Screening for prostate cancer: History, evidence, controversies and future perspectives toward individualized screening
Bibliographic record
Abstract
Differences in the incidence and mortality rate of prostate cancer between the USA and Japan have been decreasing over time, and were only twofold in 2017. Therefore, countermeasures against prostate cancer could be very important not only in Western countries, but also in developed Asian countries. Screening for prostate cancer in the general population using transrectal ultrasonography, digital rectal examination and/or prostate acid phosphatase began in Japan in the early 1980s, and screening with prostate-specific antigen and digital rectal examination has been widespread in the USA since the late 1980s. Large- and mid-scale randomized controlled trials on screening for prostate cancer began around 1990 in the USA, Canada and Europe. However, most of these studies failed as randomized controlled trials because of high contamination in the control arm, low compliance in the screening arm or insufficient screening setting about screening frequency and/or biopsy indication. The best available level 1 evidence is data from the European Randomized Study of Screening for Prostate Cancer and the Göteborg screening study. However, several non-urological organizations and lay media around the world have mischaracterized the efficacy of prostate-specific antigen screening. To avoid long-term confusion about screening for prostate cancer, leading professional urological organizations, including the Japanese Urological Association, are moving toward the establishment of an optimal screening system that minimizes the drawbacks of overdetection, overtreatment and loss of quality of life due to treatment, and maximizes reductions in the risk of death as a result of prostate cancer and the development of metastatic 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 | 0.052 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".