A single blood test adjusted for different liver fibrosis targets improves fibrosis staging and especially cirrhosis diagnosis

Abstract

Fibrosis blood tests are usually developed using significant fibrosis, which is a unique diagnostic target; however, these tests are employed for other diagnostic targets, such as cirrhosis. We aimed to improve fibrosis staging accuracy by simultaneously targeting biomarkers for several diagnostic targets. A total of 3,809 patients were included, comprising 1,012 individuals with chronic hepatitis C (CHC) into a derivation population and 2,797 individuals into validation populations of different etiologies (CHC, chronic hepatitis B, human immunodeficiency virus/CHC, nonalcoholic fatty liver disease, alcohol) using Metavir fibrosis stages as reference. FibroMeter biomarkers were targeted for different fibrosis‐stage combinations into classical scores by logistic regression. Independent scores were combined into a single score reflecting Metavir stages by linear regression and called Multi‐FibroMeter Version Second Generation (V2G). The primary objective was to combine the advantages of a test targeted for significant fibrosis (FibroMeterV2G) with those of a test targeted for cirrhosis (CirrhoMeterV2G). In the derivation CHC population, we first compared Multi‐FibroMeterV2G to FibroMeterV2G and observed significant increases in the cirrhosis area under the receiver operating characteristic curve (AUROC), Obuchowski index (reflecting all fibrosis‐stage AUROCs), and classification metric (six classes expressed as a correctly classified percentage) and a nonsignificant increase in significant fibrosis AUROC. Thereafter, we compared it to CirroMeterV2G and observed a nonsignificant increase in the cirrhosis AUROC. In all 3,809 patients, respective accuracies for Multi‐FibroMeterV2G and FibroMeterV2G were the following: cirrhosis AUROC, 0.906 versus 0.878 (P < 0.001; versus CirroMeterV2G, 0.897, P = 0.014); Obuchowski index, 0.795 versus 0.791 (P = 0.059); classification, 86.0% versus 82.1% (P < 0.001); significant fibrosis AUROC, 0.833 versus 0.832 (P = 0.366). Multi‐FibroMeterV2G had the highest correlation with the area of portoseptal fibrosis and the highest reproducibility over time. Correct classification rates of Multi‐FibroMeter with hyaluronate (V2G, 86.0%) or without (V3G, 86.1%) did not differ (P = 0.938). Conclusion: Multitargeting biomarkers significantly improves fibrosis staging and especially cirrhosis diagnosis compared to classical single‐targeted blood tests. (Hepatology Communications 2018;2:455‐466)

Systematic Review with Meta-Analyses: Diagnostic Accuracy of FibroMeter Tests in Patients with Non-Alcoholic Fatty Liver Disease

“…Calès and colleagues combined FibroMeter V2G and CirrhoMeter V2G into a score called Multi-FibroMeter. This score showed significant increases in the AUROC for cirrhosis compared to FibroMeter V2G, which leads to the conclusion that, in the recommended head-to-head comparison studies, Multi-FibroMeter should also have a role [41].…”

Noninvasive Fibrosis Assessment in Chronic Hepatitis C Infection: An Update

“…The FibroMeter test combines platelet count, prothrombin index, AST, A2M, HA, blood urea nitrogen, and age. 88 A study by Calès et al 89 included patients with CLD (including chronic HCV infection), multi-FibroMeter showed overall accuracy in fibrosis staging and diagnosis of cirrhosis superior to classical single-targeted blood tests or TE. The sequential algorithm for fibrosis evaluation (SAFE biopsy) 90 is a stepwise combination of APRI, Forns index, and FibroTest at the time of LB.…”

The using of genetic markers as a possibility of predicting the rate of progress of liver fibrosis in patients with chronic hepatitis B

“…Для зіставлення динаміки фіброзу печінки у хворих на ХГВ в І та ІІ групах були вибрані по 10 осіб зі ступенем фіброзу F1, F2 та F3, тобто кількість пацієнтів з певним ступенем фіброзу була однаковою (таблиці [7][8].…”

“…Функціонування цитокінової мережі визначається багатьма чинниками, зокрема й генетичними. Молекулярною 23/ Том XXVIII / 3 основою функціонування цитокінів є поліморфізм генів цитокінів та його рецепторів [5,6,7].…”