A meta-analysis of biochemotherapy (BCT) for the treatment of metastatic malignant melanoma (MM)
Bibliographic record
Abstract
7529 Background: Systemic approaches to therapy of metastatic MM include cytotoxic chemotherapy, immunotherapy such as interferon-alpha (IFN) and interleukin-2 (IL-2), and more recently BCT. Methods: A systematic review of the literature regarding BCT for treatment of metastatic MM was conducted using MEDLINE, CANCERLIT, Cochrane Library and Physician Data Query clinical trials databases. Relevant articles and abstracts were selected and reviewed by one member of the MDSG and methodologists. All published reports including abstracts for randomized controlled trials (RCTs) and single-arm phase II trials involving BCT were considered. An estimate of the effect of BCT on overall response rate (ORR), time to progression (TTP) and overall survival (OS) was determined using pooled data from published reports of individual RCTs. Results: Nine RCTs, 8 randomized phase II trials and 39 single-arm phase II trials were identified. Six studies compared chemotherapy alone to chemotherapy plus IL-2 and IFN. In only one study, BCT was superior for ORR (48% vs. 25%, p=0.001) and median survival (11.9 vs. 9.2 months, p=0.06) while a second demonstrated an improved ORR (44% vs. 27%, p=0.071) but a lower median survival (10.7 vs. 15.8 months, p=0.052). The remaining four studies showed no significant differences in ORR, TTP or OS. A pooled meta-analysis demonstrated that BCT was superior to chemotherapy for ORR (relative risk (RR)=1.49, CI 1.21–1.83, p=0.0002), and delayed TTP at six months (RR=0.82, CI 0.72–0.94, p=0.004) but not one-year survival (RR=0.89, CI 0.77–1.03, p=0.13). Therapy was toxic but quality of life did not seem to be impaired. Grade 3 and 4 toxicities were common. Conclusions: BCT is associated with higher ORR compared to standard therapy but does not have a meaningful impact on survival in patients with metastatic MM. Due to the toxicity of BCT, treatment should be restricted to experienced centres. No significant financial relationships to disclose.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.051 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".