Are men on 5α‐reductase inhibitors appropriately referred to urology? A survey of primary care physicians
Bibliographic record
Abstract
Study Type – Therapy (practice pattern survey) Level of Evidence 2b What’s known on the subject? and What does the study add? Benign prostatic hyperplasia is one of the most common urologic conditions encountered by general practitioners. 5‐alpha‐reductase inhibitors are newer drugs used for its treatment. Their use, however, can affect PSA kinetics and potentially mask the early detection of prostate cancer. This study further confirms that most general practitioners prefer to use alpha‐blockers over 5‐alpha‐reductase inhibitors in the management of BPH. Furthermore, it clearly shows that there is a lack of awareness of the effect of these medications on PSA kinetics and, as such, further education among GPs is recommended about these drugs in order to optimize their usage at the primary care level and to avoid delays in cancer detection. OBJECTIVE • To investigate among general practitioners (GPs) their level of awareness and indications for urological consultations in patients treated with 5α‐reductase inhibitors (5ARIs). SUBJECTS AND METHODS • We conducted a survey of GPs in Quebec. • Questions covered GPs’ preferred benign prostatic hyperplasia (BPH) management, knowledge of 5ARIs, their role in prostate cancer prevention, and triggers for urology consultation. RESULTS • Of the surveys mailed, 599 were returned (15.7% response rate). • Therapy with 5ARIs was initiated by GPs in 34.3%, with 20% and 12% preferring 5ARIs alone and combined with an α‐blocker as first‐line therapy for BPH, respectively. • Once on therapy, 74% did not refer to a urologist if the PSA level did not decline after 6–12 months. • Finally, 40.7% would not advocate 5ARI chemoprevention for prostate cancer, regardless of risk reduction. • Findings were not associated with GP gender, experience or geographic location of practice (urban versus rural). CONCLUSIONS • There was a preference amongst GP to use α‐blockers over 5ARIs for BPH and hesitancy to use them in prostate cancer chemoprevention. • There is a lack of awareness of 5ARI effects on PSA kinetics and a reluctance to refer to a urologist. • Further education in Quebec is needed about 5ARIs to optimize their usage and avoid delaying cancer detection.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".