Durvalumab in Advanced Biliary Tract Cancer: Real‐World Data From a Large Cohort of Patients Across Multiple International Centers
Bibliographic record
Abstract
BACKGROUND: We recently published the first real-world multicenter and multi-institutional study of cisplatin, gemcitabine, and durvalumab in patients with advanced biliary tract cancer (BTC). Here we present an expanded patient cohort with an increased sample size and longer median follow-up. METHODS: The study population included patients with advanced BTC, who received cisplatin/gemcitabine plus durvalumab at 55 centers across 12 countries in Europe, the United States, and Asia. The primary endpoints of the study were progression-free survival (PFS) and overall survival (OS). Secondary endpoints were overall response rate (ORR) and safety. RESULTS: Overall, 1358 patients were enrolled. Median PFS was 7.6 months (95% CI: 7.2-8.1), and median OS was 15.6 months (95% CI: 14.8-16.5). ORR was 35.6%, and DCR was 82.7%. Any grade AEs occurred in 1213 patients (89.3%). Grade 3-4 AEs occurred in 597 patients (43.2%). The rate of immune-related AEs (irAE) was 20.3%. Grade 3-4 irAE occurred in 3.0% of patients. At the multivariate analysis for OS, normal albumin level (HR 0.68, 95% CI 0.57-0.81, p < 0.0001), CEA levels within normal ranges (HR 0.68, 95% CI 0.57-0.82, p < 0.0001), NLR < 3 (HR 0.62, 95% CI 0.52-0.74, p < 0.0001), ECOG PS 0 (HR 0.51, 95% CI 0.42-0.61, p < 0.0001), and prior surgery (HR 0.80, 95% CI 0.65-0.99, p = 0.036) were positive prognostic factors. CONCLUSION: The updated findings, derived from an expanded cohort, further support the adoption of durvalumab in combination with gemcitabine and cisplatin in routine clinical practice, reinforcing the efficacy and safety outcomes demonstrated in the phase III TOPAZ-1 trial.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".