Current progress in systemic therapy for biliary tract cancers
Bibliographic record
Abstract
BACKGROUND: Biliary tract cancers (BTCs) are heterogeneous cancers that include cancers of the bile duct and gallbladder. Although they are relatively uncommon, most patients with BTC are diagnosed at advanced-stage disease with high mortality rates. Recently, systemic therapy options for patients with BTC have evolved. This paper reviews recent advancements in systemic therapy and the results of key clinical trials in BTC. METHODS: A literature search in PubMed and Google Scholar was performed using keywords related to BTC and systemic therapy. Studies that were presented in major international cancer research conferences were also included. RESULTS: The evidence shows that adjuvant capecitabine has been associated with a lower relapse rate in early-stage BTC. In unselected patients with advanced BTC, combination chemotherapy is a standard treatment option. However, with a better understanding of the molecular profile of BTC, there has been a shift toward targeted agents in BTC that have shown promising responses. The evolving data also support the evolving role of immunotherapy in patients with deficient DNA mismatch repair or PD-L1-positive BTC. DISCUSSION: Systemic treatment options for BTC have improved. The future identification of new targets, novel compounds, and predictive markers is a key step toward the use of personalized medicine in BTC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".