PURPOSE: The usefulness of a panel of tumour markers and clinical-radiological criteria for diagnosing malignant pleural effusion (MPE) is not clearly stated. Our purpose was to assess the performance of those parameters in the diagnosis of MPE. METHODS: Consecutive patients with exudative PE were enrolled and divided into two groups: MPE and non-MPE. Logistic regression analysis was used to estimate the probability of MPE. Four prognostic models were considered: (1) clinical-radiological variables; (2) analytical variables; (3) combination of clinical and analytical variables; and (4) simpler model removing some analytical variables. Calibration and discrimination (receiver operating characteristics curves and AUC) were performed. RESULTS: A total of 491 pleural exudates were included: tuberculous (n = 72), malignant (n = 211), parapneumonic (n = 115), empyemas (n = 32), or miscellaneous (n = 61). The AUC obtained with Model 1 (absence of chest pain and fever and radiological images compatible with malignancy), Model 2 (CEA, NSE, CYFRA 21-1, and TPS), Model 3 (sum of the variables of models 1 and 2), and Model 4 (the variables of model 1 plus CEA) were 0.918, 0.832, 0.952 (all with a P < 0.05), and 0.939 (P < 0.01 compared to models 1 and 2), respectively. The correct classification rate for Models 1, 2, 3, and 4, was 87.2, 79.5, 88.4, and 87.6 %, respectively. CONCLUSIONS: All models analysed had a good diagnostic yield for MPE, being greater in those that combined radiological and analytical criteria. Although Model 3 obtained a higher yield, the simplest model (Model 4) is very attractive due to its simplicity of use in daily practice.
PURPOSE: The usefulness of a panel of tumour markers and clinical-radiological criteria for diagnosing malignant pleural effusion (MPE) is not clearly stated. Our purpose was to assess the performance of those parameters in the diagnosis of MPE. METHODS: Consecutive patients with exudative PE were enrolled and divided into two groups: MPE and non-MPE. Logistic regression analysis was used to estimate the probability of MPE. Four prognostic models were considered: (1) clinical-radiological variables; (2) analytical variables; (3) combination of clinical and analytical variables; and (4) simpler model removing some analytical variables. Calibration and discrimination (receiver operating characteristics curves and AUC) were performed. RESULTS: A total of 491 pleural exudates were included: tuberculous (n = 72), malignant (n = 211), parapneumonic (n = 115), empyemas (n = 32), or miscellaneous (n = 61). The AUC obtained with Model 1 (absence of chest pain and fever and radiological images compatible with malignancy), Model 2 (CEA, NSE, CYFRA 21-1, and TPS), Model 3 (sum of the variables of models 1 and 2), and Model 4 (the variables of model 1 plus CEA) were 0.918, 0.832, 0.952 (all with a P < 0.05), and 0.939 (P < 0.01 compared to models 1 and 2), respectively. The correct classification rate for Models 1, 2, 3, and 4, was 87.2, 79.5, 88.4, and 87.6 %, respectively. CONCLUSIONS: All models analysed had a good diagnostic yield for MPE, being greater in those that combined radiological and analytical criteria. Although Model 3 obtained a higher yield, the simplest model (Model 4) is very attractive due to its simplicity of use in daily practice.
Authors: Lucía Ferreiro; Francisco Gude; María E Toubes; Adriana Lama; Juan Suárez-Antelo; Esther San-José; Francisco Javier González-Barcala; Antonio Golpe; José M Álvarez-Dobaño; Carlos Rábade; Nuria Rodríguez-Núñez; Carla Díaz-Louzao; Luis Valdés Journal: J Thorac Dis Date: 2017-01 Impact factor: 2.895