Population-based assessment of sentinel lymph node biopsy in the management of cutaneous melanoma
Bibliographic record
Abstract
Background: Sentinel lymph node biopsy (SLNB) for melanoma plays a central role in determining prognosis and guiding treatment and surveillance strategies. Despite widely published guidelines for SLNB, variation exists in its use. We aimed to determine the frequency of and predictive factors for SLNB in patients with clinically node-negative melanoma in British Columbia. Methods: A retrospective review was performed of patients with clinically node-negative melanoma diagnosed between January 2015 and December 2017. Patients included had a Breslow depth greater than 0.75 mm or a Breslow depth less than or equal to 0.75 mm with ulceration, or a mitotic rate greater than or equal to 1/mm2. SLNB was considered to be indicated for clinical stages IB to IIC (American Joint Committee on Cancer’s AJCC Cancer Staging Manual, seventh edition). Results: A total of 759 patients were included. SLNB was performed in 54.8% (363/662) of patients when indicated. SLNB was more likely to be performed for tumours with a Breslow depth greater than 1.0 mm or a mitotic rate greater than or equal to 1/mm2. SLNB was less likely to be performed in patients older than 75 years and with a nonextremity tumour location. Compliance with SLNB guidelines decreased distant recurrence but did not significantly affect regional recurrence, nor did it have a significant impact on overall survival among patients aged 75 years and younger. Conclusion: SLNB is being underutilized in British Columbia. These results are concerning and highly relevant given the rapidly evolving field of adjuvant systemic therapy for high-risk patients and the increased proportion of patients who should be considered for SLNB on the basis of the eighth edition of the AJCC Cancer Staging Manual and current guidelines. Efforts should be made to increase the use of SLNB in appropriate 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".