Predicting Malignant and Paramalignant Pleural Effusions by Combining Clinical, Radiological and Pleural Fluid Analytical Parameters

Our plain-English summary of Predicting Malignant and Paramalignant Pleural Effusions by Combining Clinical, Radiological and Pleural Fluid Analytical Parameters, by S. Herrera Lara, E. Fernández-Fabrellas, G. Juan Samper, et al (Lung, 2017).

The study

• Authors: S. Herrera Lara, E. Fernández-Fabrellas, G. Juan Samper, J. Marco Buades, R. Andreu Lapiedra, A. Pinilla Moreno, M. Morales Suárez-Varela
• Journal: Lung
• Published: 2017;195(5):653-660
• Cited by: 31 articles, as counted by NIH iCite
• Read it: PubMed · Publisher

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.

In plain English

This prospective observational cohort study, carried out at the Dr. Peset University Hospital in Valencia, Spain, from 2013 to 2015, analysed 71 patients with fluid around the lung (pleural effusion) whose cause was unknown at first. By final diagnosis, 31 had malignant effusions (cancer cells in the pleural space), 15 had paramalignant effusions (caused by a tumour but with no cancer cells found in the fluid or tissue) and 25 had benign effusions. Two malignant cases were due to mesothelioma, and two benign effusions were attributed to asbestos exposure. The authors found no difference between the groups in asbestos exposure. Breathlessness, weight loss, lung nodules, pleural thickening and pleural fluid glucose differed between groups, and pleural fluid pH was lower in malignant than in paramalignant effusions. The authors built decision trees, in which a lung mass on imaging was the main predictor. The first tree correctly classified 71.8% of patients overall. A second tree, built from breathlessness, lung mass and cut-offs for pleural fluid pH and LDH, correctly classified 76.1%. The authors concluded the trees are a simple tool for usual clinical practice, and named the small sample size as the main limitation.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: prospective observational cohort study using decision-tree (CHAID) analysis to predict the type of pleural effusion
• Who was studied: 73 patients enrolled and 71 analysed (2 excluded because no cells were obtained from the pleural fluid), all with pleural effusion of unknown cause, at the Dr. Peset University Hospital, Valencia, Spain, 2013 to 2015. Final diagnoses: malignant 31 (43.7%), paramalignant 15 (21.1%), benign 25 (35.2%).
• Exposure: This was not a study of an exposure. It studied clinical, radiological and pleural fluid test results as predictors of effusion type. Possible occupational exposure was recorded as background data, and the groups did not differ in exposure to asbestos.
• Main results:
  • Among the 31 malignant effusions, 2 (6.5%) were due to mesothelioma.
  • Among the 25 benign effusions, 2 (8%) were attributed to exposure to asbestos.
  • The lung was the most frequent site of the primary tumour in both the malignant group (51.6%) and the paramalignant group (73.3%).
  • Breathlessness (dyspnoea) occurred in 70.4% of all patients and in 87.1% of patients with malignant effusion (p = 0.013).
  • Weight loss differed between groups (p = 0.016).
  • A lung nodule was present in up to 60% of patients with paramalignant effusion (p = 0.024).
  • Pleural thickening was seen in 11 of 31 (35.5%) malignant, 2 of 15 (13.3%) paramalignant and 2 of 25 (8%) benign cases (p = 0.031).
  • Malignant effusions had a lower pleural fluid pH than paramalignant effusions (p less than 0.001). In Table 2, the overall comparison of pH across all three groups was not statistically significant (p greater than 0.05).
  • Pleural fluid glucose was lower in the malignant group than in the other groups (p = 0.021).
  • In both decision trees, a lung mass was the main predictor variable.
  • Decision tree 1 (personal history of cancer, dyspnoea, mass, pleural thickening) correctly classified 71.8% of patients overall, with a cross-validation of 0.059.
  • Decision tree 2 used dyspnoea, mass, pleural fluid pH (above or below 7.38) and pleural fluid LDH (above or below 169 UI/L). It correctly classified 76.1% of patients overall: 80.6% of malignant, 73.3% of paramalignant and 72% of benign cases, with a cross-validation of 0.057.
  • In tree 2, among patients with no lung mass and pleural fluid LDH of 169 UI/L or less, 91.7% of effusions were benign.
• The authors' conclusion: The authors concluded that the decision trees are a simple tool to help usual clinical practice tell malignant from paramalignant pleural effusion when the cause of the effusion is unknown.
• Limitations the authors state:
  • The small sample size; the authors state the results would have been more conclusive with more pleural effusions.
  • Few or methodologically different published studies were available for comparison.

Topics

The National Library of Medicine indexes this study under subjects our site covers: Asbestosis.

Medical terms in this study, explained in our Lexicon: Pleural Effusion, Habit, Pleural Thickening.

Related studies

• Expression Profiles of Cytokine mRNAs in the Pleural Fluid Reveal Differences Among Tuberculosis, Malignancies, and Pneumonia-Exudative Pleural Effusions — D.L. Espósito, V.R. Bollela, et al. (2015)
• Vascular endothelial growth factor in pleural fluid for differential diagnosis of benign and malignant origin and its clinical applications — A. Fiorelli, G. Vicidomini, et al. (2011)
• Adenosine Deaminase in Pleural Effusion and Its Relationship with Clinical Parameters in Patients with Malignant Pleural Mesothelioma — Y. Nakajima, K. Kuribayashi, et al. (2020)
• Utility of hyaluronic acid in pleural fluid for differential diagnosis of pleural effusions: likelihood ratios for malignant mesothelioma — S. Atagi, M. Ogawara, et al. (1997)
• Diffuse pleural thickening following heart failure-related pleural effusions in an asbestos exposed patient — M. Evison, P. Barber (2015)
• Ultrastructural studies of malignant cells in fluids — G.A. Herrera, J.A. Wilkerson (1985)

Browse more research in Lung, or return to medical research.