Vertical Growth Phase as a Prognostic Factor for Sentinel Lymph Node Positivity in Thin Melanomas: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The 2010 American Joint Committee on Cancer guidelines recommended consideration of sentinel lymph node biopsy for thin melanoma (Breslow thickness <1.0 mm) with aggressive pathologic features such as ulceration and/or high mitotic rate. The therapeutic benefit of biopsy-based treatment remains controversial. The authors conducted a meta-analysis to estimate the risk and outcomes of sentinel lymph node positivity in thin melanoma, and examined established and potential novel predictors of positivity. METHODS: Three databases were searched by two independent reviewers for sentinel lymph node positivity in patients with thin melanoma. Study heterogeneity, publication bias, and quality were assessed. Data collected included age, sex, Breslow thickness, mitotic rate, ulceration, regression, Clark level, tumor-infiltrating lymphocytes, and vertical growth phase. Positivity was estimated using a random effects model. Association of positivity and clinicopathologic features was investigated using meta-regression. RESULTS: Ninety-three studies were identified representing 35,276 patients with thin melanoma who underwent sentinel lymph node biopsy. Of these patients, 952 had a positive sentinel lymph node biopsy, for an event rate of 5.1 percent (95 percent CI, 4.1 to 6.3 percent). Significant associations were identified between positivity and Breslow thickness greater than 0.75 mm but less than 1.0 mm, mitotic rate, ulceration, and Clark level greater than IV. Seven studies reported on vertical growth phase, which was strongly associated with positivity (OR, 4.3; 95 percent CI, 2.5 to 7.7). CONCLUSIONS: To date, this is the largest meta-analysis to examine predictors of sentinel lymph node biopsy positivity in patients with thin melanoma. Vertical growth phase had a strong association with biopsy positivity, providing support for its inclusion in standardized pathologic reporting.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.031 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".