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Phenotyping malignant pleural effusions

Authors: Macy Mei Sze Lui; Y. C. Gary Lee; Deirdre B. Fitzgerald;

Phenotyping malignant pleural effusions

Abstract

Patients with malignant pleural effusions (MPEs) are heterogenous in their disease course, symptom severity, responses to cancer therapies, fluid recurrence rates, and thus need for definitive fluid control measures. To tailor the most appropriate treatment for individual patients, clinicians need to 'phenotype' the patients and predict their clinical course. This review highlights the recent efforts to develop better predictive tools and knowledge gaps for further research.The LENT scoring system, which includes pleural fluid lactate dehydrogenase, performance status, serum neutrophil-to-lymphocyte ratio and tumor type, allows prediction of the survival of patients with MPE. Symptomatic response after therapeutic pleural drainage is highly variable; ongoing studies aim to identify those who would derive symptomatic benefit from fluid drainages. Multivariate analysis found that patients with low pleural fluid pH [odds ratio (OR) 37.04], large effusions (OR 3.31), and increasing age (OR 1.02) were more likely to require pleurodesis or indwelling pleural catheter placement for fluid control. Better predictive tools for rate of fluid recurrence and likelihood of successful pleurodesis would help guide clinical decision-making.Phenotyping MPE would guide the formulation of optimal management for individual MPE patients.

Keywords

Male, Prognosis, Catheterization, Pleural Effusion, Malignant, Catheters, Indwelling, Phenotype, Drainage, Health Status Indicators, Humans, Pleura, Female, Karnofsky Performance Status, Pleurodesis

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    14
    popularity
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    influence
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    Top 10%
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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Average
Top 10%
Related to Research communities
Cancer Research
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