Clinical identification of malignant pleural effusions

INTRODUCTION: Pleural effusions frequently signal disseminated cancer. Diagnostic markers of pleural malignancy at presentation that would assess cancer risk and would streamline diagnostic decisions remain unidentified. METHODS: A consecutive cohort of 323 patients with pleural effusion (PE) from different etiologies were recruited between 2013 and 2017 and was retrospectively analyzed. Data included history, chest X-ray, and blood/pleural fluid cell counts and biochemistry. Group comparison, receiver-operator characteristics, unsupervised hierarchical clustering, binary logistic regression, and random forests were used to develop the malignant pleural effusion detection (MAPED) score. MAPED was validated in an independent retrospective UK cohort (n = 238). RESULTS: Five variables showed significant diagnostic power and were incorporated into the 5-point MAPED score. Age > 55 years, effusion size > 50% of the most affected lung field, pleural neutrophil count 〈 2,500/mm(3), effusion protein 〉 3.5 g/dL, and effusion lactate dehydrogenase > 250 U/L, each scoring one point, predicted underlying cancer with the area under curve(AUC) = 0.819 (P < 10(−15)) in the derivation cohort. The integrated discrimination improvement of MAPED scores showed an increase compared to cytology (p <0.001). Decision curve analysis indicated that the MAPED score generated net clinical benefit. In the validation dataset, the AUC of MAPED scores was 0.723 ( P = 3 × 10(−9)) for the MAPED score. Interestingly, MAPED correctly identified 33/42(79%) of cytology-negative patients that indeed had cancer. CONCLUSIONS: The MAPED score identifies malignant pleural effusions with satisfactory accuracy and can be used complementary to cytology to streamline diagnostic procedures. CONDENSED ABSTRACT: Diagnostic markers for malignant pleural effusions remain uncertain. The MAPED score identifies malignant pleural effusions and complements cytology and confers no additional risk to the patient or cost to the healthcare system.