130 Relationship between Testosterone and Prostatitis: Results from the REDUCE study
Bibliographic record
Abstract
While some prior studies have have suggested a relationship between hypogonadism and the risk prostatitis, other studies have not confirmed this association. Therefore, we sought to determine whether total testosterone (TT) and dihydrotestosterone (DHT) levels are associated with prostatitis and chronic prostatitis symptom index scores (CPSI). We examined 5,315 men from the REDUCE trial who were randomized to receive either dutasteride or placebo for prostate cancer prevention. Serum TT and DHT, CPSI questionnaires and diagnosis of prostatitis were obtained at baseline. CP/CPPS was defined as a positive response to CPSI question 1a and/or question 2b, and a total pain subscore of at least 4. Men were sub-grouped into quintiles based on TT in nmol/L (<10.15, 10.15-13.14, 13.15-16.09, 16.10-20.35, and >20.35) and DHT levels in nmol/L (<0.77, 0.77-1.05, 1.06-1.35, 1.36-1.80, and >1.8). The association of serum TT and DHT levels with baseline characteristics including CPSI scores was analyzed with Kruskal-Wallis and chi-squared tests. The association of serum TT and DHT levels with prostatitis was analyzed with Kruskal-Wallis test and logistic regression adjusting for age, race, region, BMI, DRE, prostate volume, PSA, history of diabetes mellitus, sexual activity and treatment arm.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".