Human prostate cancer risk factors
Bibliographic record
Abstract
Prostate cancer has the highest prevalence of any nonskin cancer in the human body, with similar likelihood of neoplastic foci found within the prostates of men around the world regardless of diet, occupation, lifestyle, or other factors. Essentially all men with circulating androgens will develop microscopic prostate cancer if they live long enough. This review is a contemporary and comprehensive, literature-based analysis of the putative risk factors for human prostate cancer, and the results were presented at a multidisciplinary consensus conference held in Crystal City, Virginia, in the fall of 2002. The objectives were to evaluate known environmental factors and mechanisms of prostatic carcinogenesis and to identify existing data gaps and future research needs. The review is divided into four sections, including 1) epidemiology (endogenous factors [family history, hormones, race, aging and oxidative stress] and exogenous factors [diet, environmental agents, occupation and other factors, including lifestyle factors]); 2) animal and cell culture models for prediction of human risk (rodent models, transgenic models, mouse reconstitution models, severe combined immunodeficiency syndrome mouse models, canine models, xenograft models, and cell culture models); 3) biomarkers in prostate cancer, most of which have been tested only as predictive factors for patient outcome after treatment rather than as risk factors; and 4) genotoxic and nongenotoxic mechanisms of carcinogenesis. The authors conclude that most of the data regarding risk relies, of necessity, on epidemiologic studies, but animal and cell culture models offer promise in confirming some important findings. The current understanding of biomarkers of disease and risk factors is limited. An understanding of the risk factors for prostate cancer has practical importance for public health research and policy, genetic and nutritional education and chemoprevention, and prevention strategies.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".