Conventional versus Reduced-Frequency Follow-Up in Early-Stage Melanoma Survivors: A Systematic Review with Meta-Analysis
Bibliographic record
Abstract
To date, there have been multiple studies and clinical guidelines or recommendations for complex management of melanoma patients. The most controversial subjects included the frequency of follow-up. This study provides a coherent and comprehensive comparison of conventional vs. reduced-frequency follow-up strategies for early-stage melanoma patients. The value of our study consists in the precise analysis of a large collection of articles and the selection of the most valuable works in relation to the topic according to rigorous criteria, which allowed for a thorough study of the topic. The search strategy was implemented using multiple databases. The inclusion criteria were randomized clinical trial or cohort studies that compared the outcomes of a conventional follow-up schedule versus a reduced-frequency follow-up schedule for patients diagnosed with melanoma. In this study, authors analyzed recurrence and 3-year survival. Meta-analysis of outcomes presented by Deckers et al. and Moncrieff et. al. did not reveal a significant difference favoring one of the groups (OR 1.14; 95%CI: 0.65–2.00; p = 0.64). The meta-analysis of 3-year overall survival included two studies. The statistical analysis showed no significant difference in favor of the conventional follow-up group. (OR 1.10; 95%CI: 0.57–2.11; p = 0.79). Our meta-analysis shows that there is no advantage in a conventional follow-up regimen over a reduced-frequency regimen in early-stage melanoma patients.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.041 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".