Accurate prediction of biliary atresia with an integrated model using MMP-7 levels and bile acids

Background Biliary atresia(BA)is a rare fatal liver disease in children,and the aim of this study was to develop a method to diagnose BA early.Methods We determined serum levels of matrix metalloproteinase-7(MMP-7),the results of 13 liver tests,and the levels of 20 bile acids,and integrated computational models were constructed to diagnose BA.Results Our findings demonstrated that MMP-7 expression levels,as well as the results of four liver tests and levels of ten bile acids,were significantly different between 86 BA and 59 non-BA patients(P<0.05).The computational prediction model revealed that MMP-7 levels alone had a higher predictive accuracy[area under the receiver operating characteristic curve(AUC)=0.966,95%confidence interval(CI):0.942,0.989]than liver test results and bile acid levels.The AUC was 0.890(95%CI 0.837,0.943)for liver test results and 0.825(95%CI 0.758,0.892)for bile acid levels.Furthermore,bile levels had a higher contribution to enhancing the predictive accuracy of MMP-7 levels(AUC=0.976,95%CI 0.953,1.000)than liver test results.The AUC was 0.983(95%CI 0.962,1.000)for MMP-7 levels combined with liver test results and bile acid levels.In addition,we found that MMP-7 levels were highly correlated with gamma-glutamyl transferase levels and the liver fibrosis score.Conclusion The innovative integrated models based on a large number of indicators provide a noninvasive and cost-effective approach for accurately diagnosing BA in children.