BACKGROUND: Hepascore combining serum bilirubin, gamma glutamyl transpeptidase, hyaluronic acid (HA) and alpha2-macroglobulin with age and sex, was reported as relevant in predicting liver fibrosis in patients with chronic HCV infection and was proposed as an alternative to liver biopsy. METHODS: Since an automated HA assay (Latex method, Wako, Japan) became available, we investigated to automate Hepascore by simultaneous measurements of components using an OLYMPUS AU640 analyzer (Tokyo, Japan). For its clinical evaluation, we considered a cohort of chronic HCV patients included in a multicenter prospective study (ANRS HC EP 23 Fibrostar). RESULTS: Automated Hepascore was not significantly different than assayed as previously described. An improvement in HA variability was evidenced. In 512 chronic HCV patients, automated Hepascore, using ROC curves analysis, showed good predictive performances for significant fibrosis (AUROC=0.81), severe fibrosis (AUROC=0.82), and cirrhosis (AUROC=0.88). For significant fibrosis, Hepascore (cut-off=0.5) had a sensitivity of 0.77, a specificity of 0.70, a positive predictive value of 0.71 and a negative predictive value (NPV) of 0.77. Hepascore <0.25 could exclude significant fibrosis with a sensitivity of 0.95 and a NPV of 0.90 and Hepascore <0.75 could exclude cirrhosis with a sensitivity of 0.86 and a NPV of 0.97. CONCLUSIONS: This study shows that Hepascore, a non-invasive index of liver fibrosis, necessitating only one serum sample, can be totally automated using a single analyzer and confirms that Hepascore accurately predicts liver fibrosis in chronic HCV. Hepascore might be largely used in assessing liver fibrosis as surrogate to the liver biopsy.
BACKGROUND: Hepascore combining serum bilirubin, gamma glutamyl transpeptidase, hyaluronic acid (HA) and alpha2-macroglobulin with age and sex, was reported as relevant in predicting liver fibrosis in patients with chronic HCV infection and was proposed as an alternative to liver biopsy. METHODS: Since an automated HA assay (Latex method, Wako, Japan) became available, we investigated to automate Hepascore by simultaneous measurements of components using an OLYMPUS AU640 analyzer (Tokyo, Japan). For its clinical evaluation, we considered a cohort of chronic HCV patients included in a multicenter prospective study (ANRS HC EP 23 Fibrostar). RESULTS: Automated Hepascore was not significantly different than assayed as previously described. An improvement in HA variability was evidenced. In 512 chronic HCV patients, automated Hepascore, using ROC curves analysis, showed good predictive performances for significant fibrosis (AUROC=0.81), severe fibrosis (AUROC=0.82), and cirrhosis (AUROC=0.88). For significant fibrosis, Hepascore (cut-off=0.5) had a sensitivity of 0.77, a specificity of 0.70, a positive predictive value of 0.71 and a negative predictive value (NPV) of 0.77. Hepascore <0.25 could exclude significant fibrosis with a sensitivity of 0.95 and a NPV of 0.90 and Hepascore <0.75 could exclude cirrhosis with a sensitivity of 0.86 and a NPV of 0.97. CONCLUSIONS: This study shows that Hepascore, a non-invasive index of liver fibrosis, necessitating only one serum sample, can be totally automated using a single analyzer and confirms that Hepascore accurately predicts liver fibrosis in chronic HCV. Hepascore might be largely used in assessing liver fibrosis as surrogate to the liver biopsy.
Authors: Sim Yee Ong; Lara Dolling; Jeannette L Dixon; Amanda J Nicoll; Lyle C Gurrin; Michelle Wolthuizen; Erica M Wood; Greg J Anderson; Grant A Ramm; Katrina J Allen; John K Olynyk; Darrell Crawford; Jennifer Kava; Louise E Ramm; Paul Gow; Simon Durrant; Lawrie W Powell; Martin B Delatycki Journal: BMJ Open Date: 2015-08-12 Impact factor: 2.692
Authors: John K Olynyk; Martin B Delatycki; Sim Yee Ong; Tiffany Khoo; Amanda J Nicoll; Lyle Gurrin; Thomas Worland; Puraskar Pateria; Louise E Ramm; Adam Testro; Gregory J Anderson; Richard Skoien; Lawrie W Powell; Grant A Ramm Journal: Sci Rep Date: 2021-07-19 Impact factor: 4.379