ArticleJournal of clinical laboratory analysis2019
Diagnosing malignant pleural effusion using clinical and analytical parameters.
Article in Journal of clinical laboratory analysis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Risk factor identification and prediction of pleural effusion following coronary artery bypass grafting.American journal of translational research · 2025Article
- Echogenic swirling pattern, carcinoembryonic antigen, and lactate dehydrogenase in the diagnosis of malignant pleural effusion.Scientific reports · 2022Article
- Development of risk prediction models for lung cancer based on tumor markers and radiological signs.Journal of clinical laboratory analysis · 2021Article
- Article
- Driverless artificial intelligence framework for the identification of malignant pleural effusion.Translational oncology · 2021Article
- Article
- Diagnostic accuracy of cancer ratio for malignant pleural effusion: a systematic review and meta-analysis.Annals of translational medicine · 2019Article
- Diagnosing malignant pleural effusion using clinical and analytical parameters.Journal of clinical laboratory analysis · 2019Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMalignant pleural effusion (MPE) is common and diagnosis is often problematic. A cancer ratio (serum lactate dehydrogenases: pleural adenosine deaminase ratio) has been proposed for diagnosing MPE. However, the usefulness of this "cancer ratio" and the clinical-radiological criteria for diagnosing MPE has not been clearly determined to date. The aim of this study was to assess the performance of those parameters in the diagnosis of MPE.
methodsWe analyzed 240 patients including 120 with MPE and 120 with non-MPE (93 tuberculous and 27 parapneumonic). Patients were divided into two groups: MPE and non-MPE (eg, tuberculous and parapneumonic). We constructed two predictive models to assess the probability of MPE: (a) clinical-radiological data only and (b) a combination of clinical-radiological data, the cancer ratio, and the carcinoembryonic antigen (CEA). The performances of the predictive models were assessed using receiver operating characteristic (ROC) curves and by examining the calibration.
resultsThe area under the ROC curves for model 1 and model 2 were excellent, 0.936 and 0.998, respectively. The overall diagnostic accuracies for model 1 and model 2 were 87.5% and 98.8%, respectively.
conclusionThe results confirm that both models achieved a high diagnostic accuracy for MPE; however, model 2 was superior with the addition of its simplicity of use in daily practice. This model should be applied to determine which patients with a pleural effusion of unknown origin would not benefit from further invasive procedures.
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