Patterns and trends in prostate cancer incidence, survival, prevalence and mortality. Part I: international comparisons
Bibliographic record
Abstract
The international patterns and trends in prostate cancer incidence, survival, prevalence and mortality were examined. Age-standardized incidence and death rates among men in a variety of countries worldwide were obtained from various sources, survival rates from European sources and elsewhere, and prevalence estimates from the EUROPREVAL study. Results from many published studies were summarized. The incidence of prostate cancer varies widely around the world, with by far the highest rates in the USA and Canada. There has been a gradual increase in the incidence of prostate cancer since the 1960s in many countries and in most continents; there were large increases in the late 1980s and early 1990s in the USA, but increases have also occurred in countries with comparatively low incidence, e.g. India. Survival from prostate cancer improved during the 1970s and 1980s; further increases in the 1990s may be largely a result of earlier diagnosis. There were wide differences in survival across Europe, with rates in the UK well below the average, but all European rates were far below those in the USA. There was wide variation in the prevalence of prostate cancer in Europe; in some countries with high incidence and high life-expectancy, prostate cancers formed approximately 15% of all prevalent cancers in men. Mortality from prostate cancer has also increased in many countries, but to a lesser extent than incidence; this is consistent with the observed trends in survival. Mortality decreased slightly in the mid to late 1990s in several countries, including the USA, Canada, England, France and Austria. Part of the apparent increases in the incidence of prostate cancer has been associated with diagnostic artefacts (particularly detecting preclinical tumours through the increased use of transurethral resection) which may also have had an effect on death certification through the incorrect attribution of prostate cancer as the underlying cause of death. However, the greatest effect on the registration of new cases of prostate cancer has been the increased availability of prostate specific antigen testing during the early- to mid-1990s. Possibly, in addition to the effect of attribution bias, the earlier diagnosis of prostate cancers has contributed to the recent slight decreases in mortality. However, this is unlikely to account for much of the reduction, given the slow development of the disease from onset to death. Changes in disease management are probably more important. There are many strong arguments against introducing population-based screening for prostate cancer.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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, 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".