The childhood cancer registry in Switzerland: methods and results in 2025
Bibliographic record
Abstract
Summary Aims Nationwide registration of childhood cancers in Switzerland began in 1976. With the implementation of the Federal Law on Cancer Registration in 2020, cancer registration became compulsory, and methods were standardized nationwide across childhood and adult cancers. This paper describes the objectives and methods of the Childhood Cancer Registry (ChCR) as of 2025 and presents recent data on incidence, mortality and survival of childhood and adolescent cancers in Switzerland. Methods The ChCR records all primary cancers diagnosed in children and adolescents aged 0–19 years who live in Switzerland. Case reporting is mandatory for physicians, hospitals, and pathology laboratories. Eligible diagnoses include all malignant tumors, tumors of uncertain/unknown behavior, benign central nervous system tumors, histiocytosis, and selected other conditions. Cases are coded primarily according to ICD-10, ICD-O, the International Classification of Childhood Cancer (ICCC), and the Toronto Childhood Cancer Staging Guidelines. The registry collaborates closely with the Swiss Paediatric Oncology Group (SPOG), Cantonal Cancer Registries (CCRs), the National Agency for Cancer Registration (NACR), and the Federal Statistical Office (FSO). We calculated incidence and mortality rates for patients diagnosed between 2014 and 2023 using FSO population statistics and estimated 1-, 5- and 10-year observed survival using the Kaplan-Meier method with the period approach. Results From 1976 to 2023, 12,665 primary cancers diagnosed in individuals aged 0–19 years were registered. Between 2014 and 2023, 2,441 new cases were diagnosed among children (0–14 years) and an estimated 1,214 among adolescents (15–19 years), adjusting for incomplete regional coverage in adolescents before 2020. In children, the most frequent diagnostic groups were CNS tumors (653, 27%), leukemias (641, 26%) and lymphomas (275, 11%), followed by neuroblastoma, soft tissue sarcomas and other carcinomas and melanomas (all 6%), kidney tumors (5%) and bone tumors (4%). In adolescents, the most common diagnoses were lymphomas (287, 24%), carcinomas and melanomas (277, 23%), and CNS tumors (213, 18%), followed by leukemias (12%) and germ cell tumors (10%). Age-standardized annual incidence per million (standardized to the European Standard Population 2013) was 189 (95% CI 182– 197) in children aged 0–14, and 282 (95% CI 265–299) in those aged 15–19. Overall, five-year survival was 89% for children and 90% for adolescents, with variation across ICCC-3 diagnostic groups. Conclusions With mandatory reporting and strong collaboration among national stakeholders, the ChCR has evolved into a comprehensive and reliable data source. Its high completeness and long-term follow-up make it a critical resource for epidemiological and clinical research on childhood and adolescent cancers in Switzerland.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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".