Carbohydrate antigen 19‐9 is a prognostic and predictive biomarker in patients with advanced pancreatic cancer who receive gemcitabine‐containing chemotherapy
Bibliographic record
Abstract
BACKGROUND: Carbohydrate antigen 19-9 (CA19-9) is a widely used biomarker in pancreatic cancer. There is no consensus on the interpretation of the change in CA19-9 serum levels and its role in the clinical management of patients with pancreatic cancer. METHODS: Individual patient data from 6 prospective trials evaluating gemcitabine-containing regimens from 3 different institutions were pooled. CA19-9 values were obtained at baseline and after successive cycles of treatment. The objective of this study was to correlate a decline in CA19-9 with outcomes while undergoing treatment. RESULTS: A total of 212 patients with locally advanced (n = 50) or metastatic (n = 162) adenocarcinoma of the pancreas were included. Median baseline CA19-9 level was 1077 ng/mL (range, 15-492,241 ng/mL). Groups were divided into those levels below (low) or above (high) the median. Median overall survival (mOS) was 8.7 versus 5.2 months (P = .0018) and median time to progression (mTTP) was 5.8 versus 3.7 months (P = .082) in the low versus high groups, respectively. After 2 cycles of chemotherapy, up to a 5% increase versus ≥ 5% increase in CA19-9 levels conferred an improved mOS (10.3 vs 5.1 months, P = .0022) and mTTP (7.5 vs 3.5 months, P = 0.0005). CONCLUSIONS: In patients who have advanced pancreatic cancer treated with gemcitabine-containing regimens baseline CA19-9 is prognostic for outcome. A decline in CA19-9 after the second cycle of chemotherapy is not predictive of improved mOS or mTTP; thus, CA19-9 decline is not a useful surrogate endpoint in clinical trials. Clinically, a ≥ 5% rise in CA19-9 after 2 cycles of chemotherapy serves as a negative predictive marker.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".