Feasibility and potential benefits of second-line chemotherapy in patients with advanced biliary tract cancer.
Bibliographic record
Abstract
338 Background: Chemotherapy is effective in metastatic or unresectable biliary tract cancer (BTC). The benefits of second-line chemotherapy (CT2) are unclear. Methods: We retrospectively studied all patients (pts) receiving at least one cycle of chemotherapy for advanced BTC at our institution between 1991 and 2011. We analyzed pt and chemotherapy characteristics (type of regimen; tumor response; time to progression (TTP); and overall survival (OS)). The objectives were: 1) to characterize pts eligible for CT2; 2) to evaluate the efficacy of CT2. Results: 367, 89 (24%), and 24 (6%) pts received CT1, CT2, and CT3, respectively. Primary tumor location was the gallbladder (30%), intraphepatic (16%), perihilar (20%), distal common bile duct (20%), and ampulla of Vater (14%). 88% had a baseline performance status of 0-1 prior to CT1. The regimen and efficacy data of CT1 and CT2 are presented in the Table . On univariate analysis females (p=0.002) and pts with TTP >6 months on CT1 (p=0.016) were the only variables associated with receiving CT2. The only factor associated with disease control (objective response+ stable disease) on CT2 was the regimen type (75% with a doublet versus 46% with monotherapy, p=0.03). Conclusions: Among patients with advanced BTC treated with chemotherapy, less than 25% received CT2; but responses were seen and were surprisingly high even in this selected population. Pts with a longer TTP on CT1 were more likely to be offered CT2. Better disease control with CT2 occurs with a doublet than single agent, however clearly more effective therapies must be found. Updated data 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".