Outcome of adjuvant therapy for biliary tract cancers.
Bibliographic record
Abstract
e14592 Background: There are high rates of recurrence following definitive surgery in patients (pts) with biliary tract cancers (BTCs). Our aim was to review patterns of use and effectiveness of adjuvant therapy (AT) (chemotherapy (CT) +/- radiotherapy (RT)) in pts who underwent definitive surgery for BTC at a tertiary referral centre (Princess Margaret Hospital, Toronto). Methods: The clinical/pathological characteristics, treatment details and survival data of all pts with a diagnosis of BTC who had definitive surgery from Jan 1987 to Sept 2011 were reviewed. Results: The cohort includes 297 pts of which 42% were male, with a median age of 63 yrs, performance status 0-1 in 88%. 56 (19%) had well differentiated, 144 (48%) moderately and 60 (2%) poorly differentiated tumors, 37 (12%) data not available (NA). 125 (42%) and 41 (14%) had R0/R1 resection respectively, 131 (44%) NA. 122 (41%) were node positive, 72 (24%) NA. AT was given in 78 (27%) pts, 49 receiving adjuvant CT and 29 concurrent CT/RT; 34% receiving AT in distal bile duct, 14% in gallbladder, 12% in intrahepatic and 27% in klatskin. 179 (60%) pts recurred; 56/78 (72%) in the AT group (grp) and 123/179 (68%) in non-AT grp, 40 (13%) NA. In the AT and non-AT grps, local recurrence was seen in 7/56 (13%) and 26/123 (21%), distant in 32/56 (57%) and 73/123 (59%), and both in 176/56 (30%) and 24/123 (20%) respectively. In multivariate analysis, node positivity, HR 0.54, 95% CI 0.37 – 0.77, (p=0.001) was the only prognostic factor of DFS after definitive surgery. In node positive population (n=48 with AT, 50 without AT), median DFS was greater in AT grp; 13.8mo vs. 10.4mo (p=0.068). DFS and overall survival (OS) for entire cohort is detailed in Table. Conclusions: Given the limits of this retrospective cohort analysis and potential bias to treat higher risk pts, it does appear that pts receiving adjuvant therapy with node positive disease derived DFS advantage following definitive surgery, though not significant, and is probably an effective option for node positive, curative resected, BTC. However, larger prospective trials are paramount. [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 | 0.003 |
| 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 | 0.000 |
| 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".