Development of a clinical algorithm-based scoring system to diagnose smear-negative pulmonary tuberculosis in Sabah, Malaysia using the modified Delphi Method

Background: Tuberculosis (TB) remains a major global health threat, particularly in resourceconstrained settings where delayed diagnosis of smear-negative pulmonary TB is common due to limited access to rapid molecular diagnostics. This study aimed to develop a clinical algorithm-based scoring system to aid the diagnosis of smear-negative pulmonary TB among symptomatic patients in Sabah, Malaysia. In this manuscript we present the development of the algorithm. Methods: A modified Delphi process was conducted between January and June 2024 involving three rounds of expert consultation via email to identify key clinical parameters for diagnosing smear-negative TB. This was followed by a consensus meeting to finalise the parameters and assign weightings. The algorithm was then applied to a dataset of 60 symptomatic smear-negative individuals of whom 29 were confirmed to be TB and 31 not TB based on culture. The sensitivity, specificity, positive predictive value (PPV) and negative predictive values (NPV) of the algorithm were calculated to obtain a cut-off score for ‘likely TB’ vs ‘unlikely TB’. Results: Of 27 invited experts, 23 (85.2%) consented to participate in the Delphi process and contributed to the final consensus. Fifty-four parameters were identified in Round One, reduced to 26 in Round Two and 23 in Round Three. Following the consensus meeting, 21 weighted parameters (scores 1–10) were incorporated into the final algorithm. The clinical algorithm achieved an area under the receiver operating characteristic curve (AUC) of 0.88. A cut-off score of 19.5 differentiated ‘likely TB’ from ‘unlikely TB’, yielding a sensitivity of 86.2%, specificity of 77.4%, PPV of 78.1%, and NPV of 85.7%. Conclusions: This diagnostic clinical algorithm has the potential to facilitate doctors practicing in resource- constraint settings to make a diagnosis of smear-negative TB. Next steps include prospective validation of the algorithm. Keywords: Modified Delphi; smear-negative tuberculosis; diagnosis; clinical algorithm; consensus