Development and validation of a nomogram for predicting hemoptysis recurrence in cystic bronchiectasis patients following bronchial artery embolization.

BACKGROUND

Hemoptysis is a life-threatening manifestation frequently observed in patients with cystic bronchiectasis (CB), a radiologically defined subtype of bronchiectasis. Bronchial artery embolization (BAE) is widely employed as an effective interventional therapy for controlling hemoptysis. Despite its clinical utility, the risk of recurrence remains high, particularly in patients with CB. Currently, no reliable predictive model specifically targeting CB-related hemoptysis recurrence following BAE has been established, highlighting the need for a tailored prognostic tool in this population.

OBJECTIVE

This study aimed to develop and validate a model to predict the recurrence of hemoptysis in CB patients following BAE, enabling individualized clinical management and prevention strategies.

METHODS

A retrospective study was conducted on 111 CB patients who underwent BAE between January 2015 and June 2020. Clinical, radiological, and laboratory data were collected for analysis. Least absolute shrinkage and selection operator (LASSO) regression was applied to identify relevant predictive variables, followed by multivariable Cox proportional hazards regression to determine independent prognostic factors. Based on these predictors, a nomogram was constructed. Its performance was assessed using the concordance index (C-index), receiver operating characteristic (ROC) curves, area under the curve (AUC), calibration plots, and decision curve analysis (DCA).

RESULTS

Five independent predictors were identified: history of hemoptysis (HR = 3.42, 95% CI: 1.64-7.12,  = 0.001), diabetes (HR = 15.0, 95% CI: 4.69-48.1,  < 0.001), pleural thickening (HR = 3.78, 95% CI: 1.07-13.4,  = 0.039), prolonged hospitalization (HR = 1.99, 95% CI: 1.08-3.67,  = 0.028), and positive sputum culture (HR = 2.29, 95% CI: 1.26-4.19,  = 0.007). The nomogram showed good discriminatory ability, with AUCs of 0.778, 0.797, and 0.829 at 1-, 2-, and 3-year follow-ups, respectively. The integrated Brier score was 0.147, reflecting good overall accuracy. Time-dependent AUC and C-index curves further confirmed the model's prognostic robustness. Calibration plots demonstrated close agreement between predicted and observed recurrence, and decision curve analysis indicated favorable clinical utility. Recurrence-free time was significantly shorter in the high-risk group ( < 0.0001).

CONCLUSION

The nomogram is a reliable tool for predicting hemoptysis recurrence in CB patients after BAE. It facilitates early identification of high-risk patients, enabling timely, targeted interventions and improved outcomes.