarketing studies usually represent medication exposure by baseline or current use only. We propose new methods for modeling various aspects of medication use history and employment of them to assess the adverse effects of selected benzodiazepines. STUDY DESIGN AND SETTING: Time-dependent measures of cumulative dose or duration of use, with weighting of past exposures by recency, were proposed. These measures were then included in alternative versions of the multivariable Cox model to analyze the risk of fall related injuries among the elderly new users of three benzodiazepines (nitrazepam, temazepam, and flurazepam) in Quebec. Akaike's information criterion (AIC) was used to select the most predictive model for a given benzodiazepine. RESULTS: The best-fitting model included a combination of cumulative duration and current dose for temazepam, and cumulative dose for flurazepam and nitrazepam, with different weighting functions. The window of clinically relevant exposure was shorter for flurazepam than for the two other products. CONCLUSION: Careful modeling of the medication exposure history may enhance our understanding of the mechanisms underlying their adverse effects.
Authors: Pedro David Wendel-Garcia; Rolf Erlebach; Rea Andermatt; Sascha David; Daniel Andrea Hofmaenner; Giovanni Camen; Reto Andreas Schuepbach; Christoph Jüngst; Beat Müllhaupt; Jan Bartussek; Philipp Karl Buehler Journal: Crit Care Date: 2022-05-23 Impact factor: 19.334
Authors: Rollin M Wright; Yazan F Roumani; Robert Boudreau; Anne B Newman; Christine M Ruby; Stephanie A Studenski; Ronald I Shorr; Douglas C Bauer; Eleanor M Simonsick; Sarah N Hilmer; Joseph T Hanlon Journal: J Am Geriatr Soc Date: 2009-02 Impact factor: 5.562
Authors: William G Dixon; Michal Abrahamowicz; Marie-Eve Beauchamp; David W Ray; Sasha Bernatsky; Samy Suissa; Marie-Pierre Sylvestre Journal: Ann Rheum Dis Date: 2012-01-12 Impact factor: 19.103
Authors: Cristiano S Moura; Michal Abrahamowicz; Marie-Eve Beauchamp; Diane Lacaille; Yishu Wang; Gilles Boire; Paul R Fortin; Louis Bessette; Claire Bombardier; Jessica Widdifield; John G Hanly; Debbie Feldman; Walter Maksymowych; Christine Peschken; Cheryl Barnabe; Steve Edworthy; Sasha Bernatsky Journal: Arthritis Res Ther Date: 2015-08-03 Impact factor: 5.156