Fig. 9

Logistic regression analysis and decision curve analysis for diagnosis of CHD. GS, gravida serum; AF, amniotic fluid; ECG, echocardiography; NT, fetal nuchal translucency. A-E depict the logistic regression analyses. A displays that ECG showed the best diagnostic effect for fetal CHD among the single index. B indicate the diagnostic effects of the double-index is better than that of the single index, when ECG is excluded from the analysis. C illustrates that POSTN and PAPPA in GS among the best diagnostic effect for fetal CHD among the three indexes. D presents the regression analysis with multiple variables (more than 3). E shows ROC of POSTN and PAPPA in GS combined with ECG and ECG alone. In addition, we have listed all parameters such as AUC, sensitivity, specificity, etc. for each group in the Logistic regression analysis in Additional file 3. F is the decision curve analysis (DCA) curve, which shows that the predictive ability of the comprehensive model group(include POSTN, PAPPA and the two clinical indicators, namely NT and age) is significantly higher than that of the diagnosis group without using above CHD markers and clinical indicators. G is the nomograms of the diagnostic model, which represents the prediction of disease scores using a comprehensive model combining clinical indicators and gene expression