A clinical score for identifying active tuberculosis while awaiting microbiological results: Development and validation of a multivariable prediction model in sub-Saharan Africa

Background In highly resource-limited settings, many clinics lack same-day microbiological testing for active tuberculosis (TB). In these contexts, risk of pretreatment loss to follow-up is high, and a simple, easy-to-use clinical risk score could be useful. Methods and findings We analyzed data from adults tested for TB with Xpert MTB/RIF across 28 primary health clinics in rural South Africa (between July 2016 and January 2018). We used least absolute shrinkage and selection operator regression to identify characteristics associated with Xpert-confirmed TB and converted coefficients into a simple score. We assessed discrimination using receiver operating characteristic (ROC) curves, calibration using Cox linear logistic regression, and clinical utility using decision curves. We validated the score externally in a population of adults tested for TB across 4 primary health clinics in urban Uganda (between May 2018 and December 2019). Model development was repeated de novo with the Ugandan population to compare clinical scores. The South African and Ugandan cohorts included 701 and 106 individuals who tested positive for TB, respectively, and 686 and 281 randomly selected individuals who tested negative. Compared to the Ugandan cohort, the South African cohort was older (41% versus 19% aged 45 years or older), had similar breakdown of biological sex (48% versus 50% female), and had higher HIV prevalence (45% versus 34%). The final prediction model, scored from 0 to 10, included 6 characteristics: age, sex, HIV (2 points), diabetes, number of classical TB symptoms (cough, fever, weight loss, and night sweats; 1 point each), and >14-day symptom duration. Discrimination was moderate in the derivation (c-statistic = 0.82, 95% CI = 0.81 to 0.82) and validation (c-statistic = 0.75, 95% CI = 0.69 to 0.80) populations. A patient with 10% pretest probability of TB would have a posttest probability of 4% with a score of 3/10 versus 43% with a score of 7/10. The de novo Ugandan model contained similar characteristics and performed equally well. Our study may be subject to spectrum bias as we only included a random sample of people without TB from each cohort. This score is only meant to guide management while awaiting microbiological results, not intended as a community-based triage test (i.e., to identify individuals who should receive further testing). Conclusions In this study, we observed that a simple clinical risk score reasonably distinguished individuals with and without TB among those submitting sputum for diagnosis. Subject to prospective validation, this score might be useful in settings with constrained diagnostic resources where concern for pretreatment loss to follow-up is high. Author summary Why was this study done? In high-burden settings, up to 40% of patients with confirmed tuberculosis (TB) are lost to follow-up between the time they initially present for diagnosis and the time treatment can be initiated. A simple clinical prediction rule for initiation of empiric treatment could therefore be very helpful, but existing prediction rules for TB have been designed for use in specific contexts (e.g., HIV clinics and contact investigation), require data and/or infrastructure (e.g., radiography) that are unlikely to be available in highly resource-limited settings, or have been constructed in a format that is difficult to implement for busy midlevel clinicians with little time or access to computers. What did the researchers do and find? We developed a simple clinical risk score for diagnosis of TB among adults presenting to primary health clinics in rural South Africa and validated the score in urban Uganda. This score (ranging from 1 to 10) is easy to calculate by hand and requires only information readily accessible to clinicians in highly resource-limited settings. This score adds clinical utility at cutoffs that likely reflect the risk-benefit ratio of making a TB diagnosis when same-day microbiological testing is unavailable. What do these findings mean? If prospectively validated in other populations, this clinical risk score could improve the process of empiric TB diagnosis in peripheral health settings where access to same-day microbiological testing is lacking and the risk of loss to follow-up is high. This clinical risk score might be used for patients at high risk to initiate a short-term empirical course of 4-drug TB treatment on the same day of their clinic visit until their microbiological test results are available.