High regional variation in prostate surgery for benign prostatic hyperplasia in Switzerland
Bibliographic record
Abstract
BACKGROUND: Among various treatment options for benign prostatic hyperplasia (BPH), surgical therapy is the most invasive. As Switzerland has the highest transurethral prostatectomy rate among OECD countries, we assessed the regional variation in prostate surgery for BPH and explored potential determinants of variation. METHODS: We conducted a population-based analysis using discharge data for men aged ≥40 years with transurethral or simple prostatectomy from all Swiss hospitals during 2013-2018. After excluding patients with genitourinary/prostate cancer, we derived hospital service areas (HSAs) by analyzing patient flows. We calculated age-standardized mean procedure rates and variation indices (extremal quotient [EQ] and systematic component of variation [SCV]). We estimated the reduction in variance across HSAs of prostatectomy rates in multilevel regression models, with incremental adjustment for age, regional cultural and socioeconomic factors, disease burden, density of urologists, and the time since urologists' graduation. RESULTS: Overall, 44,253 prostatectomies (42,710 transurethral and 1543 simple) from 44 HSAs were analyzed. The mean age-standardized prostate surgery rate was 314 (range 166-500) per 100,000 men aged ≥40 years per year. The EQ was 3.01 and the SCV 5.53, indicating a high regional variation. In multivariate models, men aged 75-79 years had an 11.6-fold higher prostatectomy rate than those aged 50-54 years. French/Italian language areas had a 21% lower rate than Swiss German speaking areas. Socioeconomic factors, disease burden, and density of urologist/time since graduation were not associated with prostatectomy rates. After full adjustment, 80% of the variance in prostate surgery across HSAs remained unexplained. CONCLUSION: We found a remarkably high regional variation in prostate surgery rates for BPH within Switzerland.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".