Longitudinal trajectories of polypharmacy in older people, and their association with the risk of mortality: a joint latent class model analysis of real-world data from the UK and the Netherlands.
Elhussein L., Williams RD., Man WY., Burn E., Delmestri A., Strauss VY., Prieto-Alhambra D.
OBJECTIVE: Polypharmacy is the use of multiple drugs. Many definitions have been established for polypharmacy, often cross-sectionally, despite it naturally changing over time. In this study, we aimed to identify clusters of older people with distinct polypharmacy trajectories over time and associated mortality risks. We then characterised the identified clusters and assessed their generalisability in two external databases. METHODS: Data were extracted from three primary care databases: the UK Clinical Practice Research Datalink (CPRD) GOLD, CPRD Aurum and the Dutch Integrated Primary Care Information (IPCI). People aged ≥65 on 1 January 2015 were included. Polypharmacy, defined as the cumulative number of prescribed ingredients, was calculated at baseline and at the end of each subsequent follow-up year (2015-19). We applied joint latent class modelling, which divides the population into clusters with different trajectories and associated mortality risks. The model was trained in GOLD and validated in Aurum and IPCI. RESULTS: Four clusters were identified and characterised based on polypharmacy baseline and rate of progression: low-steady, intermediate-slow/increasing, intermediate-fast/increasing and high-decreasing. The high-decreasing cluster had the highest average baseline polypharmacy (intercept = 23.4) and prevalence of non-cancer chronic comorbidities, whilst the intermediate-fast/increasing had the steepest polypharmacy rate of progression per year (slope = 6.4), highest baseline and cumulative incidence of cancer, and worst survival outcome. Good validation was found in Aurum and IPCI. CONCLUSION: High baseline levels and increasing levels of polypharmacy were associated with an increased mortality risk in older people. The clusters identified in this study were externally validated in two European databases, confirming their robustness and generalisability.