000136752 001__ 136752
000136752 005__ 20240229105056.0
000136752 0247_ $$2doi$$a10.1186/s12876-018-0840-9
000136752 0247_ $$2pmid$$apmid:30005625
000136752 0247_ $$2pmc$$apmc:PMC6045848
000136752 0247_ $$2altmetric$$aaltmetric:46601536
000136752 037__ $$aDKFZ-2018-01190
000136752 041__ $$aeng
000136752 082__ $$a610
000136752 1001_ $$0P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe$$aKühn, Tilman$$b0$$eFirst author$$udkfz
000136752 245__ $$aAnthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults.
000136752 260__ $$aLondon$$bBioMed Central$$c2018
000136752 3367_ $$2DRIVER$$aarticle
000136752 3367_ $$2DataCite$$aOutput Types/Journal article
000136752 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1536312934_14253
000136752 3367_ $$2BibTeX$$aARTICLE
000136752 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000136752 3367_ $$00$$2EndNote$$aJournal Article
000136752 520__ $$aNon-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.
000136752 536__ $$0G:(DE-HGF)POF3-313$$a313 - Cancer risk factors and prevention (POF3-313)$$cPOF3-313$$fPOF III$$x0
000136752 588__ $$aDataset connected to CrossRef, PubMed,
000136752 7001_ $$aNonnenmacher, Tobias$$b1
000136752 7001_ $$0P:(DE-He78)fd4ffe2a3f08e0158b82400acd6716be$$aSookthai, Disorn$$b2$$udkfz
000136752 7001_ $$0P:(DE-He78)ceb74219d144ab5760a228e71440c5ca$$aSchübel, Ruth$$b3$$udkfz
000136752 7001_ $$0P:(DE-He78)2b1939dd3b00e62eeea7798367576c30$$aQuintana Pacheco, Daniel Antonio$$b4$$udkfz
000136752 7001_ $$avon Stackelberg, Oyunbileg$$b5
000136752 7001_ $$0P:(DE-He78)9a183bfc8348c1db81a0ecf1458d0708$$aGraf, Mirja$$b6$$udkfz
000136752 7001_ $$0P:(DE-He78)79ab945544e5bc017a2317b6146ed3aa$$aJohnson, Theron Scot$$b7$$udkfz
000136752 7001_ $$aSchlett, Christopher L$$b8
000136752 7001_ $$0P:(DE-He78)94b37a09583db23ab2d40029b2c6e0b3$$aKirsten, Romy$$b9$$udkfz
000136752 7001_ $$aUlrich, Cornelia M$$b10
000136752 7001_ $$0P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aKaaks, Rudolf$$b11$$udkfz
000136752 7001_ $$aKauczor, Hans-Ulrich$$b12
000136752 7001_ $$aNattenmüller, Johanna$$b13
000136752 773__ $$0PERI:(DE-600)2041351-8$$a10.1186/s12876-018-0840-9$$gVol. 18, no. 1, p. 113$$n1$$p113$$tBMC gastroenterology$$v18$$x1471-230X$$y2018
000136752 909CO $$ooai:inrepo02.dkfz.de:136752$$pVDB
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)0907a10ba1dc8f53f04907f54f6fdcfe$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)fd4ffe2a3f08e0158b82400acd6716be$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)ceb74219d144ab5760a228e71440c5ca$$aDeutsches Krebsforschungszentrum$$b3$$kDKFZ
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)2b1939dd3b00e62eeea7798367576c30$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)9a183bfc8348c1db81a0ecf1458d0708$$aDeutsches Krebsforschungszentrum$$b6$$kDKFZ
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)79ab945544e5bc017a2317b6146ed3aa$$aDeutsches Krebsforschungszentrum$$b7$$kDKFZ
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)94b37a09583db23ab2d40029b2c6e0b3$$aDeutsches Krebsforschungszentrum$$b9$$kDKFZ
000136752 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)4b2dc91c9d1ac33a1c0e0777d0c1697a$$aDeutsches Krebsforschungszentrum$$b11$$kDKFZ
000136752 9131_ $$0G:(DE-HGF)POF3-313$$1G:(DE-HGF)POF3-310$$2G:(DE-HGF)POF3-300$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vCancer risk factors and prevention$$x0
000136752 9141_ $$y2018
000136752 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bBMC GASTROENTEROL : 2015
000136752 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS
000136752 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline
000136752 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database
000136752 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal
000136752 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ
000136752 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ
000136752 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search
000136752 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC
000136752 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bThomson Reuters Master Journal List
000136752 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded
000136752 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection
000136752 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine
000136752 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5
000136752 9201_ $$0I:(DE-He78)C020-20160331$$kC020$$lEpidemiologie von Krebserkrankungen$$x0
000136752 9201_ $$0I:(DE-He78)G110-20160331$$kG110$$lPräventive Onkologie$$x1
000136752 980__ $$ajournal
000136752 980__ $$aVDB
000136752 980__ $$aI:(DE-He78)C020-20160331
000136752 980__ $$aI:(DE-He78)G110-20160331
000136752 980__ $$aUNRESTRICTED