Ethnic differences in prostate-specific antigen levels in men without prostate cancer: a systematic review
Bibliographic record
Abstract
INTRODUCTION: Black men are twice as likely to be diagnosed with prostate cancer than White men. Raised prostate-specific antigen (PSA) levels can indicate an increased risk of prostate cancer, however it is not known whether PSA levels differ for men of different ethnic groups. METHODS: PubMed and Embase were searched to identify studies that reported levels of PSA for men of at least two ethnic groups without a prostate cancer diagnosis or symptoms suggestive of prostate cancer. An adaptation of the Newcastle-Ottawa scale was used to assess risk of bias and study quality. Findings were stratified into the following broad ethnic groups: White, Black, Asian, Hispanic, and Other. Data were analysed in a narrative synthesis due to the heterogeneity of reported PSA measures and methods in the included studies. RESULTS: A total of 654 197 males from 13 studies were included. By ethnicity, this included 536 201 White (82%), 38 287 Black (6%), 38 232 Asian (6%), 18 029 Pacific Island (3%), 13 614 Maori (2%), 8 885 Hispanic (1%), and 949 Other (<1%) men aged ≥40 years old. Black men had higher PSA levels than White men, and Hispanic men had similar levels to White men and lower levels than Black men. CONCLUSIONS: Black men without prostate cancer have higher PSA levels than White or Hispanic men, which reflects the higher rates of prostate cancer diagnosis in Black men. Despite that, the diagnostic accuracy of PSA for prostate cancer for men of different ethnic groups is unknown, and current guidance for PSA test interpretation does not account for ethnicity. Future research needs to determine whether Black men are diagnosed with similar rates of clinically significant prostate cancer to White men, or whether raised PSA levels are contributing to overdiagnosis of prostate cancer in Black men.
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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 | 0.007 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".