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.

Abstract

Health differences among the elderly and the role of medical treatments are topical issues in aging societies. We demonstrate the use of modern statistical learning methods to develop a data-driven health measure based on 21 years of pharmacy purchase and mortality data of 12,047 aging individuals. The resulting score was validated with 33,616 individuals from two fully independent datasets and it is strongly associated with all-cause mortality (HR 1.18 per point increase in score; 95% CI 1.14-1.22; p = 2.25e-16). When combined with Charlson comorbidity index, individuals with elevated medication score and comorbidity index had over six times higher risk (HR 6.30; 95% CI 3.84-10.3; AUC = 0.802) compared to individuals with a protective score profile. Alone, the medication score performs similarly to the Charlson comorbidity index and is associated with polygenic risk for coronary heart disease and type 2 diabetes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age of Onset
  • Aged
  • Aging*
  • Biostatistics / methods*
  • Comorbidity
  • Female
  • Genetic Predisposition to Disease
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Mortality*
  • Time Factors