Objective To establish and verify a nomogram based on quantitative CT for predicting the risk of bronchiec-tasis hemoptysis.Methods The general and quantitative CT indexes of 233 patients with bronchiectasis were collected retrospectively.Stratified random sampling was used to divide patients into training group(n = 133)and verification group(n = 100)according to ratio of 6∶ 4,and patients were divided into two groups according to the occurrence of hemoptysis during the follow-up within 2 years.In the training group,the independent risk factors of bronchiectasis hemoptysis were de-termined by multi-factor stepwise Logistic regression,and the nomogram was constructed.The calibration curve was used to evaluate the goodness of fit of the model,the receiver operating characteristic(ROC)curve was used to evaluate the predic-tive efficiency of the model,and the decision curve analysis(DCA)was used to evaluate the clinical application value of the model.Results Multivariate Logistic regression results showed that smoking history,the total number of involved bron-chus,the cross-sectional area of the most severely dilated bronchus,the degree of the most severely dilated bronchus were independent risk factors for bronchiectasis hemoptysis.Nomogram showed good calibration and differentiation ability with the area under the curve(AUC)of 0.951(95% CI:0.914-0.989)in the training group and 0.956(95% CI:0.918-0.994)in the verificationgroup.Theanalysisofdecisioncurve(DCA)showedthattherewasofclinicalpracticalvaluein the nomogram model.Conclusion The nomogram constructed based on quantitative CT has good clinical predictive effi-cacy and has been verified reliably.
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