Susana Herrera Lara1, Estrella Fernández-Fabrellas2, Gustavo Juan Samper2, Josefa Marco Buades3, Rafael Andreu Lapiedra4, Amparo Pinilla Moreno3, María Morales Suárez-Varela5,6,7. 1. Pulmonology Department, Dr Peset University Hospital, Avenue Gaspar Aguilar, 90, 46017, Valencia, Spain. susancord5@hotmail.com. 2. Pulmonology Department, General University Consorci Hospital, Valencia, Spain. 3. Hematology Department, Dr Peset University Hospital, Valencia, Spain. 4. Hematology Department, La Fe University and Polytechnic Hospital, Valencia, Spain. 5. Unit of Public Health and Environmental Care, Department of Preventive Medicine, University of Valencia, Valencia, Spain. 6. Biomedical Research Centre Network on Epidemiology and Public Health (CIBERESP), Institute of Health Carlos III, Madrid, Spain. 7. Center for Public Health Research (CSISP-FISABIO), Valencia, Spain.
Abstract
BACKGROUND: The usefulness of clinical, radiological and pleural fluid analytical parameters for diagnosing malignant and paramalignant pleural effusion is not clearly stated. Hence this study aimed to identify possible predictor variables of diagnosing malignancy in pleural effusion of unknown aetiology. METHODS: Clinical, radiological and pleural fluid analytical parameters were obtained from consecutive patients who had suffered pleural effusion of unknown aetiology. They were classified into three groups according to their final diagnosis: malignant, paramalignant and benign pleural effusion. The CHAID (Chi-square automatic interaction detector) methodology was used to estimate the implication of the clinical, radiological and analytical variables in daily practice through decision trees. RESULTS: Of 71 patients, malignant (n = 31), paramalignant (n = 15) and benign (n = 25), smoking habit, dyspnoea, weight loss, radiological characteristics (mass, node, adenopathies and pleural thickening) and pleural fluid analytical parameters (pH and glucose) distinguished malignant and paramalignant pleural effusions (all with a p < 0.05). Decision tree 1 classified 77.8% of malignant and paramalignant pleural effusions in step 2. Decision tree 2 classified 83.3% of malignant pleural effusions in step 2, 73.3% of paramalignant pleural effusions and 91.7% of benign ones. CONCLUSIONS: The data herein suggest that the identified predictor values applied to tree diagrams, which required no extraordinary measures, have a higher rate of correct identification of malignant, paramalignant and benign effusions when compared to techniques available today and proved most useful for usual clinical practice. Future studies are still needed to further improve the classification of patients.
BACKGROUND: The usefulness of clinical, radiological and pleural fluid analytical parameters for diagnosing malignant and paramalignant pleural effusion is not clearly stated. Hence this study aimed to identify possible predictor variables of diagnosing malignancy in pleural effusion of unknown aetiology. METHODS: Clinical, radiological and pleural fluid analytical parameters were obtained from consecutive patients who had suffered pleural effusion of unknown aetiology. They were classified into three groups according to their final diagnosis: malignant, paramalignant and benign pleural effusion. The CHAID (Chi-square automatic interaction detector) methodology was used to estimate the implication of the clinical, radiological and analytical variables in daily practice through decision trees. RESULTS: Of 71 patients, malignant (n = 31), paramalignant (n = 15) and benign (n = 25), smoking habit, dyspnoea, weight loss, radiological characteristics (mass, node, adenopathies and pleural thickening) and pleural fluid analytical parameters (pH and glucose) distinguished malignant and paramalignant pleural effusions (all with a p < 0.05). Decision tree 1 classified 77.8% of malignant and paramalignant pleural effusions in step 2. Decision tree 2 classified 83.3% of malignant pleural effusions in step 2, 73.3% of paramalignant pleural effusions and 91.7% of benign ones. CONCLUSIONS: The data herein suggest that the identified predictor values applied to tree diagrams, which required no extraordinary measures, have a higher rate of correct identification of malignant, paramalignant and benign effusions when compared to techniques available today and proved most useful for usual clinical practice. Future studies are still needed to further improve the classification of patients.
Authors: Luis Valdés; Esther San-José; Lucía Ferreiro; Antonio Golpe; Francisco-Javier González-Barcala; María E Toubes; María X Rodríguez-Álvarez; José M Álvarez-Dobaño; Nuria Rodríguez-Núñez; Carlos Rábade; Francisco Gude Journal: Clin Respir J Date: 2014-03-20 Impact factor: 2.570
Authors: Luis Valdés; Esther San-José; Lucía Ferreiro; Francisco-Javier González-Barcala; Antonio Golpe; José M Álvarez-Dobaño; María E Toubes; Nuria Rodríguez-Núñez; Carlos Rábade; Adriana Lama; Francisco Gude Journal: Lung Date: 2013-10-02 Impact factor: 2.584
Authors: Kendall J Kiser; Sara Ahmed; Sonja Stieb; Abdallah S R Mohamed; Hesham Elhalawani; Peter Y S Park; Nathan S Doyle; Brandon J Wang; Arko Barman; Zhao Li; W Jim Zheng; Clifton D Fuller; Luca Giancardo Journal: Med Phys Date: 2020-08-28 Impact factor: 4.071