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Eur J Intern Med. 2015 Oct;26(8):628-34. doi: 10.1016/j.ejim.2015.07.005. Epub 2015 Jul 18.

Online combination algorithm for non-invasive assessment of chronic hepatitis B related liver fibrosis and cirrhosis in resource-limited settings.

Author information

1
Department of Gastroenterology and Hepatology, University Clinical Center Tuzla, Tuzla, Bosnia and Herzegovina. Electronic address: snermin@gmail.com.
2
Department of Pathology, University Clinical Center Tuzla, Tuzla, Bosnia and Herzegovina.
3
Department of Gastroenterology and Hepatology, University Clinical Center Tuzla, Tuzla, Bosnia and Herzegovina.
4
Department of Gastroenterology, University Clinical Hospital Mostar, Mostar, Bosnia and Herzegovina.
5
Department of Infectious Diseases, University Clinical Center Tuzla, Tuzla, Bosnia and Herzegovina.

Abstract

OBJECTIVE:

The use of commercially available noninvasive markers for chronic hepatitis B (CHB) related fibrosis is not widely available in developing countries so clinicians in those countries frequently use free alternatives. We aimed to create an optimized algorithm for selection of patients with the highest probability for presence/absence of significant liver fibrosis and cirrhosis based on the use of multiple free scores.

METHODS:

We evaluated six free noninvasive markers for CHB related fibrosis against liver biopsy and selected the best thresholds for prediction/exclusion of significant fibrosis and cirrhosis in CHB patients. Algorithm based on four scores and their corresponding thresholds was created.

RESULTS:

The calculator based on developed algorithm can be found at http://www.chb-lfc.com. We evaluated 211 patients in main group and 65 patients in external validation group. We selected four scores for creation of combination algorithm. The algorithm was able to classify 123/211 (58.3%) patients with a 93.5% accuracy of correct classification for prediction of presence/absence of significant fibrosis in main group. In validation group, the algorithm was able to classify 48/65 (73.8%) of patients with 93.8% (45/48) overall accuracy. When used to predict presence/absence of cirrhosis, the algorithm was able to correctly classify 181/211 (85.8%) and 59/65 (90.8%) of patients in main and validation group, respectively, with an overall accuracy of 97.8% and 98.3%, respectively.

CONCLUSION:

Developed algorithm based on routine laboratory tests is a usable, applicable and accurate tool for diagnosis of CHB related fibrosis and cirrhosis, suitable for resource-limited settings where more expensive modalities are unavailable.

KEYWORDS:

Algorithm; Calculator; Cirrhosis; Developing countries; Liver fibrosis; Non-invasive

PMID:
26194460
DOI:
10.1016/j.ejim.2015.07.005
[Indexed for MEDLINE]

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