The association of statin subgroups with lower urinary tract symptoms following a prostate biopsy
Bibliographic record
Abstract
INTRODUCTION: This was a secondary analysis aiming to assess whether hydrophilic or hydrophobic statins have a differential effect on urinary retention (UR) and lower urinary tract symptoms (LUTS) in men following a prostate biopsy (PBx), who were at risk for prostate cancer development. METHODS: This was a population-based cohort study with data incorporated from the Institute for Clinical and Evaluative Sciences database to identify all Ontarian men aged 66 and above with a history of a single negative PBx between 1994 and 2016, with no drug prescription history of any of several putative chemo-preventative medications (statins, proton pump inhibitors, five-alpha-reductase inhibitors, and alpha-blockers). Multivariable Cox regression models with time-dependent covariates were used to assess the association of hydrophilic and hydrophobic statins with UR and LUTS within 30 days of a PBx. All models were adjusted for other known putative chemopreventive medications, age, rurality, pharmacologically treated diabetes, comorbidity score, and study inclusion year. RESULTS: Overall, 21 512 men were included, with a median followup time of 9.4 years (interquartile range [IQR] 5.4-13.4 years). Hydrophobic and hydrophilic statins were initiated by 30.7% and 19.6% of men, respectively, after the first negative PBx. UR and LUTS were experienced by 2.2% and 10% of men, respectively. Cox models demonstrated hydrophilic statins were associated with a lower risk of UR (hazard ratio [HR] 0.56, 95% confidence interval [CI] 0.38-0.83, p=0.0038) and LUTS (HR 0.86, 95% CI 0.76-0.98, p=0.022), while no such association was shown for hydrophobic statins. CONCLUSIONS: Initiation of hydrophilic statins in men older than 66 appears to be inversely associated with the risk of UR and LUTS within 30 days of a PBx.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".