Browsing by Author "Hanrahan, Colleen F."

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    A clinical score for identifying active tuberculosis while awaiting microbiological results: Development and validation of a multivariable prediction model in sub- Saharan Africa
    (PLoS medicine, 2020) Baik, Yeonsoo; Rickman, Hannah M.; Hanrahan, Colleen F.; Mmolawa, Lesego; Kitonsa, Peter J.; Sewelana, Tsundzukana; Nalutaaya, Annet; Kendall, Emily A.; Lebina, Limakatso; Martinson, Neil; Katamba, Achilles; Dowdy, David W.
    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.
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    Implementation of Xpert MTB/RIF in Uganda: Missed Opportunities to Improve Diagnosis of Tuberculosis
    (Oxford University Press, 2016) Hanrahan, Colleen F.; Haguma, Priscilla; Ochom, Emmanuel; Kinera, Irene; Cobelens, Frank; Cattamanchi, Adithya; Davis, Luke; Katamba, Achilles; Dowdy, David
    The effect of Xpert MTB/RIF (Xpert) scale-up on patient outcomes in low-income settings with a high tuberculosis (TB) burden has not been established. We sought to characterize the effectiveness of Xpert as implemented across different levels of the healthcare system in Uganda. Methods. We reviewed laboratory records from 2012 to 2014 at 18 health facilities throughout Uganda. In 8 facilities, Xpert had been implemented onsite since 2012, and in 10 sites Xpert was available as an offsite referral test from another facility. We describe Xpert testing volumes by facility, Xpert and smear microscopy results, and downtime due to malfunction and cartridge stockouts.We compare TB treatment initiation as well as time to treatment between facilities implementing Xpert and those that did not. Results. The median number of Xpert assays run at implementing facilities was 25/month (interquartile range [IQR], 10–63), amounting to 8% of total capacity. Among 1251 assays run for a new TB diagnosis, 19% were positive. Among 1899 patients with smear-negative presumptive TB, the proportion starting TB treatment was similar between Xpert facilities (11%; 95% confidence interval [CI], 9%–13%) and non-Xpert facilities (9%; 95% CI, 8%–11%; P = .325). In Xpert facilities, a positive Xpert preceded TB treatment initiation in only 12 of 70 (17%) smear-negative patients initiated on treatment. Conclusions. Xpert was underutilized in Uganda and did not significantly increase the number of patients starting treatment for TB. Greater attention must be paid to appropriate implementation of novel diagnostic tests for TB if these new tools are to impact patient important outcomes.