Evidence map›Paper›PMID 30005625›Full record

ArticleBMC gastroenterology2018

Anthropometric and blood parameters for the prediction of NAFLD among overweight and obese adults.

Tilman Kühn, Tobias Nonnenmacher, Disorn Sookthai, Ruth Schübel, Daniel Antonio Quintana Pacheco, Oyunbileg von Stackelberg, Mirja E Graf, Theron Johnson, Christopher L Schlett, Romy Kirsten and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC gastroenterology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Association between body fat percentage and metabolic and hematologic biomarkers in Korean adults.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Current Options and Future Directions for NAFLD and NASH Treatment.International journal of molecular sciences · 2021
    Review
  14. HbAJournal of clinical and translational hepatology · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 2 countries.

Tilman KühnGerman Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Tobias NonnenmacherDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, D-69120, Heidelberg, Germany.
Disorn SookthaiGerman Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Ruth SchübelGerman Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Daniel Antonio Quintana PachecoGerman Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Oyunbileg von StackelbergDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, D-69120, Heidelberg, Germany.
Mirja E GrafGerman Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Theron JohnsonGerman Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Christopher L SchlettDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, D-69120, Heidelberg, Germany.
Romy KirstenNational Center for Tumor Diseases (NCT), Liquid Biobank, Im Neuenheimer Feld 460, 69120, Heidelberg, Germany.
Cornelia M UlrichDepartment of Population Health Sciences, University of Utah, 2000 Circle of Hope, Salt Lake City, UT, 84112-5550, USA.
Rudolf KaaksGerman Cancer Research Center (DKFZ), Division of Cancer Epidemiology, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.
Hans-Ulrich KauczorDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, D-69120, Heidelberg, Germany.
Johanna NattenmüllerDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, D-69120, Heidelberg, Germany. Johanna.nattenmueller@med.uni-heidelberg.de.
Heidelberg University · DEUniversity Hospital Heidelberg · DEGerman Cancer Research Center · DEUniversity of Utah · US

Funding

Helmholtz-Gemeinschaft Metabolic DysfunactionHelmholtz-Gemeinschaft Metabolic Dysfunction
6 · The paper itself

Abstract

backroundNon-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.

methods143 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.

resultsNAFLD 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.

conclusionsThe 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.

Indexed as

AnthropometryAdultAgedAlanine TransaminaseBiomarkersFemaleGlycated HemoglobinHumansInsulin ResistanceMaleMiddle AgedModels, StatisticalNon-alcoholic Fatty Liver DiseaseObesityOverweightAlanine TransaminaseBiomarkersGlycated Hemoglobinhemoglobin A1c protein, humanALTInsulinLiver fat contentMagnetic resonance images (MRI)Non-alcoholic fatty liver disease (NAFLD)Obesity

Identifiers

PMID30005625
PMCPMC6045848
OpenAlexW2883506068

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.