Melanoma patterns of care in Ontario: A call for a strategic alignment of multidisciplinary care
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Variability in melanoma management has prompted concerns about equitable and timely treatment. We investigated patterns of melanoma diagnosis and treatment using population-level data. METHODS: Patients with invasive cutaneous melanoma were identified retrospectively from the Ontario Cancer Registry (2003-2012) and deterministically linked with administrative databases to identify incidence, disease characteristics, geographic origin, and multimodal treatment within a year of diagnosis. Melanoma treatment was categorized as inadequate or adequate based on multidisciplinary clinical algorithms. Multivariable logistic regression was used to model factors associated with treatment adequacy. RESULTS: From 2003 to 2012, 22 918 patients with invasive melanoma were identified with annual age/sex standardized incidence rates of 11.7-14.3/100 000 for females and 13.4-15.9/100 000 for males. Melanoma occurred at median age of 62 and primarily on extremities (43.9%). Within 1 year after diagnosis, 86.7% of patients received surgery as primary therapy. A total of 2312 (10.6%) patients received inadequate or no treatment after diagnosis. Receiving adequate treatment was associated with consultation with dermatology (OR 1.92, CI 1.71-2.14), plastic surgery (OR 4.80, CI 4.32-5.34), or general surgery (OR 2.15, CI 1.94-2.38). CONCLUSIONS: Significant variation exists in melanoma management and nearly one in nine patients is inadequately treated. Referral to sub-specialized providers is critical for ensuring appropriate care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".