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



Develop models to predict outcomes after intradetrusor injection of 100 or 200 units of onabotulinumtoxinA in women with non-neurogenic urgency urinary incontinence (UUI).


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.


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


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.





Published Version (Please cite this version)


Publication Info

Hendrickson, Whitney K, Gongbo Xie, David D Rahn, Cindy L Amundsen, James A Hokanson, Megan Bradley, Ariana L Smith, Vivian W Sung, et al. (2021). Predicting outcomes after intradetrusor onabotulinumtoxina for non-neurogenic urgency incontinence in women. Neurourology and urodynamics. 10.1002/nau.24845 Retrieved from

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Cindy Louise Amundsen

Roy T. Parker, M.D. Distinguished Professor of Obstetrics and Gynecology, in the School of Medicine
  • Treatment with a minimally invasive neural modulation system (sacral and posterior tibial nerve) for control of urinary continence
    - Application of botox therapy for urinary urge incontinence
    - Evaluation and treatment for nocturnal voiding
    - Application of nerve stimulation for urinary retention
    - Minimally invasive prolapse surgery for pelvic organ prolapse repairs
    - Treatment for stress urinary incontinence with minimally invasive techniques
    - Evaluation of the urinary microbiome as it relates to recurrent urinary tract infections and lower urinary tract symptoms

Anthony Gabriele Visco

Professor of Obstetrics and Gynecology

Robotic sacrocolpopexy, robotic hysterectomy, outcomes for surgical and non-surgical treatments of urinary incontinence and pelvic organ prolapse, robotic surgery, mesh erosion, Botox therapy for urge incontinence, innovation and entrepreneurship.


Sheng Luo

Professor of Biostatistics & Bioinformatics

John E Jelovsek

F. Bayard Carter Distinguished Professor of Obstetrics and Gynecology

Dr. Jelovsek is the F. Bayard Carter Distinguished Professor of OBGYN at Duke University and serves as Director of Data Science for Women’s Health. He is Board Certified in OBGYN by the American Board of OBGYN and in Female Pelvic Medicine & Reconstructive Surgery by the American Board of OBGYN and American Board of Urology. He has an active surgical practice in urogynecology based out of Duke Raleigh. He has expertise as a clinician-scientist in developing and evaluating clinical prediction models using traditional biostatistics and machine learning approaches. These “individualized” patient-centered prediction tools aim to improve decision-making regarding the prevention of lower urinary tract symptoms (LUTS) and other pelvic floor disorders after childbirth (PMID:29056536), de novo stress urinary incontinence and other patient-perceived outcomes after pelvic organ prolapse surgery, risk of transfusion during gynecologic surgery, and urinary outcomes after mid-urethral sling surgery (PMID: 26942362). He also has significant expertise in leading trans-disciplinary teams through NIH-funded multi-center research networks and international settings. As alternate-PI for the Cleveland Clinic site in the NICHD Pelvic Floor Disorders Network, he was principal investigator on the CAPABLe trial (PMID: 31320277), one of the largest multi-center trials for fecal incontinence studying anal exercises with biofeedback and loperamide for the treatment of fecal incontinence. He was the principal investigator of the E-OPTIMAL study (PMID: 29677302), describing the long-term follow up sacrospinous ligament fixation compared to uterosacral ligament suspension for apical vaginal prolapse. He was also primary author on research establishing the minimum important clinical difference for commonly used measures of fecal incontinence. Currently, he serves as co-PI in the NIDDK Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) (U01DK097780-05) where he has been involved in studies in the development of Symptoms of Lower Urinary Tract Dysfunction Research Network Symptom Index-29 (LURN SI-29) and LURN SI-10 questionnaires for men and women with LUTS. He is also the site-PI for the PREMIER trial (1R01HD105892): Patient-Centered Outcomes of Sacrocolpopexy versus Uterosacral Ligament Suspension for the Treatment of Uterovaginal Prolapse.

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