Sensitivity and specificity of routine diagnostic work-up for tuberculosis in lung clinics in Yogyakarta, Indonesia: a cohort study

Abstract

Background Establishing a correct diagnosis is challenging. We aimed to investigate the sensitivity and specificity of routine tuberculosis (TB) diagnostic work-up in lung clinics in Indonesia, a country with the third highest TB burden and the second highest gap between notifications of TB cases and the best estimate of incident cases in the world. Methods In the lung clinics of the Province of Yogyakarta, Indonesia, we recruited all consecutive patients with symptoms suggesting TB, aged ≥18 years. Routine TB examination consisted of clinical evaluation, sputum smear microscopy, and chest radiography. For research purposes, we added sputum culture, Human Immunodeficiency Virus (HIV) testing, and follow-up for 1.5 years or 2.5 years if culture results disagreed with the initial clinical diagnosis. The initial diagnosis was considered incorrect if patients did not respond to treatment. We calculated sensitivity and specificity of the TB routine examination using culture and a composite reference standard (CRS – a combination of routine examination, culture, and follow-up) as the reference standards. All analyses were conducted with IBM SPSS Statistics 25 (IBM Corp., Armonk, NY, USA). Results Between 2013 and 2015, we included 360 participants, and 21 were excluded due to incomplete data. Among those analyzed, 115 were initially diagnosed with smear-positive TB, 12 with smear-negative TB, and 212 non-TB. In 15 study participants, the diagnosis was changed after median 45 (range: 14–870) days; 14 participants initially not diagnosed with TB were later diagnosed with TB, while one subject initially diagnosed with TB actually did not have TB. Compared with culture and CRS, TB routine examination had sensitivity of 85% (95%CI: 77–91) and 90% (95%CI: 84–94), and specificity of 86.3% (95%CI: 81–91) and 99.5% (95%CI: 97–100), respectively. Conclusions A combination of clinical evaluation with sputum microscopy and chest radiography provided high sensitivity and specificity in diagnosing TB in lung clinics; in only 4.4% the diagnosis was incorrect. There is a need to improve routine TB diagnostic work by using clinical evaluation, sputum smear microscopy, and chest radiography all together in other settings, such as in primary health centers. Trial registration NCT02219945 , clinicaltrials.gov . Registered 19 August 2014 (retrospectively registered).

Diagnosis of tuberculosis through breath test: A systematic review

“…In addition, follow-up should be employed to ensure that the diagnosis made was correct. A previous study has shown that follow-up could help to cover the weakness of culture and improve its accuracy [55].…”

“…The existing tests have high sensitivity, such as culture and PCR [1], or very high specificity, such as Gene Xpert [57], or moderate sensitivity, such as sputum smear microscopy [1,55]. However, these highly sensitive tests are not point-of-care, are sputum-dependent, prone to laboratory fallacy, and need trained laboratory personnel.…”

“…A challenge for the breath test development in the future is to detect TB cases with negative sputum smear. Negative sputum smear was shown to have correlation with a misdiagnosis of TB [55]. Another challenge is to investigate whether the breath test can accelerate the diagnostic process and lower its cost.…”

Sensitivity and specificity of an electronic nose in diagnosing pulmonary tuberculosis among patients with suspected tuberculosis

“…Culture though gold standard for TB but single spot sputum culture is challenging; low quality of sputum samples and laboratory errors may jeopardize both sensitivity and specificity. The CRS that diagnoses TB based on comprehensive results of clinical symptoms, bacteriological examinations, CXR, and follow-up, could address these drawbacks of culture [15,19].…”

Tuberculosis diagnostics: overcoming ancient challenges with modern solutions

“…Nevertheless, their efficacy was found to be relatively poor when compared with other more modern methods, which utilise molecular or immunological techniques. The diagnostic flaws of these methods are often attributed to the effect of the human error in interpretation of the results [41]. To overcome this, several companies are developing computational algorithms and the use of Artificial Intelligence (AI) [42] to better interpret chest X-ray results (discussed later).…”