The Society for Immunotherapy of Cancer consensus statement on tumour immunotherapy for the treatment of cutaneous melanoma
Bibliographic record
Abstract
Immunotherapy is associated with durable clinical benefit in patients with melanoma. The goal of this article is to provide evidence-based consensus recommendations for the use of immunotherapy in the clinical management of patients with high-risk and advanced-stage melanoma in the USA. To achieve this goal, the Society for Immunotherapy of Cancer sponsored a panel of melanoma experts--including physicians, nurses, and patient advocates--to develop a consensus for the clinical application of tumour immunotherapy for patients with melanoma. The Institute of Medicine clinical practice guidelines were used as a basis for this consensus development. A systematic literature search was performed for high-impact studies in English between 1992 and 2012 and was supplemented as appropriate by the panel. This consensus report focuses on issues related to patient selection, toxicity management, clinical end points and sequencing or combination of therapy. The literature review and consensus panel voting and discussion were used to generate recommendations for the use of immunotherapy in patients with melanoma, and to assess and rate the strength of the supporting evidence. From the peer-reviewed literature the consensus panel identified a role for interferon-α2b, pegylated-interferon-α2b, interleukin-2 (IL-2) and ipilimumab in the clinical management of melanoma. Expert recommendations for how to incorporate these agents into the therapeutic approach to melanoma are provided in this consensus statement. Tumour immunotherapy is a useful therapeutic strategy in the management of patients with melanoma and evidence-based consensus recommendations for clinical integration are provided and will be updated as warranted.
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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 | 0.051 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.006 | 0.008 |
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".