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Predicting Survival for Patients with Malignant Pleural Effusion: Development of the CONCH Prognostic Model
Xin Zhang1, Feng-Shuang Yi1, Huan-Zhong Shi1
1Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, People's Republic of China.
Background:
Malignant pleural effusion (MPE) is a frequent complication of advanced malignancies that leads to a poor quality of life and limits treatment options.
Objective:
The objective of this study was to identify biomarkers of survival in patients with MPE, which will greatly facilitate the clinical management of this complication.
Methods:
This retrospective study recruited patients who had been pathologically diagnosed with MPE, regardless of the type of primary cancer, at Beijing Chao-Yang Hospital over 158 months. Demographic, clinical, hematological, and pleural fluid data were collected and analyzed as potential predictors of survival, and a new predictive model was developed based on Cox and logistic regression analyses.
Results:
In our alternative prognostic model (n = 281), four routinely detected variables, namely, carcinoembryonic antigen (CEA) level, monocyte count, N-terminal pro B-type natriuretic peptide (NT-pro-BNP) level, and pleural effusion chloride level on admission, were identified as predictors (the CONCH prognostic score). Patients were divided into three prognosis subgroups based on risk stratification, with median survival periods of 17, 11, and 5 months, respectively. In comparison with the low-risk group, patients in the medium- and high-risk groups showed significantly poorer survival (medium-risk group: hazard ratio [HR], 1.586; 95% confidence interval [CI], 1.047-2.402; P = 0.029; high-risk group: HR, 4.389; 95% CI, 2.432-7.921; P < 0.001).
Conclusion:
Four routinely detected variables were used to develop the CONCH scoring system, which was confirmed to be an accurate prognostic score for patients with MPE. This system can guide the selection of interventions and management for MPE.
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