Predicting outcomes after intradetrusor onabotulinumtoxina for non-neurogenic urgency incontinence in women.

AIMS: Develop models to predict outcomes after intradetrusor injection of 100 or 200 units of onabotulinumtoxinA in women with non-neurogenic urgency urinary incontinence (UUI). METHODS: Models were developed using 307 women from two randomized trials assessing efficacy of onabotulinumtoxinA for non-neurogenic UUI. Cox, linear and logistic regression models were fit using: (1) time to recurrence over 12 months, (2) change from baseline daily UUI episodes (UUIE) at 6 months, and (3) need for self-catheterization over 6 months. Model discrimination of Cox and logistic regression models was calculated using c-index. Mean absolute error determined accuracy of the linear model. Calibration was demonstrated using calibration curves. All models were internally validated using bootstrapping. RESULTS: Median time to recurrence was 6 (interquartile range [IQR]: 2-12) months. Increasing age, 200 units of onabotulinumtoxinA, higher body mass index (BMI) and baseline UUIE were associated with decreased time to recurrence. The c-index was 0.63 (95% confidence interval [CI]: 0.59, 0.67). Median change in daily UUIE from baseline at 6 months was -3.5 (IQR: -5.0, -2.3). Increasing age, lower baseline UUIE, 200 units of onabotulinumtoxinA, higher BMI and IIQ-SF were associated with less improvement in UUIE. The mean absolute error predicting change in UUIE was accurate to 1.6 (95% CI: 1.5, 1.7) UUI episodes. The overall rate of self-catheterization was 17.6% (95% CI: 13.6%-22.4%). Lower BMI, 200 units of onabotulinumtoxinA, increased baseline postvoid residual and maximum capacity were associated with higher risk of self-catheterization. The c-index was 0.66 (95% CI: 0.61, 0.76). The three calculators are available at http://riskcalc.duke.edu. CONCLUSIONS: After external validation, these models will assist clinicians in providing more accurate estimates of expected treatment outcomes after onabotulinumtoxinA for non-neurogenic UUI in women.

Duke Scholars

Author Cindy Louise Amundsen Obstetrics and Gynecology, Urogynecology

Author Anthony Gabriele Visco Obstetrics and Gynecology, Urogynecology

Author Sheng Luo Biostatistics & Bioinformatics, Division of Biostatistics

Author John E Jelovsek Obstetrics and Gynecology, Urogynecology