Association between dermatology follow-up and melanoma survival: A population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Guidelines recommend that patients with melanoma undergo dermatologic examination at least annually. Adherence to follow-up and its impact on survival are unclear. OBJECTIVE: To determine the level of adherence to annual dermatologic follow-up in patients with primary cutaneous melanoma, identify predictors for better adherence, and evaluate whether adherence was associated with melanoma-related mortality. METHODS: Retrospective inception cohort analysis of adults with primary invasive melanoma in Ontario, Canada from 2010 to 2013 with follow-up until December 31, 2018. RESULTS: Adherence to dermatologic follow-up was variable with only 28.0% of patients seeing a dermatologist at least annually (median follow-up 5.0 years). Younger age, female sex, higher income, greater access to dermatology care, stage 2/3 melanoma, prior keratinocyte carcinoma, fewer comorbidities, and any outpatient visit in the 12 months prior to melanoma diagnosis were predictors for adherence. Greater adherence to annual dermatology visits was associated with reduced melanoma-specific mortality compared with lower levels of adherence (adjusted hazard ratio 0.64, 95% CI 0.52-0.78). LIMITATIONS: Observational study design and inability to identify skin examinations performed by non-dermatologists. CONCLUSION: Adherence to annual dermatology visits after melanoma diagnosis was low. Greater adherence may promote better patient survival but warrants confirmation in further research including randomized trials.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".