Developing a Prediction Score for the Diagnosis of Malignant Pleural Effusion: MPE Score

Abstract

Background: The objective of this study was to develop a diagnostic prediction model for diagnosis of malignant pleural effusion (MPE) from pleural fluid cytology (MPE score). Materials and Methods: Retrospective analysis ofpleural fluid cytology was conducted in patients with MPE between 2018 and 2020. Multivariable logistic regressionwas used to explore the potential predictors. The selected logistic coefficients were transformed into a diagnosticpredictive scoring system. Internal validation was done using the bootstrapping procedure. Results: The data of pleuralfluid cytology from 155 MPE patients were analyzed. Seventy-eight positive pleural cytology patients were found(50.32%). Lung cancer was the cancer most commonly sent for pleural fluid testing, with 66.67% positive cytology.The predictive indicators included pleural fluid protein > 4.64 g/dL, pleural fluid LDH > 555 IU/L, and pleural fluidsugar > 60 mg/dL. Lung mass from imaging and double tap for pleural cytology were used for the derivation of thediagnostic prediction model. The score-based model showed that the area under the receiver operating characteristiccurve was 0.74 (95% CI 0.66-0.82). The developed MPE score ranged from zero to 17. The cut-off point was 15 with88.31% of specificity, 37.18% of sensitivity, positive predictive value of 0.76, and negative predictive value of 0.58.The measurement of the calibration was illustrated using a calibration plot (p-value = 0.49 for the Hosmer-Lemeshowbased goodness of fit). Internal validation with 1,000 bootstrap resampling showed a good discrimination. Conclusions:The MPE score, as the diagnostic prediction model can be used in planning for more efficient diagnosis of MPE inpatients with cancer under MPE