CANCER RATIO-BASED DIAGNOSTIC TOOL IN IDENTIFYING MALIGNANT PLEURAL EFFUSION: SENSITIVITY, SPECIFICITY AND CLINICAL INSIGHTS

Abstract

Background: Malignant pleural effusion (MPE) is a common cause of exudative lymphocytic pleural effusion. Although pleural fluid evaluation is routinely performed, cytology or histopathology remains the gold standard for MPE diagnosis. The cancer ratio (CR), calculated by comparing serum LDH to pleural fluid ADA levels, has shown promise in diagnosing MPE. However, no studies have investigated its utility in the Thai population, which has a high tuberculosis prevalence. Objectives: This study aimed to evaluate the diagnostic accuracy of the CR in MPE diagnosis, compare clinical and pleural fluid parameters between MPE and nonMPE cases, determine the appropriate CR cut-off for the Thai population and develop a prediction score for prediagnosing MPE. Results: Between July 2021 and December 2022, patients presenting exudative lymphocytic pleural effusion were included in the study. Demographics, symptoms, radiographic findings and pleural fluid parameters were collected and cytology/histopathology served as the reference test. CR performance was assessed using receiver operating characteristic curves, and a prediction score was developed using multivariable logistic regression analysis. Among 122 patients, 46.7% received a diagnosis of MPE. The CR exhibited a sensitivity of 87.7% and specificity of 72.3% (AUC 0.83) with a cut-off level >10. Patients with MPE showed longer symptom duration, lower fever and massive pleural effusion, which were more common in MPE than nonMPE cases. A prediction score incorporating symptom duration, fever history, effusion amount and CR demonstrated superior diagnostic performance for MPE (AUC 0.94) compared with the CR alone. Conclusion: The CR can effectively differentiate MPE from nonMPE among patients with exudative lymphocytic pleural effusion. A cut-off level >10 is recommended for diagnosing MPE in the Thai population. Combining clinical, radiologic and CR data may aid in prediagnosing MPE; however, further research is needed for validation.