Kyaw Ko Ko Htet1, Virasakdi Chongsuvivatwong2, Si Thu Aung3. 1. Department of Medical Research, Ministry of Health and Sports, Pyin Oo Lwin, Myanmar. 2. Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Hat Yai, 90110, Thailand. cvirasak@medicine.psu.ac.th. 3. Department of Public Health, Ministry of Health and Sports, Nay Pyi Taw, Myanmar.
Abstract
BACKGROUND: Globally, using tuberculosis signs and symptoms (TB-SS) as a screening tool has become less important due to its low sensitivity and specificity. We analyzed data from the Myanmar National Tuberculosis (TB) prevalence survey in 2010. The various TB screening models were developed to predict TB by using logistic regression analysis, and their performance on TB prediction was compared by the measures of overall performance, calibration and discrimination ability, and sensitivity and specificity to determine whether social pathology characteristics could be used as a TB screening tool. RESULTS: Among 51,367 participants, 311 (0.6%) had bacteriologically confirmed TB, of which 37.2% were asymptomatic and 2% had a normal chest X-ray. Out of 32 various combinations of signs and symptoms, having any signs and symptoms gave the best sensitivity of 59.8% and specificity of 67.2%, but chest X-ray (CXR) alone gave the highest sensitivity (95.1%) and specificity (86.3%). The next best combination was cough only with a sensitivity of 24.4% and specificity of 85%. Other combinations had poor sensitivity (< 10%). Among various TB screening models, the overall performance R2 was higher in the combined models of social pathology and TB signs and symptoms as well as the social pathology model, compared to TB-SS models (> 10% versus < 3%), although all TB screening models were perfect to predict TB (Brier score = 0). The social pathology model shows a better calibration, more closer to 45° line of calibration plot with Hosmer-Lemeshow test p value = 0.787, than the combined models while it had a better discrimination ability in area under the curve, AUC = 80.4%, compared to TB-SS models with any signs and symptoms, AUC = 63.5% and with any cough, AUC = 57.1% (DeLong p value = 0.0001). Moreover, at the propensity score cutoff value ≥ 0.0053, the combined and social pathology models had sensitivity of ~ 80% and specificity of ~ 70%. The highest population attributable fraction to predict TB by social pathology characteristics was male gender (42.6%), age ≥ 55 years (31.0%), and underweight (30.4%). CONCLUSION: Over one-third of bacteriologically confirmed TB was asymptomatic. The conventional TB-SS screening tool using any TB signs and symptoms had a lower sensitivity and specificity compared to CXR and social pathology screening tools. The social pathology characteristics as TB screening tool had good calibration and can improve the discrimination ability to predict TB than TB-SS screenings and should be encouraged.
BACKGROUND: Globally, using tuberculosis signs and symptoms (TB-SS) as a screening tool has become less important due to its low sensitivity and specificity. We analyzed data from the Myanmar National Tuberculosis (TB) prevalence survey in 2010. The various TB screening models were developed to predict TB by using logistic regression analysis, and their performance on TB prediction was compared by the measures of overall performance, calibration and discrimination ability, and sensitivity and specificity to determine whether social pathology characteristics could be used as a TB screening tool. RESULTS: Among 51,367 participants, 311 (0.6%) had bacteriologically confirmed TB, of which 37.2% were asymptomatic and 2% had a normal chest X-ray. Out of 32 various combinations of signs and symptoms, having any signs and symptoms gave the best sensitivity of 59.8% and specificity of 67.2%, but chest X-ray (CXR) alone gave the highest sensitivity (95.1%) and specificity (86.3%). The next best combination was cough only with a sensitivity of 24.4% and specificity of 85%. Other combinations had poor sensitivity (< 10%). Among various TB screening models, the overall performance R2 was higher in the combined models of social pathology and TB signs and symptoms as well as the social pathology model, compared to TB-SS models (> 10% versus < 3%), although all TB screening models were perfect to predict TB (Brier score = 0). The social pathology model shows a better calibration, more closer to 45° line of calibration plot with Hosmer-Lemeshow test p value = 0.787, than the combined models while it had a better discrimination ability in area under the curve, AUC = 80.4%, compared to TB-SS models with any signs and symptoms, AUC = 63.5% and with any cough, AUC = 57.1% (DeLong p value = 0.0001). Moreover, at the propensity score cutoff value ≥ 0.0053, the combined and social pathology models had sensitivity of ~ 80% and specificity of ~ 70%. The highest population attributable fraction to predict TB by social pathology characteristics was male gender (42.6%), age ≥ 55 years (31.0%), and underweight (30.4%). CONCLUSION: Over one-third of bacteriologically confirmed TB was asymptomatic. The conventional TB-SS screening tool using any TB signs and symptoms had a lower sensitivity and specificity compared to CXR and social pathology screening tools. The social pathology characteristics as TB screening tool had good calibration and can improve the discrimination ability to predict TB than TB-SS screenings and should be encouraged.
Entities:
Keywords:
Screening; Sensitivity and specificity; Social pathology; TB signs and symptoms
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