Melanoma nodal management in Ontario following ASCO/SSO guidelines.
Bibliographic record
Abstract
e21054 Background:Methods:Results: Conclusions:The American Society of Clinical Oncology and Society of Surgical Oncology (ASCO/SSO) published a joint guideline in 2012 regarding indications for sentinel lymph node biopsy (SLNB) in cutaneous melanoma. The guideline supported completion lymph node dissection (CLND) for all patients with a positive SLNB. We examined the rates and predictors of SLNB and CLND for melanoma patients in Ontario (population 13.6 million) following guideline publication. Methods: We used the Ontario Cancer Registry (OCR) to identify cutaneous melanoma patients diagnosed in 2013. Patient records were linked to prospectively maintained health administrative databases to obtain details for each patient including surgical procedures. Results: We identified 3298 melanoma patients from Ontario in 2013 of which 1,973 (59.8%) could be analyzed. The majority, 1,227 (62.2%) had a local excision alone, while 746 (37.8%) had a SLNB. SLNB was performed on T1, T2, T3 and T4 primary melanomas in 13.9%, 67.8%, 62.6% and 47.2% of cases respectively. Receipt of a SLNB was positively associated with a younger age (< 80), higher T stage, and non-head and neck primary in multivariate analysis. Of the patients who received a SLNB 136 (18.2%) were found to be node positive. A CLND was performed in 82 (60.3%) of these patients. Conclusions: In Ontario only two-thirds of intermediate thickness melanomas (T2, T3) received a SLNB as recommended by the ASCO/SSO guidelines. Utilization was lower for head and neck patients and higher for younger (< 80 years) patients. Use of CLND for positive SLNB was also low relative to the guidelines.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.011 | 0.001 |
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".