A population-based study of biliary tract cancers (BTCs) in Alberta, Canada: How do our patients fare?
Bibliographic record
Abstract
246 Background: BTCs are poorly studied due to their rarity and heterogeneity. We explored demographics and outcomes of BTC pts over a 15 year period. Methods: All patients (pts) with biopsy-proven BTC (intrahepatic [IC] and extrahepatic [EC] cholangiocarcinomas, gallbladder cancers [GB], and ampulla of vater cancers [AV]) in Alberta were reviewed from January 1, 2000, to December 31, 2015. Demographic, pathologic, and survival data were extracted from electronic charts. Descriptive statistics were utilized. Overall survival (OS) was defined as the time from pathologic diagnosis to death date. Results: A total of 1,718 pts with BTCs were identified. Median age was 68 with 52% being male. The Table demonstrates OS breakdown based on tumour location and stage. Regardless of location of primary tumour, grade impacted survival (median OS in with well differentiated tumours vs undifferentiated tumors 26.6 vs 3.9 months). Pts who received standard of care palliative cisplatin/gemcitabine (Cis/Gem) chemotherapy (n = 123) had a median OS of 15.4 months. Conclusions: Patients with AV and IC have the best and worst prognosis, respectively. Shorter survival is observed with higher stage, grade, and unresectable disease. Pts who received palliative Cis/Gem had better OS than reported in the pivotal phase III trial. Further analysis of prognostic factors will be presented. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| 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) | 0.002 | 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".