Immune Toxicities and Long Remission Duration after Ipilimumab Therapy for Metastatic Melanoma: Two Illustrative Cases
Bibliographic record
Abstract
New antitumour immunotherapy strategies for stage iv metastatic melanoma include ipilimumab, a monoclonal antibody against ctla-4. Patterns of response with cancer immunotherapy differ from those with cytotoxic chemotherapy. We present two cases of long-duration immune-related responses with ipilimumab in a phase ii trial. A 66-year-old woman with multiple lung metastases from a scalp primary melanoma received 4 doses of ipilimumab with mixed clinical response. However, after the first maintenance dose, she developed severe ileitis and colitis that responded to steroid therapy. Four months later, she had surgery and radiotherapy for a single brain metastasis. Radiologically, stable disease continued for 36 months after the last ipilimumab dose, and partial response for 5 years after ipilimumab start. A 54-year-old man with cervical lymph node and pulmonary metastases from a scalp primary melanoma received three induction doses of ipilimumab. He developed alopecia universalis and widespread vitiligo, and he discontinued treatment because of hypophysitis. Maintenance ipilimumab was started after a 6-month drug-free interval, with no further adverse events over 15 cycles. At week 12, computed tomography imaging showed no lung metastases and partial response in a supraclavicular lymph node, which was positive on positron-emission tomography. Five years after starting ipilimumab, the supraclavicular lymph node was calcified, and the patient was off steroid therapy and asymptomatic. The foregoing patients demonstrate long responses with ipilimumab (in association with delayed severe colitis in one case, and a constellation of immune events, including alopecia universalis in another). Re-treatment with ipilimumab may be possible even after significant immune adverse events.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".