New systemic treatment paradigms in advanced biliary tract cancer and variations in patient access across Europe
Bibliographic record
Abstract
In recent years, treatment options for patients with advanced biliary tract cancer (BTC) have increased significantly due to the positive results from phase 2/3 clinical trials of immune checkpoint inhibitors, combined with chemotherapy, and molecularly targeted agents. These advances have led to the need for molecular testing to identify actionable alterations and patients amenable to targeted therapies. However, these improvements have brought with them many questions and challenges, including the identification of resistance mechanisms and therapeutic sequences. In this Series paper we aim to provide an overview of the current systemic treatment options for patients with BTC, highlighting disparities in access to innovative treatments and molecular testing across European countries, which lead to inequalities in the possibilities of treating patients with advanced BTC. We also discuss how ongoing European collaborative projects, such as the COST Action Precision-BTC-Network CA22125, supported by COST (European Cooperation in Science and Technology), linked to the European Network for the Study of Cholangiocarcinoma (ENSCCA), can help overcome these disparities and improve the current scenario.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".