Treatment effectiveness in interstitial cystitis/bladder pain syndrome: Do patient perceptions align with efficacy-based guidelines?
Bibliographic record
Abstract
INTRODUCTION: We sought to determine if patients' perceptions of success or failure of interstitial cystitis/bladder pain syndrome (IC/BPS) therapies proposed in treatment guidelines align with the evidence from available clinical trial treatment data. METHODS: A total of 1628 adult females with a self-reported diagnosis of IC completed a web-based survey in which patients described their perceived outcomes with the therapies they were exposed to. Previously published literature, used in part to develop IC/BPS guidelines, provided the clinical trial data outcomes. Patient-reported outcomes were compared to available clinical trial outcomes and published treatment guidelines. RESULTS: Based on patient perceived outcomes (benefit:risk ratio), the most effective treatments were opioids, phenazopyridine, and alkalizing agents, with amitriptyline and antihistamines reported as moderately effective. The only surgical procedure with any effectiveness was electrocautery of Hunner's lesions. In order of efficacy reported in the literature, the therapies for IC/BPS with predicted superior outcomes should be: cyclosporine A, amitriptyline, hyperbaric oxygen, pentosan polysulfate plus subcutaneous heparin, botulinum toxin A plus hydrodistension, and L-arginine. While some of the guideline recommendations aligned with patient-reported effectiveness data, there was a general disconnect between guidelines and effectiveness reported in clinical practice. CONCLUSIONS: There is a disconnect between real-world patient perceived effectiveness of IC/BPS treatments compared to the efficacy reported from clinical trial data and subsequent guidelines developed from this efficacy data. Optimal therapy must include the best evidence from clinical research, but should also include real-life clinical practice implementation and effectiveness.
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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 | 0.030 | 0.126 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".