Contemporary Neoadjuvant Therapies for High-Risk Melanoma: A Systematic Review
Bibliographic record
Abstract
Despite advances in adjuvant immuno- and targeted therapies, the risk of relapse for stage III melanoma remains high. With 43 active entries on clinicaltrials.gov (8 July 2020), there is a surge of interest in the role of contemporary therapies in the neoadjuvant setting. We conducted a systematic review of trials performed in the last decade evaluating neoadjuvant targeted, immuno- or intralesional therapy for resectable stage III or IV melanoma. Database searches of Medline, Embase, and the Cochrane Central Register of Controlled Trials were conducted from inception to 13 February 2020. Two reviewers assessed titles, abstracts, and full texts. Trials investigating contemporary neoadjuvant therapies in high-risk melanoma were included. Eight phase II trials (4 randomized and 4 single-arm) involving 450 patients reported on neoadjuvant anti-BRAF/MEK targeted therapy (3), anti-PD-1/CTLA-4 immunotherapy (3), and intralesional therapy (2). The safest and most efficacious regimens were dabrafenib/trametinib and combination ipilimumab (1 mg/kg) + nivolumab (3 mg/kg). Pathologic complete response (pCR) and adverse events were comparable. Ipilimumab + nivolumab exhibited longer RFS. Contemporary neoadjuvant therapies are not only safe, but also demonstrate remarkable pCR and RFS-outcomes which are regarded as meaningful surrogates for long-term survival. Studies defining predictors of pCR, its correlation with oncologic outcomes, and phase III trials comparing neoadjuvant therapy to standard of care will be crucial.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".