Incidence of Nonmelanoma Skin Cancer in New Brunswick, Canada, 1992 to 2001
Bibliographic record
Abstract
BACKGROUND: Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), collectively referred to as nonmelanoma skin cancer (NMSC), cause significant morbidity and generate a substantial cost to the health care system. Canadian data on the incidence of NMSC are lacking. OBJECTIVE: To study the incidence and characteristics of NMSC in New Brunswick, Canada (population 729,498 people in 2001), by using the Provincial Cancer Registry. METHOD: Data were obtained from 1992 to 2001 from the New Brunswick Provincial Cancer Registry, to which reporting of all cancers is mandatory. Multiple tumors of a given histologic type are recorded only once in the registry per individual per lifetime. A descriptive analysis of incidence rates of BCC and invasive SCC of the skin was performed in relation to gender, age, and anatomic location. The main outcome measures were the age- and sex-specific incidence rates of BCC and SCC. Age standardization was performed using the Canadian, US, and world standard populations. RESULTS: When adjusted to the world standard population, the age-standardized incidence rates (ASIRs) per 100,000 population for BCC from 1992 through 2001 were 87 for males and 68 for females. For invasive SCC, the ASIRs per 100,000 population were 34 for males and 16 for females. There was an increasing incidence trend for both BCC and invasive SCC over the 10-year study period, with minimal change in the incidence of SCC in women. The overall ratio of BCC to invasive SCC in the population was 2.8 to 1. The approximate lifetime probabilities of developing BCC and invasive SCC were 13% and 5%, respectively. CONCLUSIONS: The incidence of NMSC in the province of New Brunswick is similar to that reported from 1973 through 1987 in the province of British Columbia, higher than those reported in most parts of Europe, and lower than all published rates in the United States and Australia. Owing to the inability of the registry to account for tumor multiplicity, the actual annual number of all NMSC lesions in this population is likely much higher.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".