Cumulative incidence and disease-specific survival of metastatic cutaneous squamous cell carcinoma: A nationwide cancer registry study
Bibliographic record
Abstract
BACKGROUND: Cutaneous squamous cell carcinoma (cSCC) represents the most serious form of keratinocyte cancers because of its metastatic potential. Studies on nationwide incidence and disease-specific survival rates of metastatic cSCC (mcSCC) are lacking. OBJECTIVE: To investigate the cumulative incidence and disease-specific survival of patients with mcSCC in the Dutch population and assess patient-based risk factors. METHODS: We conducted a nationwide cancer registry study including all patients with the first cSCC in 2007 or 2008, using data from the Netherlands Cancer Registry, the nationwide network and registry of histopathology and cytopathology, and Statistics Netherlands. Cumulative incidence and Kaplan-Meier curves were calculated, and time-dependent Cox proportional hazards regression analyses were used. RESULTS: Of the 11,137 patients, metastases developed in 1.9% (n = 217). The median time to metastasis was 1.5 years (interquartile range 0.6-3.8 years). The risk factors were age (adjusted hazard ratio [aHR] 1.03, 95% CI 1.02-1.05), male sex (aHR 1.7, 95% CI 1.3-2.3), and immunosuppression (aHR [organ transplant recipient] 5.0, 95% CI 2.5-10.0; aHR [hematologic malignancy] 2.7, 95% CI 1.6-4.6). The 5-year disease-specific survival for patients with mcSCC was 79.1%. LIMITATIONS: Only histopathologically confirmed mcSCCs were included. CONCLUSION: About 2% of cSCCs metastasize, with higher risk for men, increasing age, and immunocompromised patients. Disease-specific survival for patients with mcSCC is high.
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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 | 0.000 | 0.001 |
| 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".