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A novel superior medication-based chronic disease score predicted all-cause mortality in independent geriatric cohorts.

Authors :
Quinzler R
Freitag MH
Wiese B
Beyer M
Brenner H
Dahlhaus A
Döring A
Freund T
Heier M
Knopf H
Luppa M
Prokein J
Riedel-Heller SG
Schäfer I
Scheidt-Nave C
Scherer M
Schöttker B
Szecsenyi J
Thürmann P
van den Bussche H
Gensichen J
Haefeli WE
Source :
Journal of clinical epidemiology [J Clin Epidemiol] 2019 Jan; Vol. 105, pp. 112-124. Date of Electronic Publication: 2018 Sep 22.
Publication Year :
2019

Abstract

Objectives: On the basis of current treatment guidelines, we developed and validated a medication-based chronic disease score (medCDS) and tested its association with all-cause mortality of older outpatients.<br />Study Design and Setting: Considering the most prevalent chronic diseases in the elderly German population, we compiled a list of evidence-based medicines used to treat these disorders. Based on this list, a score (medCDS) was developed to predict mortality using data of a large longitudinal cohort of older outpatients (training sample; MultiCare Cohort Study). By assessing receiver-operating characteristics (ROC) curves, the performance of medCDS was then confirmed in independent cohorts (ESTHER, KORA-Age) of community-dwelling older patients and compared with already existing medication-based scores and a score using selected anatomical-therapeutic-chemical (ATC) codes.<br />Results: The final medCDS score had an ROC area under the curve (AUC) of 0.73 (95% CI 0.70-0.76). In the validation cohorts, its ROC AUCs were 0.79 (0.76-0.82, KORA-Age) and 0.74 (0.71-0.78, ESTHER), which were superior to already existing medication-based scores (RxRisk, CDS) and scores based on pharmacological ATC code subgroups (ATC3) or age and sex alone (Age&Sex).<br />Conclusions: A new medCDS, which is based on actual treatment standards, predicts mortality of older outpatients significantly better than already existing scores.<br /> (Copyright © 2018 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1878-5921
Volume :
105
Database :
MEDLINE
Journal :
Journal of clinical epidemiology
Publication Type :
Academic Journal
Accession number :
30253216
Full Text :
https://doi.org/10.1016/j.jclinepi.2018.09.004