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@ARTICLE{Katzke:286665,
      author       = {V. Katzke$^*$ and R. Bajracharya$^*$ and M. I. Nasser and
                      B. Schöttker$^*$ and R. Kaaks$^*$},
      title        = {{N}umber of medically prescribed pharmaceutical agents as
                      predictor of mortality risk: a longitudinal, time-variable
                      analysis in the {EPIC}-{H}eidelberg cohort.},
      journal      = {Scientific reports},
      volume       = {14},
      number       = {1},
      issn         = {2045-2322},
      address      = {[London]},
      publisher    = {Macmillan Publishers Limited, part of Springer Nature},
      reportid     = {DKFZ-2024-00029},
      pages        = {106},
      year         = {2024},
      note         = {#EA:C020#LA:C020#},
      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.},
      cin          = {C020 / C070},
      ddc          = {600},
      cid          = {I:(DE-He78)C020-20160331 / I:(DE-He78)C070-20160331},
      pnm          = {313 - Krebsrisikofaktoren und Prävention (POF4-313)},
      pid          = {G:(DE-HGF)POF4-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:38167443},
      doi          = {10.1038/s41598-023-50487-5},
      url          = {https://inrepo02.dkfz.de/record/286665},
}