Bronchoplasty for treating the whole lung atelectasis caused by endobronchial tuberculosis in main bronchus

Development, assessment and validation of a novel prediction nomogram model for risk identification of tracheobronchial tuberculosis in patients with pulmonary tuberculosis

OBJECTIVE

Tracheobronchial tuberculosis (TBTB), a specific subtype of pulmonary tuberculosis (PTB), can lead to bronchial stenosis or bronchial occlusion if not identified early. However, there is currently no available means for predicting the risk of associated TBTB in PTB patients. The objective of this study was to establish a risk prediction nomogram model for estimating the associated TBTB risk in every PTB patient.

METHODS

A retrospective cohort study was conducted with 2153 PTB patients. Optimised characteristics were selected using least absolute shrinkage and selection operator regression. Multivariate logistic regression was applied to build a predictive nomogram model. Discrimination, calibration and clinical usefulness of the prediction model were assessed using C-statistics, receiver operator characteristic curves, calibration plots and decision analysis. The developed model was validated both internally and externally.

RESULTS

Among all PTB patients who underwent bronchoscopies (n=2153), 40.36% (n=869) were diagnosed with TBTB. A nomogram model incorporating 11 predictors was developed and displayed good discrimination with a C-statistics of 0.782, a sensitivity of 0.661 and a specificity of 0.762 and good calibration with a calibration-in-the-large of 0.052 and a calibration slope of 0.957. Model's discrimination was favourable in both internal (C-statistics, 0.782) and external (C-statistics, 0.806) validation. External validation showed satisfactory accuracy (sensitivity, 0.690; specificity, 0.804) in independent cohort. Decision curve analysis showed that the model was clinically useful when intervention was decided on at the exacerbation possibility threshold of 2.3%-99.2%. A clinical impact curve demonstrated that our model predicted high-risk estimates and true positives.

CONCLUSION

We developed a novel and convenient risk prediction nomogram model that enhances the risk assessment of associated TBTB in PTB patients. This nomogram can help identify high-risk PTB patients who may benefit from early bronchoscopy and aggressive treatment to prevent disease progression.

Clinical significance of serum transforming growth factor-β1 and procollagen type I N-propeptide in post-tuberculosis tracheobronchial stenosis

Non-invasive strategies for monitoring post-tuberculosis (TB) tracheobronchial stenosis (PTTS) are clinically important but currently lacking. Transforming growth factor-β1 (TGF-β1) and procollagen type I N-propeptide (PINP) have been identified as markers of fibrosis. The present study aimed to investigate the clinical significance of serum TGF-β1 and PINP in PTTS. Serum samples were collected from 119 patients with tracheobronchial TB after the condition was treated for at least 6 months (59 patients with airway stenosis and 60 patients with no stenosis). Serum TGF-β1 and PINP levels were measured using ELISA and compared between the groups. Relationships between serum TGF-β1 and PINP levels and clinical characteristics, interventional bronchoscopy and outcomes of airway stenosis were analysed. The correlation between TGF-β1 and PINP, and their diagnostic efficacy for airway stenosis were also analysed. The TGF-β1 and PINP levels in the airway stenosis group were higher than those in the non-stenosis group. Furthermore, airway stenosis with atelectasis or mucus plugging was associated with higher TGF-β1 levels, and airway stenosis with atelectasis, mucus plugging, right main bronchus stenosis or severe airway tracheal stenosis was associated with higher PINP levels. In addition, TGF-β1 and PINP levels increased after interventional bronchoscopy therapy and airway stenosis with recurrent stenosis was associated with higher baseline levels of both markers. Finally, TGF-β1 levels were positively correlated with PINP levels in patients with airway stenosis. The area under the receiver operating characteristic curve of TGF-β1 and PINP for distinguishing airway stenosis from non-stenosis cases was 0.824 (95% CI: 0.748-0.900) and 0.863 (95% CI: 0.796-0.930), respectively. Therefore, TGF-β1 and PINP are potential biomarkers that may be useful for diagnosing and monitoring PTTS.