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Malignant Pleural Effusion Risk Based On A Novel Tool Using Homocysteine And Carcinoembryonic Antigen In Pleural Fluid: A Multicenter Study

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URI: http://hdl.handle.net/10498/34336

DOI: 10.1016/J.CLINBIOCHEM.2024.110841

ISSN: 1873-2933

ISSN: 0009-9120

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Santotoribio, Jose D.; Corral Pérez, JuanAuthority UCA; Nuñez Jurado, David; Fatela Cantillo, Daniel; García de la Torre, Ángela; Orantes Maroto, Gabirel; Del Valle Vázquez, Luis; Del Castillo Otero, Daniel; Maira González, María NievesAuthority UCA; Cobos Diaz, Andrés; Juan M, Guerrero; López Sáez, José Juan BoscoAuthority UCA
Date
2024
Department
Didáctica de la Educación Física, Plástica y Musical
Source
Clinical Biochemistry, Vol. 135, 2025
Abstract
Introduction This multicenter study aimed to evaluate the Malignant Pleural Effusion Risk (MPER) diagnostic accuracy in distinguishing between benign and malign pleural effusion. Methods: MPER is based on pleural fluid Homocysteine (HCY) and carcinoembryonic antigen (CEA) that were measured using three different methods. MPER was calculated by assessing a previously published probabilistic model: Probability (%) = 100× (1 + e-z)-1, where Z = 0.5471 × [HCY] + 0.3846 × [CEA]–8.2671. Results A total of 301 patients were included (140 MPE). MPER demonstrated a high AUC (0.891), sensitivity (84.3 %), and specificity (80.7 %) with a cut-off > 35.3 %. Conclusions The MPER model demonstrated a high diagnostic accuracy supporting its use as a novel and powerful tool.Introduction This multicenter study aimed to evaluate the Malignant Pleural Effusion Risk (MPER) diagnostic accuracy in distinguishing between benign and malign pleural effusion. Methods: MPER is based on pleural fluid Homocysteine (HCY) and carcinoembryonic antigen (CEA) that were measured using three different methods. MPER was calculated by assessing a previously published probabilistic model: Probability (%) = 100× (1 + e-z)-1, where Z = 0.5471 × [HCY] + 0.3846 × [CEA]–8.2671. Results A total of 301 patients were included (140 MPE). MPER demonstrated a high AUC (0.891), sensitivity (84.3 %), and specificity (80.7 %) with a cut-off > 35.3 %. Conclusions The MPER model demonstrated a high diagnostic accuracy supporting its use as a novel and powerful tool.
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