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@ARTICLE{Rosberg:178793,
      author       = {V. Rosberg and J. K. Vishram-Nielsen and A. M. D.
                      Kristensen and M. Pareek and T. S. G. Sehested and P. M.
                      Nilsson and A. Linneberg and L. Palmieri and S. Giampaoli
                      and C. Donfrancesco and F. Kee and G. Mancia and G. Cesana
                      and G. Veronesi and G. Grassi and K. Kuulasmaa and V.
                      Salomaa and T. Palosaari and S. Sans and J. Ferrieres and J.
                      Dallongeville and S. Söderberg and M. Moitry and W. Drygas
                      and A. Tamosiunas and A. Peters and H. Brenner$^*$ and B.
                      Schöttker$^*$ and S. Grimsgaard and T. Biering-Sørensen
                      and M. H. Olsen},
      title        = {{S}imple cardiovascular risk stratification by replacing
                      total serum cholesterol with anthropometric measures: {T}he
                      {MORGAM} prospective cohort project.},
      journal      = {Preventive Medicine Reports},
      volume       = {26},
      issn         = {2211-3355},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {DKFZ-2022-00272},
      pages        = {101700},
      year         = {2022},
      abstract     = {To assess whether anthropometric measures (body mass index
                      [BMI], waist-hip ratio [WHR], and estimated fat mass [EFM])
                      are independently associated with major adverse
                      cardiovascular events (MACE), and to assess their added
                      prognostic value compared with serum total-cholesterol. The
                      study population comprised 109,509 individuals $(53\%$ men)
                      from the MORGAM-Project, aged 19-97 years, without
                      established cardiovascular disease, and not on
                      antihypertensive treatment. While BMI was reported in all,
                      WHR and EFM were reported in ∼52,000 participants.
                      Prognostic importance of anthropometric measurements and
                      total-cholesterol was evaluated using adjusted Cox
                      proportional-hazards regression, logistic regression, area
                      under the receiver-operating-characteristic curve (AUCROC),
                      and net reclassification improvement (NRI). The primary
                      endpoint was MACE, a composite of stroke, myocardial
                      infarction, or death from coronary heart disease. Age
                      interacted significantly with anthropometric measures and
                      total-cholesterol on MACE (P ≤ 0.003), and therefore
                      age-stratified analyses (<50 versus ≥ 50 years) were
                      performed. BMI, WHR, EFM, and total-cholesterol were
                      independently associated with MACE (P ≤ 0.003) and
                      resulted in significantly positive NRI when added to age,
                      sex, smoking status, and systolic blood pressure. Only
                      total-cholesterol increased discrimination ability (AUCROC
                      difference; P < 0.001). In subjects < 50 years, the
                      prediction model with total-cholesterol was superior to the
                      model including BMI, but not superior to models containing
                      WHR or EFM, while in those ≥ 50 years, the model with
                      total-cholesterol was superior to all models containing
                      anthropometric variables, whether assessed individually or
                      combined. We found a potential role for replacing
                      total-cholesterol with anthropometric measures for
                      MACE-prediction among individuals < 50 years when
                      laboratory measurements are unavailable, but not among
                      those ≥ 50 years.},
      keywords     = {ACM, all-cause mortality (Other) / ASCVD, atherosclerotic
                      cardiovascular disease (Other) / AUCROC, area under the
                      receiver-operating-characteristic curve (Other) / Adipose
                      tissue (Other) / Assessment, risk (Other) / BMI, body mass
                      index (Other) / BP, blood pressure (Other) / Body mass index
                      (Other) / CEP, composite cardiovascular endpoint (Other) /
                      CI, confidence interval (Other) / CV, cardiovascular (Other)
                      / CVD, cardiovascular disease (Other) / CVM, cardiovascular
                      mortality (Other) / Cardiovascular diseases (Other) / Chol,
                      serum total cholesterol (Other) / Cholesterol (Other) / DBP,
                      diastolic blood pressure (Other) / EFM, estimated fat mass
                      (Other) / HDL-cholesterol, high density lipoprotein
                      cholesterol (Other) / HR, hazard ratio (Other) / IQR,
                      interquartile range (Other) / MACE, major adverse
                      cardiovascular events (Other) / MBP, mean blood pressure
                      (Other) / MONICA, Multi-national MONItoring of Trends and
                      Determinants in CArdiovascular Disease (Other) / MORGAM,
                      MOnica, Risk, Genetics, Archiving and Monograph (Other) /
                      NRI, net reclassification improvement (Other) / NS,
                      non-significant (Other) / PP, pulse pressure (Other) / SBP,
                      systolic blood pressure (Other) / SCORE, Systematic COronary
                      Risk Evaluation (Other) / WHR, waist-hip ratio (Other) /
                      Waist-hip ratio (Other) / cNRI, continuous net
                      reclassification improvement (Other)},
      cin          = {C070},
      ddc          = {610},
      cid          = {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:35141116},
      pmc          = {pmc:PMC8814644},
      doi          = {10.1016/j.pmedr.2022.101700},
      url          = {https://inrepo02.dkfz.de/record/178793},
}