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@ARTICLE{Khn:136752,
      author       = {T. Kühn$^*$ and T. Nonnenmacher and D. Sookthai$^*$ and R.
                      Schübel$^*$ and D. A. Quintana Pacheco$^*$ and O. von
                      Stackelberg and M. Graf$^*$ and T. S. Johnson$^*$ and C. L.
                      Schlett and R. Kirsten$^*$ and C. M. Ulrich and R. Kaaks$^*$
                      and H.-U. Kauczor and J. Nattenmüller},
      title        = {{A}nthropometric and blood parameters for the prediction of
                      {NAFLD} among overweight and obese adults.},
      journal      = {BMC gastroenterology},
      volume       = {18},
      number       = {1},
      issn         = {1471-230X},
      address      = {London},
      publisher    = {BioMed Central},
      reportid     = {DKFZ-2018-01190},
      pages        = {113},
      year         = {2018},
      abstract     = {Non-alcoholic fatty liver disease (NAFLD) comprises
                      non-progressive steatosis and non-alcoholic steatohepatitis
                      (NASH), the latter of which may cause cirrhosis and
                      hepatocellular carcinoma (HCC). As NAFLD detection is
                      imperative for the prevention of its complications, we
                      evaluated whether a combination of blood-based biomarkers
                      and anthropometric parameters can be used to predict NAFLD
                      among overweight and obese adults.143 overweight or obese
                      non-smokers free of diabetes $(50\%$ women, age:
                      35-65 years) were recruited. Anthropometric indices and
                      routine biomarkers of metabolism and liver function were
                      measured to predict magnetic resonance (MR) - derived NAFLD
                      by multivariable logistic regression models. In addition, we
                      evaluated to which degree the use of more novel biomarkers
                      (adiponectin, leptin, resistin, C-reactive protein, TNF-α,
                      IL-6, IL-8 and interferon-γ) could improve prediction
                      models.NAFLD was best predicted by a combination of age,
                      sex, waist circumference, ALT, HbA1c, and HOMA-IR at an area
                      under the receiver operating characteristic curve (AUROC) of
                      0.87 $(95\%$ CI: 0.81, 0.93) before and 0.85 $(95\%$ CI:
                      0.78, 0.91) after internal bootstrap validation. The use of
                      additional biomarkers of inflammation and metabolism did not
                      improve NAFLD prediction. Previously published indices
                      predicted NAFLD at AUROCs between 0.71 and 0.82.The AUROC of
                      > 0.8 obtained by our regression model suggests the
                      feasibility of a non-invasive detection of NAFLD by
                      anthropometry and circulating biomarkers, even though
                      further increments in the capacity of prediction models may
                      be needed before NAFLD indices can be applied in routine
                      clinical practice.},
      cin          = {C020 / G110},
      ddc          = {610},
      cid          = {I:(DE-He78)C020-20160331 / I:(DE-He78)G110-20160331},
      pnm          = {313 - Cancer risk factors and prevention (POF3-313)},
      pid          = {G:(DE-HGF)POF3-313},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:30005625},
      pmc          = {pmc:PMC6045848},
      doi          = {10.1186/s12876-018-0840-9},
      url          = {https://inrepo02.dkfz.de/record/136752},
}