Prognostic Relevance of Carbohydrate Antigen 19-9 Levels in Patients with Advanced Biliary Tract Cancer
Bibliographic record
Abstract
Abstract Serum carbohydrate antigen 19-9 (CA 19-9) has been identified as biochemical marker for biliary tract cancer (BTC). The purpose of this study was to evaluate its value as a treatment response marker and its value as a prognostic parameter in patients with unresectable BTC. We analyzed 70 patients with BTC treated with chemotherapy. CA 19-9 levels before and after two treatment courses were analyzed with respect to their effect on treatment response. Patients were categorized into two subgroups according to biliary stenting: patients without endoscopic intervention or biliary drainage (non-stent subgroup) and patients with endoluminal stenting (stent subgroup). Pretreatment CA 19-9 levels were prognostic with respect to overall survival for the entire study population. Patients with CA 19-9 levels above the median of 300 units/mL had a nearly 3-fold risk for early death (hazard ratio, 2.92; 95% confidence interval, 1.51-5.64; adjusted P = 0.002) as compared with patients with CA 19-9 levels ≤300 units/mL. An association between CA 19-9 and therapeutic response was observed in the non-stent subgroup (P = 0.001) only. Furthermore, the decrease of CA 19-9 levels after treatment was predictive for improved survival in the non-stent subgroup (adjusted P = 0.018) but not in the stent subgroup. Our results indicate that pretreatment CA 19-9 levels and CA 19-9 decrease after chemotherapy are of prognostic relevance in patients with BTC. (Cancer Epidemiol Biomarkers Prev 2007;16(10):2097–100)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".