Risk of Second Primary Cancer and Death Following a Diagnosis of Nonmelanoma Skin Cancer
Bibliographic record
Abstract
Cancer-free patients diagnosed with a first primary nonmelanoma skin cancer (NMSC) offer an opportunity for studying the risk of a second primary cancer without the confounding effect of systemic treatment. The objective of the study was to estimate the risk of second primary cancer in people with a history of basal cell carcinoma (BCC) or squamous cell carcinoma (SCC) and the risk of dying in cancer patients with a NMSC history. BCC and SCC cases diagnosed between 1956 and 2000 in Manitoba, Canada were followed-up for second primaries (other than NMSC). Standardized incidence and mortality ratios (SIR and SMR) were calculated. Men [SIR, 1.06; 95% confidence interval (95% CI), 1.02-1.10] and women (SIR, 1.07; 95% CI, 1.02-1.12) with a BCC history as well as men (SIR, 1.15; 95% CI, 1.08-1.22) with a SCC history were at greater risk of a second primary cancer. Overall, the increased risk was observed only in the first 4 years following a NMSC, although it remained increased for specific cancer sites. The risk remained higher in all age groups up to 75 years of age. People with a history of BCC (males: SMR, 1.09; 95% CI, 1.04-1.14; females: SMR, 1.24; 95% CI, 1.16-1.32) or SCC (males: SMR, 1.18; 95% CI, 1.09-1.27; females: SMR, 1.55; 95% CI, 1.35-1.79) had a greater risk of death following their second primaries. Even if NMSC patients are at greater risk of a second cancer, it is not recommended to follow them up beyond the generally accepted periodic examination of the skin.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".