Clinical whole‐body skin examination reduces the incidence of thick melanomas
Bibliographic record
Abstract
Survival from melanoma is strongly related to tumour thickness, thus earlier diagnosis has the potential to reduce mortality from this disease. However, in the absence of conclusive evidence that clinical skin examination reduces mortality, evidence-based assessments do not recommend population screening. We aimed to assess whether clinical whole-body skin examination is associated with a reduced incidence of thick melanoma and also whether screening is associated with an increased incidence of thin lesions (possible overdiagnosis). We conducted a population-based case-control study of all Queensland residents aged 20-75 years with a histologically confirmed first primary invasive cutaneous melanoma diagnosed between January 2000 and December 2003. Telephone interviews were completed by 3,762 eligible cases (78.0%) and 3,824 eligible controls (50.4%). Whole-body clinical skin examination in the three years before diagnosis was associated with a 14% lower risk of being diagnosed with a thick melanoma (>0.75 mm) (OR = 0.86, 95% CI = 0.75, 0.98). Risk decreased for melanomas of increasing thickness: the risk of being diagnosed with a melanoma 0.76-1.49 mm was reduced by 7% (OR = 0.93, 95% CI 0.79, 1.10), by 17% for melanomas 1.50-2.99 mm (OR = 0.83, 95% CI = 0.65, 1.05) and by 40% for melanomas > or =3 mm (OR = 0.60, 95% CI = 0.43, 0.83). Screening was associated with a 38% higher risk of being diagnosed with a thin invasive melanoma (< or =0.75 mm) (OR = 1.38, 95% CI = 1.22, 1.56). This is the strongest evidence to date that whole-body clinical skin examination reduces the incidence of thick melanoma. Because survival from melanoma is strongly related to tumour thickness, these results suggest that screening would reduce melanoma mortality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".