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

Abstract

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 χ2 = 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.

Development and validation of a risk prediction model for pulmonary tuberculosis among presumptive tuberculosis cases in Ethiopia

“…This is similar to a model that used CD4 count, CXR abnormality, previous TB treatment, smoking and a number of WHO symptoms to predict TB among HIV patients. 22 However, the predictive accuracy of our model was lower than other models that use Anti Retroviral Treatment (ART) status, body mass index and CD4 count (AUC=0.79) 23 ; HIV status, diabetes and age (AUC=0.82) 41 ; and Midupper arm circumference (MUAC) and haemoglobin (AUC=0.75). 21 Some of these prediction rules 21 23 have been only designed for people living with HIV, and they might be limited in their ability to generalise to HIV-negative populations.…”

“…These factors have been identified by previous studies as predictors of TB. 22 37–41 Close contacts of infectious TB are at a higher risk of becoming infected with Mycobacterium TB and development of primary pulmonary TB, 42 due to airborne transmission of the bacteria. 43 On the other hand, chronic cough, weight loss, low-grade fever and night sweats are the classical symptoms of PTB.…”

“…20 Some studies have developed clinical risk scores with varying performances to predict TB among HIV patients in Ethiopia 21 and other settings. [22][23][24] However, a risk score to predict pulmonary TB among patients with presumptive TB is yet to be developed in Ethiopia. Therefore, this study aimed to develop a score for predicting the risk of pulmonary TB among patients with presumptive TB, using nationally representative Ethiopian TB prevalence survey data.…”

Risk score prediction for bacteriologically confirmed tuberculosis among adults with HIV on antiretroviral therapy in northwest Ethiopia: prognostic model development

“…Since then, despite the well expansion of ART sites and TB/HIV-collaborative prevention activities, TB is the major cause of morbidity and mortality among PWH in Ethiopia. Recent evidence shows that a risk score prediction model is used for predicting high-risk groups for TB among PWH, which is an important tool in resource-limited countries like Ethiopia to intervene early [9,10]. Therefore, we conducted this risk score prediction model for TB among adults with HIV, which will be applicable at any healthcare facility found in Ethiopia.…”

Development and Evaluation of a Nomogram for Predicting the Outcome of Immune Reconstitution Among HIV/AIDS Patients Receiving Antiretroviral Therapy in China

“…Nomogram, as a convenient and useful model for clinicians, integrates multiple key factors, and each relevant parameter is scored based on its value. [ 27 ] In terms of AIDS, the nomograms are frequently applied to assess the risk of HIV infection and the incidence of AIDS and non‐AIDS diseases. [ 28 ] With the development of ART in recent years, some nomograms have also been established to predict the mortality of HIV/AIDS patients after ART.…”