Factors associated with reaching maintenance therapy in patients with advanced biliary tract cancer treated with durvalumab: Real‐world results from a multicenter and multinational study
Bibliographic record
Abstract
Standard of care first-line systemic treatment for advanced biliary tract cancer includes chemo-immunotherapy with gemcitabine, cisplatin, and durvalumab, followed by maintenance durvalumab monotherapy. The present work aims to investigate the differences in baseline clinical and molecular characteristics between patients with early progression during chemo-immunotherapy and those who reach durvalumab maintenance therapy. The study population included patients with unresectable, locally advanced, or metastatic BTC who received treatment at 38 clinical Institutions in 12 countries from July 2021 to December 2023. The primary objective of the study was to investigate whether baseline clinical and molecular characteristics differed between patients with early progression during chemo-immunotherapy versus those reaching durvalumab maintenance therapy. Four hundred forty-eight patients were included in this study. Two hundred twenty-seven patients (50.7%) received maintenance with durvalumab monotherapy, whereas 221 (49.3%) did not receive maintenance therapy due to PD during first-line chemo-immunotherapy before completing 8 cycles. Results show that patients who received maintenance were more likely to be older (≥70 years), have an ECOG = 0, locally advanced disease, and a neutrophil-to-lymphocyte ratio (NLR) <3. A higher proportion of patients with BAP1 mutations received maintenance, while TP53 mutations were more common in those who progressed early. According to the present analysis, a substantial proportion of patients (50.7%) with advanced BTC who were treated with chemotherapy plus durvalumab proceeded to receive maintenance therapy with durvalumab monotherapy, with a median treatment duration of 4.4 cycles. Patients ≥70 years, with ECOG PS 0, with locally advanced disease, and with NLR <3 had a higher likelihood of receiving maintenance therapy.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".