Benzodiazepine Use and Risk of Developing Alzheimer's Disease: A Case-Control Study Based on Swiss Claims Data

A possible association between benzodiazepine use and Alzheimer's disease (AD) has been hypothesized in previous studies.; Using claims data from the Helsana Group, a large Swiss health insurance provider, we examined the association between previous benzodiazepine use and the risk of AD.; We conducted a matched case-control study and identified 1438 incident AD cases between 2013 and 2014 based on recorded first-time use of drugs used to treat AD [i.e., acetylcholinesterase inhibitors (donepezil, rivastigmine, and galantamine) and the N-methyl-D-aspartate receptor antagonist memantine] and matched one control to each case on age, sex, index date, and residence (canton). Because the initiation of benzodiazepine use shortly before the AD diagnosis date may occur as a result of symptomatic treatment of prodromal symptoms of early major neurocognitive disorder, we introduced an induction period of 2 years before the AD diagnosis date. Additionally, we categorized medication use by duration of use prior to the index date using prescriptions. We applied conditional logistic regression analyses to calculate odds ratios with 95% confidence intervals and adjusted for use of antidepressants.; The crude odds ratio (95% confidence interval) of developing AD for patients starting benzodiazepine treatment was 1.71 (1.17-2.99) in the year before diagnosis and 1.19 (0.82-1.72) in the third year before diagnosis. After accounting for benzodiazepine use initiated during the prodromal phase, benzodiazepine use was not associated with an increased risk of developing AD; long-term benzodiazepine use (≥30 prescriptions) yielded an adjusted odds ratio of 0.78 (0.53-1.14).; After taking into consideration a possible protopathic bias in the 2 years preceding the AD diagnosis date, benzodiazepine use was not associated with an increased risk of developing AD

Multiple-group analysis of similarity in latent profile solutions

Despite the increased popularity of person-centered analyses, no comprehensive approach exists to guide the systematic investigation of the similarity (or generalizability) of latent profiles, their predictors, and their outcomes across subgroups of participants or time points. We propose a six-step process to assess configural (number of profiles), structural (within-profile means), dispersion (within-profile variability), distributional (size of the profiles), predictive (relations between predictors and profile membership), and explanatory (relations between profile membership and outcomes) similarity. We then apply this approach to data on organizational commitment mindsets collected in North America (n = 492) and France (n = 476). This approach provides a rigorous method to systematically and quantitatively assess the extent to which a latent profile solution generalizes across diverse samples, such as in the cross-national comparison in our illustrative example, or the extent to which interventions or naturalistic changes may impact the nature of a latent profile solution. This approach also helps to identify the nature of any differences that might be present, thus providing richer interpretations of observed differences and ideas for future research