Pleural Fluid Tumour Markers in Malignant Pleural Effusion with Inconclusive Cytologic Results
Bibliographic record
Abstract
BACKGROUND: The presence of tumour cells in pleural fluid or tissue defines an effusion as malignant. Cytology analysis of the pleural fluid has about 60% diagnostic sensitivity. Several tests have been proposed to improve diagnosis-among them, the concentrations of tumour markers in pleural fluid. We evaluated whether the concentrations of tumour markers in pleural fluid could improve the diagnosis of malignant pleural effusion (mpe) when cytology is doubtful. METHODS: Lymphocytic pleural fluids secondary to tuberculosis or malignancy from 156 outpatients were submitted for cytology and tumour marker quantification [carcinoembryonic antigen (cea), cancer antigen 15-3 (ca15-3), carbohydrate antigen 19-9 (ca19-9), cancer antigen 72-4 (ca72-4), cancer antigen 125 (ca125), and cyfra 21-1). Oneway analysis of variance, the Student t-test or Mann-Whitney test, and receiver operating characteristic curves were used in the statistical analysis. RESULTS: Concentrations of the tumour markers cea, ca15-3, ca125, and cyfra 21-1 were higher in mpes than they were in the benign effusions (p < 0.001), regardless of cytology results. The markers ca19-9 and ca72-4 did not discriminate malignant from benign effusions. When comparing the concentrations of tumour markers in mpes having positive, suspicious, or negative cytology with concentrations in benign effusions, we observed higher levels of cea, ca15-3, cyfra 21-1, and ca125 in malignant effusions with positive cytology (p = 0.003, p = 0.001, p = 0.002, and p = 0.001 respectively). In pleural fluid, only ca125 was higher in mpes with suspicious or negative cytology (p = 0.001) than in benign effusions. CONCLUSIONS: Given high specificity and a sensitivity of about 60%, the concentrations of tumour markers in pleural effusions could be evaluated in cases of inconclusive cytology in patients with a high pre-test chance of malignancy or a history of cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".