Determining patient preferences in the treatment of medication‐refractory overactive bladder
Bibliographic record
Abstract
INTRODUCTION: Overactive bladder (OAB) is often suboptimally addressed by behavioral or pharmacological treatments. Less than 15% of patients choose to pursue advanced OAB therapy (sacral nerve stimulation [SNS], percutaneous tibial nerve stimulation [PTNS], and bladder onabotulinum toxin type-A [BTX-A]). We seek to better understand which factors are most important to patients when choosing a third-line therapy. METHODS/MATERIALS: We developed a conjoint analysis survey that included five attributes of the third-line options for OAB (SNS, PTNS, and BTX-A). We administered the survey to new patients with urinary incontinence at two institutions. A hierarchical Bayes random effects regression analysis was used to determine the relative importance of the attributes. A choice simulator was used to model which third-line treatment options patients preferred. We followed patients to see if they pursued their predicted treatment. RESULTS: A total of 108 patients completed the study of whom 89% were women. There was representation from all age groups. The most important attributes of decision-making were the frequency of future procedures, the risk of catheterization, and the need for a device. On market simulation, SNS was the preferred treatment option (47%), followed by PTNS (29%) and BTX-A (14%). Only 10% of patients did not find any treatment option acceptable. CONCLUSIONS: Frequent follow-up, risk of catheterization, and the need for a device were the most important attributes when making a decision on third-line OAB therapy. On market simulation, SNS is the preferred treatment for all age groups though the ultimate choice in third-line therapy may be affected by external factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".