Empiric antibiotics for an elevated prostate‐specific antigen ( <scp>PSA</scp> ) level: a randomised, prospective, controlled multi‐institutional trial
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of empiric antibiotics on men with an elevated prostate-specific antigen (PSA) level. SUBJECTS/PATIENTS AND METHODS: Men of any age with a PSA level of >2.5 ng/mL and normal digital rectal examination undergoing their first prostate biopsy were recruited from five medical centres. Patients with previous biopsy, prostate cancer, urinary tract infection (UTI) or prostatitis within the prior year, antibiotic use within 1 month, 5α-reductase inhibitor use, allergy to fluoroquinolones or clinical suspicion of UTI were excluded. Men were randomised to 2 weeks of ciprofloxacin or no antibiotic. A PSA measurement was obtained 21-45 days after randomisation immediately before prostate biopsy. The primary endpoint was the change in PSA level between baseline and immediately before biopsy. RESULTS: Complete data were available for 77 men with a mean (interquartile range) age of 60.6 (53-66) years. In the control group of men not receiving antibiotic (39 men), the mean baseline and pre-biopsy PSA levels were 6.5 and 6.9 ng/mL, respectively (P = 0.8). In men receiving ciprofloxacin (38 men), the mean baseline PSA level was 7.6 ng/mL and after 2 weeks of ciprofloxacin was 8.5 ng/mL (P = 0.7). Compared with controls not receiving antibiotic, use of ciprofloxacin was not associated with a statistically significant change in PSA level (P = 0.33). Prostate cancer was detected in 36 (47%) men, 23 (59%) in the control group and 13 (34%) in the antibiotic group (P = 0.04). Detection rates were not significantly associated with the change in PSA level between baseline and biopsy. The primary limitation of the study is early stoppage due to an interim futility analysis and poor accrual. CONCLUSION: Despite not meeting the target accrual goal, empiric use of antibiotics for asymptomatic men with an elevated PSA level does not appear to be of clinical benefit.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".