Predicting the risk of active pulmonary tuberculosis in people living with HIV: development and validation of a nomogram

Background Diagnosis of pulmonary tuberculosis (PTB) among people living with HIV (PLHIV) was challenging. The study aimed to develop and validated a simple, convenient screening model for prioritizing TB among PLHIV. Methods The study included eligible adult PLHIV participants who attended health care in Yunnan, China, from January 2016 to July 2019. Participants included before June 2018 were in the primary set; others were in the independent validation set. The research applied the least absolute shrinkage and selection operator regression to identify predictors associated with bacteriological confirmed PTB. The TB nomogram was developed by multivariate logistic regression. The C-index, receiver operating characteristic curve (ROC), the Hosmer-Lemeshow goodness of fit test (H-L), and the calibration curves were applied to evaluate and calibrate the nomogram. The developed nomogram was validated in the validation set. The clinical usefulness was assessed by cutoff analysis and decision curve analysis in the primary set. Result The study enrolled 766 PLHIV, of which 507 were in the primary set and 259 in the validation set, 21.5% and 14.3% individuals were confirmed PTB in two sets, respectively. The final nomogram included 5 predictors: current CD 4 cell count, the number of WHO screen tool, previous TB history, pulmonary cavity, and smoking status (p < 0.05). The C-statistic was 0.72 (95% CI 0.66-0.77) in primary set and 0.68 (95% CI 0.58-0.75) in validation set, ROC performed better than other models. The nomogram calibration was good (H-L chi(2) = 8.14, p = 0.15). The area under the decision curve (0.025) outperformed the existing models. The optimal cutoff for screening TB among PLHIV was the score of 100 (sensitivity = 0.93, specificity = 0.35). Conclusion The study developed and validated a discriminative TB nomogram among PLHIV in the moderate prevalence of TB and HIV. The easy-to-use and straightforward nomogram would be beneficial for clinical practice and rapid risk screening in resource-limited settings.