Real‐world onabotulinumtoxinA treatment patterns in patients with overactive bladder
Bibliographic record
Abstract
PURPOSE: Utilization patterns of third-line onabotulinumtoxinA for overactive bladder (OAB) symptoms-including discontinuation and use of other therapeutic options during or after treatment-are not well understood. This retrospective analysis of administrative claims was designed to characterize the unmet need for OAB treatment. MATERIALS AND METHODS: A retrospective claims analysis of Optum's deidentified Clinformatics® Data Mart Database (2009-2021) was performed among patients with diagnosis of OAB newly starting onabotulinumtoxinA injection (2015-2017). Study measures were evaluated during an 18-month pretreatment baseline and over a minimum of 36 months of follow-up. These included number of injections, days between injections, other measures of onabotulinumtoxinA utilization, use of second-line pharmacologic treatments, use of device and surgical treatment options, and complications. RESULTS: Of 2505 eligible patients, 535 (21.4%; 66.8 ± 13.3 y, 87.3% females) continued onabotulinumtoxinA throughout the study. The remaining 1970 (78.6%; 71.4 ± 11.6 y, 79.1% females) were considered discontinuers. Of continuers, 57% received ≥5 treatments. Of discontinuers, 84% received ≤2 treatments. Anticholinergics and β3-adrenoceptor agonist medication use declined in all patients from baseline to follow-up; however, the absolute reduction in the proportion with any medication fill was similar across continuers versus discontinuers (21% vs. 18%, p < 0.0001). Sacral neuromodulation was initiated by 15/535 (3%) of continuers and 137/1970 (7%) of discontinuers (p < 0.0001). No patients initiated percutaneous tibial neuromodulation. CONCLUSIONS: Early discontinuation of onabotulinumtoxinA therapy for OAB is common and most discontinuers do not receive alternative treatments. Providers have the opportunity to educate OAB patients with un- or undertreated symptoms regarding alternative options.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".