Progress in survival in renal cell carcinoma through 50 years evaluated in Finland and Sweden
Bibliographic record
Abstract
Global survival studies have shown favorable development in renal cell carcinoma (RCC) treatment but few studies have considered extended periods or covered populations for which medical care is essentially free of charge. We analyzed RCC survival in Finland and Sweden over a 50-year period (1967-2016) using data from the NORDCAN database provided by the local cancer registries. While the health care systems are largely similar in the two countries, the economic resources have been stronger in Sweden. In addition to the standard 1- and 5-year relative survival rates, we calculated the difference between these as a measure of how well survival was maintained between years 1 and 5. Relative 1- year survival rates increased almost linearly in both countries and reached 90% in Sweden and 80% in Finland. Although 5-year survival also developed favorably the difference between 1- and 5-year survival rates did not improve in Sweden suggesting that the gains in 5-year survival were entirely due to gains in 1-year survival. In Finland there was a gain in survival between years 1 and 5, but the gain in 1-years survival was the main contributor to the favorable 5-year survival. Age group specific analysis showed large survival differences, particularly among women. Towards the end of the follow-up period the differences narrowed but the disadvantage of the old patients remained in 5-year survival. The limitations of the study were lack of information on performed treatment and clinical stage in the NORDCAN database. In conclusion, the available data suggest that earlier diagnosis and surgical treatment of RCC have been the main driver of the favorable change in survival during the past 50 years. The main challenges are to reduce the age-specific survival gaps, particularly among women, and push survival gains past year 1.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".