A Population-Based Retrospective Study of Biliary Tract Cancers in Alberta, Canada
Bibliographic record
Abstract
Background: Biliary tract cancers (BTC) are uncommon malignancies and are underrepresented in the literature. Methods: We performed a retrospective population-based review of adult patients with biopsy-confirmed BTC in Alberta from 2000 to 2015. Demographic data, risk factors, symptoms, treatment, and staging data were collected and analyzed. Survival analyses were completed. Results: A total of 1604 patients were included in our study, of which 766 (47.8%) were male. The median age at diagnosis was 68 (range 19–99). There were 374 (23.3%) patients with resectable tumors at diagnosis versus 597 (37.2%) with unresectable tumors. Of the patients, 380 (21.5%) received chemotherapy (CT) and 81 (5.0%) underwent radiation therapy. There was a clear trend with worsening stage and performance status associated with shorter median overall survival (OS). Ampulla of Vater tumors had the best median OS (25.69 months), while intrahepatic bile duct cancers had the worst (5.78 months). First-line palliative CT regimens included gemcitabine+cisplatin (OS 14.98 months (mo), n = 212), single agent gemcitabine (OS 12.42 mo, n = 22), capecitabine (OS 8.12 mo, n = 8), and capecitabine+gemcitabine (OS 6.93 mo, n = 13). Patients with advanced or metastatic disease who received first-line gemcitabine+cisplatin had a median OS of 11.8 months (n = 119). Conclusion: BTCs have poor survival. Worse outcomes occur in higher stage and poorer Eastern Cooperative Oncology Group (ECOG) performance status patients across all tumor subtypes. Tumor resectability at diagnosis was associated with better OS. Our study supports the use of gemcitabine+cisplatin as a combination first-line palliative CT, as patients treated in Alberta have a comparable OS to that reported in the ABC-02 phase III study.
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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 | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".