Prediction of Post-Tuberculosis Lung Function Impairment

Objective: The aim of this study was to establish prediction equations for post-tuberculosis residual lung function in patients successfully treated for pulmonary tuberculosis (PTB). Methods: This study took place at the Yaounde Jamot Hospital of Yaounde (YJH) and used data from three cross-sectional studies conducted from January to July 2015 (7 months), December 2015 to May 2016 (6 months) and from January to May 2017 (5 months). Adults successful treated for bacteriologically proven pulmonary TB were included. Spirometric indices including forced expiratory volume in 1s (FEV1), forced vital capacity (FVC) and FEV1/FVC ratio were measured using standard methods. Predicted values were estimated using the reference spirometric equations of the Global Lung Initiative equations (GLI) 2012. General linear models were used to establish prediction equations of post-tuberculous residual lung function. Internal validation of the derived models used the bootstrap resampling procedures. A difference was considered significant if p < 5%. Results: In this study, 400 patients (53.5% men) were included. The median age (25th -75th percentiles) of men was 40 (31-50) years and that of women was 36(27.8-46) years (p=0.002). Determinants of the post-tuberculosis spirometric indices vary according to each indice and include age, weight, height, body mass index, smoking, duration of symptoms before TB treatment, persistent of respiratory symptoms after TB treatment, persistent of cavity lesions and extension of lung sequelae. The prediction equations of the spirometric indices have been established separately for men and women to account for significant differences in the absolute values of spirometric parameters in men and women. The prediction equations of residual lung function parameters were in the form: lung function parameters = Intercept + β1*P1 + β2*P2 +…βn*Pn; βn is regression coefficient for corresponding predictor (Pn), for categorical variables Pn is 1 if the modality is present and 0 if the modality is absent. For each of the spirometric variable, differences in performance measures (optimism) were mostly marginal. Conclusion: The equations developed and validated in this study could help the selection of patients in whom spirometry should be a priority after TB treatment. Like any newly developed model, results from this study are just preliminary findings. Models will require independent external validation to establish the performance both in the study setting and in other settings