ArticleScientific reports2024
Number of medically prescribed pharmaceutical agents as predictor of mortality risk: a longitudinal, time-variable analysis in the EPIC-Heidelberg cohort.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Polypharmacy Among 200 000 Subjects of the Population-Based German National Cohort Study (NAKO), Aged 19-74: A Baseline Analysis.Deutsches Arzteblatt international · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
The number of prescribed medications might be used as proxy indicator for general health status, in models to predict mortality risk. To estimate the time-varying association between active pharmaceutical ingredient (API) count and all-cause mortality, we analyzed data from a population cohort in Heidelberg (Germany), including 25,546 participants with information on medication use collected at 3-yearly intervals from baseline recruitment (1994-1998) until end of 2014. A total of 4548 deaths were recorded until May 2019. Time-dependent modeling was used to estimate hazard ratios (HR) and their 95% confidence intervals (CI) for all-cause mortality in relation to number of APIs used, within three strata of age (≤ 60, > 60 to ≤ 70 and > 70 years) and adjusting for lifestyle-related risk factors. For participants reporting commonly used APIs only (i.e., API types accounting for up to 80% of medication time in the population) total API counts showed no association with mortality risk within any age stratum. However, when at least one of the APIs was less common, the total API count showed a strong relationship with all-cause mortality especially up to age ≤ 60, with HR up to 3.70 (95% CI 2.30-5.94) with 5 or 6 medications and 8.19 (5.61-11.97) for 7 or more APIs (versus none). Between > 60 and 70 years of age this risk association was weaker, with HR up to 3.96 (3.14-4.98) for 7 or more APIs, and above 70 years it was weakened further (HR up to 1.54 (1.34-1.79)). Multiple API-use may predict mortality risk in middle-aged and women and men ≤ 70 years, but only if it includes at least one less frequently used API type. With advancing age, and multiple medication becomes increasingly prevalent, the association of API count with risk of death progressively attenuates, suggesting an increasing complexity with age of underlying mortality determinants.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.