The economic burden of occupational non-melanoma skin cancer due to solar radiation
Bibliographic record
Abstract
Solar ultraviolet (UV) radiation is the second most prevalent carcinogenic exposure in Canada and is similarly important in other countries with large Caucasian populations. The objective of this article was to estimate the economic burden associated with newly diagnosed non-melanoma skin cancers (NMSCs) attributable to occupational solar radiation exposure. Key cost categories considered were direct costs (healthcare costs, out-of-pocket costs (OOPCs), and informal caregiver costs); indirect costs (productivity/output costs and home production costs); and intangible costs (monetary value of the loss of health-related quality of life (HRQoL)). To generate the burden estimates, we used secondary data from multiple sources applied to computational methods developed from an extensive review of the literature. An estimated 2,846 (5.3%) of the 53,696 newly diagnosed cases of basal cell carcinoma (BCC) and 1,710 (9.2%) of the 18,549 newly diagnosed cases of squamous cell carcinoma (SCC) in 2011 in Canada were attributable to occupational solar radiation exposure. The combined total for direct and indirect costs of occupational NMSC cases is $28.9 million ($15.9 million for BCC and $13.0 million for SCC), and for intangible costs is $5.7 million ($0.6 million for BCC and $5.1 million for SCC). On a per-case basis, the total costs are $5,670 for BCC and $10,555 for SCC. The higher per-case cost for SCC is largely a result of a lower survival rate, and hence higher indirect and intangible costs. Our estimates can be used to raise awareness of occupational solar UV exposure as an important causal factor in NMSCs and can highlight the importance of occupational BCC and SCC among other occupational cancers.
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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 | 0.001 |
| 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) | 0.002 | 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".