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Development of Seru...
Development of Serum Marker Models to Increase Diagnostic Accuracy of Advanced Fibrosis in Nonalcoholic Fatty Liver Disease: The New LINKI Algorithm Compared with Established Algorithms
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- Lykiardopoulos, Byron (författare)
- Linköpings universitet,Institutionen för medicin och hälsa,Medicinska fakulteten
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- Hagström, Hannes (författare)
- Karolinska Institutet,Karolinska Institute, Sweden
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- Fredrikson, Mats (författare)
- Linköpings universitet,Avdelningen för neuro- och inflammationsvetenskap,Medicinska fakulteten
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- Ignatova, Simone (författare)
- Linköpings universitet,Avdelningen för cellbiologi,Medicinska fakulteten
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- Stal, Per (författare)
- Karolinska Institutet,Karolinska Institute, Sweden
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- Hultcrantz, Rolf (författare)
- Karolinska Institutet,Karolinska Institute, Sweden
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- Ekstedt, Mattias (författare)
- Linköpings universitet,Avdelningen för kardiovaskulär medicin,Medicinska fakulteten,Region Östergötland, Magtarmmedicinska kliniken
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- Kechagias, Stergios (författare)
- Linköpings universitet,Avdelningen för kardiovaskulär medicin,Medicinska fakulteten,Region Östergötland, Magtarmmedicinska kliniken
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(creator_code:org_t)
- 2016-12-09
- 2016
- Engelska.
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Ingår i: PLOS ONE. - : PUBLIC LIBRARY SCIENCE. - 1932-6203. ; 11:12
- Relaterad länk:
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https://liu.diva-por... (primary) (Raw object)
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https://journals.plo...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Background and Aim Detection of advanced fibrosis (F3-F4) in nonalcoholic fatty liver disease (NAFLD) is important for ascertaining prognosis. Serum markers have been proposed as alternatives to biopsy. We attempted to develop a novel algorithm for detection of advanced fibrosis based on a more efficient combination of serological markers and to compare this with established algorithms. Methods We included 158 patients with biopsy-proven NAFLD. Of these, 38 had advanced fibrosis. The following fibrosis algorithms were calculated: NAFLD fibrosis score, BARD, NIKEI, NASH-CRN regression score, APRI, FIB-4, Kings score, GUCI, Lok index, Forns score, and ELF. Study population was randomly divided in a training and a validation group. A multiple logistic regression analysis using bootstrapping methods was applied to the training group. Among many variables analyzed age, fasting glucose, hyaluronic acid and AST were included, and a model (LINKI-1) for predicting advanced fibrosis was created. Moreover, these variables were combined with platelet count in a mathematical way exaggerating the opposing effects, and alternative models (LINKI-2) were also created. Models were compared using area under the receiver operator characteristic curves (AUROC). Results Of established algorithms FIB-4 and Kings score had the best diagnostic accuracy with AUROCs 0.84 and 0.83, respectively. Higher accuracy was achieved with the novel LINKI algorithms. AUROCs in the total cohort for LINKI-1 was 0.91 and for LINKI-2 models 0.89. Conclusion The LINKI algorithms for detection of advanced fibrosis in NAFLD showed better accuracy than established algorithms and should be validated in further studies including larger cohorts.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
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