Ipilimumab in Treatment-naive and Previously Treated Patients with Metastatic Melanoma
Bibliographic record
Abstract
Ipilimumab is a fully human, monoclonal antibody that blocks cytotoxic T-lymphocyte antigen-4 to potentiate antitumor T-cell responses. In a phase III trial, ipilimumab monotherapy at 3 mg/kg demonstrated an improvement in overall survival (OS) in patients with previously treated, metastatic melanoma. Here, we conducted a retrospective analysis of efficacy and safety data from a phase II clinical trial in which treatment-naive and previously treated patients with metastatic melanoma received ipilimumab at an investigational dose of 10 mg/kg. Patients were randomized 1:1 to receive oral budesonide or placebo, and ipilimumab at 10 mg/kg every 3 weeks for 4 doses, to determine whether prophylactic budesonide affected the rate of grade ≥2 diarrhea. One hundred fifteen patients were randomized and treated: 62 had received prior systemic therapy for metastatic disease and 53 had not. No efficacy endpoint was affected by budesonide therapy, and the efficacy data were therefore pooled for budesonide and placebo subgroups. Median OS was 30.5 months for treatment-naive patients who received ipilimumab, with survival rates of 69.4%, 62.9%, and 56.9% at 12, 18, and 24 months. In previously treated patients who received ipilimumab, median OS was 13.6 months, with survival rates of 50.0%, 37.7%, and 28.5% at 12, 18, and 24 months. There were no meaningful differences in the number of objective responses or rate of grade ≥2 diarrhea between groups. These retrospective analyses are the first to provide survival data for ipilimumab in treatment-naive and previously treated patients within the same clinical 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".