A novel polypharmacy score predicts mortality among the elderly

Researchers from FIMM and the Finnish Institute for Health and Welfare have demonstrated how modern data-driven approaches and longitudinal secondary health data can be used to construct a novel measure of health differences from pharmacy purchases.

The results of the study were published in Scientific Reports on September 25, 2020.

Health differences among the elderly and the role of medical treatments are topical issues in many aging societies. Understanding these differences better would help target resources and interventions more effectively to those at risk.

The research team led by Professor Samuli Ripatti from the University of Helsinki utilized modern statistical learning methods to develop a data driven health measure based on 21 years of pharmacy purchase and mortality data of 12 000 aging individuals.

The researchers showed that the resulting score is strongly associated with mortality in the national FINRISK study cohort. This finding was replicated with over 33 000 individuals from two independent datasets, national Health 2000 cohort and the Estonian Biobank cohort.

In contrast to many classic comorbidity and polypharmacy measures, the approach used poses no presumptions of relevant medication indications and is based purely on an empirical analysis of the longitudinal register data.

“Healthy aging is something we all wish for, but how to define it in research settings? This type of easily derived medication score could be used as a simple screening tool for healthy aging in health research and potentially in clinics. It can indicate individuals in need of a more detailed attention due to elevated mortality risk”, Samuli Ripatti said.

Together with classic comorbidity index, the novel polypharmacy score was able to identify 1.2% of elderly population with over six times higher risk of mortality compared to the individuals with a protective medication profile.

“It is important to note that the score measures complex correlations between medication use and underlying health conditions, and these associations should not be considered as causal relationships between individual medications and mortality”, the first author of the study, Paavo Häppölä from the Institute for Molecular Medicine Finland FIMM, noted.

“Our study demonstrates how we can utilize large-scale medication data in novel ways to help us identify aging individuals with an increased risk of long-term mortality and potentially diminished health status. Future research is needed to understand how approach relates to frailty, quality of life, and essentially translates to health utility”, Paavo Häppölä continued.

Original publication:

Häppölä P, Havulinna AS, Tasa T, Mars NJ, Perola M, Kallela M, Milani L, Koskinen S, Salomaa V, Neale BM, Palotie A, Daly M, Ripatti S. A data-driven medication score predicts 10-year mortality among aging adults. Sci Rep. 2020 Sep 25;10(1):15760. doi: 10.1038/s41598-020-72045-z.