A population based analysis of prognostic factors in advanced biliary tract cancer.
Bibliographic record
Abstract
BACKGROUND: Data regarding prognostic factors in advanced biliary tract cancer (BTC) remains scarce. The aim of this study was to review our institutional experience with cisplatin and gemcitabine in advanced BTC as well as to evaluate potential prognostic factors for overall survival (OS). MATERIAL AND METHODS: Consecutive patients with advanced BTC who initiated palliative chemotherapy with cisplatin and gemcitabine from 2009 to 2012 at the BC Cancer Agency were identified using the pharmacy database. Clinicopathologic variables and treatment outcome were retrospectively collected. Potential prognostic factors were assessed by univariate and multivariate analyses. RESULTS: A total of 106 patients were included in the analysis. Median OS was 8.5 months (95% CI: 6.5-10.5). On univariate analysis, poor ECOG performance status (ECOG PS) at diagnosis, primary tumor location (extra-hepatic cholangiocarcinoma, and unknown biliary cancer), and sites of advanced disease (extra-hepatic metastasis) were significantly associated with worse OS (P<0.001, 0.036 and 0.034, respectively). Age, gender, CA19-9, CEA, hemoglobin, neutrophil count, and prior stent were not significantly associated with OS. On multivariate analysis, ECOG PS 2/3 was the only predictor of poor OS (P<0.001), while primary location (P=0.089) and sites of advanced disease (P=0.079) had a non-significant trend towards prognostic significance. CONCLUSIONS: In this population based analysis, a poorer performance status was significantly prognostic of worse OS. Although not significant in our analysis, primary tumor location and sites of advanced disease may also have prognostic relevance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".