Efficacy of intravesical chondroitin sulphate in treatment of interstitial cystitis/bladder pain syndrome (IC/BPS): Individual patient data (IPD) meta-analytical approach
Bibliographic record
Abstract
BACKGROUND: Raw data from 3 similar clinical trials were analyzed in this individual participant data (IPD) meta-analysis to define any possible efficacy of intravesical 2% chondroitin sulphate in IC/BPS. METHODS: We pooled IPD from an open label and 2 small randomized placebo controlled trials assessing chondroitin sulphate in IC/BPS (similar inclusion/exclusion criteria, treatment, outcome assessment). Our primary objective was to compare rates of global response assessment (GRA) responsiveness between chondroitin sulphate and vehicle control. Secondary objectives compared the Interstitial Cystitis Symptom/Problem Index (ICSI/PI) total score and improvement rates, and average daily urine frequency. The treatment response was calculated for individual trials and pooled data using IPD meta-analysis for pooling proportions. RESULTS: In total, 213 patients were included in the pooling analysis. At the end of the treatment period, the overall GRA response rates were 43.2 (95% CI: 35.0, 51.5) and 27.4 (95% CI: 17.6, 37.2) for the chondroitin sulphate and vehicle control groups, respectively. Pooled RR was 1.55 (p = 0.014, 95% CI: 1.09, 2.22). The chance of being an ICSI responder was similarly 54% higher in the chondroitin sulphate group. The small decrease in total ICSI score and urine frequency between the two groups was less impressive (-0.8 and -0.5 points respectively) and not statistically significant. CONCLUSIONS: Benefits from intravesical chondroitin sulphate treatment in IC/BPS patients can be confirmed by increasing the power of the available data using an IPD meta-analytical approach. However, disconnect between response rates and severity scores underline the importance of choosing the right patient for this organ-specific treatment.
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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 | 0.043 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.071 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".