A randomized phase 2 trial of nivolumab, gemcitabine, and cisplatin or nivolumab and ipilimumab in previously untreated advanced biliary cancer: <scp>BilT</scp>‐01
Bibliographic record
Abstract
BACKGROUND: Gemcitabine and cisplatin has limited benefit as treatment for advanced biliary tract cancer (BTC). The addition of an anti-programmed death receptor (PD-1)/PD-ligand (L1) antibody to either systemic chemotherapy or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA4) antibody has shown benefit in multiple solid tumors. METHODS: In this phase 2 trial, patients 18 years or older with advanced BTC without prior systemic therapy and Eastern Cooperative Oncology Group Performance Status 0-1 were randomized across six academic centers. Patients in Arm A received nivolumab (360 mg) on day 1 along with gemcitabine and cisplatin on days 1 and 8 every 3 weeks for 6 months followed by nivolumab (240 mg) every 2 weeks. Patients in Arm B received nivolumab (240 mg) every 2 weeks and ipilimumab (1 mg/kg) every 6 weeks. RESULTS: Of 75 randomized patients, 68 received therapy (Arm A = 35, Arm B = 33); 51.5% women with a median age of 62.5 years. The observed primary outcome of 6-month progression-free survival (PFS) rates in the evaluable population was 59.4% in Arm A and 21.2% in Arm B. The median PFS and overall survival (OS) in Arm A were 6.6 and 10.6 months, and in Arm B 3.9 and 8.2 months, respectively, in patients who received any treatment. The most common treatment-related grade 3 or higher hematologic adverse event was neutropenia in 34.3% (Arm A) and nonhematologic adverse events were fatigue (8.6% Arm A) and elevated transaminases (9.1% Arm B). CONCLUSIONS: The addition of nivolumab to chemotherapy or ipilimumab did not improve 6-month PFS. Although median OS was less than 12 months in both arms, the high OS rate at 2 years in Arm A suggests benefit in a small cohort of patients.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".