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High-probability grants
According to our matching algorithm, James A. Hokanson is the likely recipient of the following grants.
| Years |
Recipients |
Code |
Title / Keywords |
Matching
score |
| 2020 |
Hokanson, James Arthur |
K01Activity Code Description:
For support of a scientist, committed to research, in need of both advanced research training and additional experience. |
Predicting Urinary Continence Status With Sacral Neuromodulation and Botulinum Toxin Treatments
PROJECT SUMMARY Lower Urinary Tract Symptoms (LUTS) include urinary urgency, incontinence, and nocturia, afflict roughly 50% of the adult population, and have substantial, wide-ranging impact. Many gaps remain in our understanding of these symptoms, leading to inadequate treatment. Urgency urinary incontinence, one form of LUTS, was the focus of two recent multi-site clinical trials (Anticholinergic vs. Botox Comparison Study or ABC and Refractory Overactive Bladder: Sacral NEuromodulation vs. BoTulinum Toxin Assessment or ROSETTA). These trials compared the efficacy of urgency urinary incontinence therapies, 100 Units (U) Onabotulinum Toxin A (Botox) versus an anticholinergic medication (ABC) and 200U Botox versus sacral neuromodulation (SNM)(ROSETTA). These studies compared whether on average 100U Botox was superior to a standard anticholinergic regimen (ABC) and whether 200U Botox was superior to SNM (ROSETTA). The objective of this K01 proposal is to use the same clinical trial data to create predictive models that accurately estimate the likelihood that a patient will respond to Botox and SNM treatments, as well as the likelihood of developing urinary retention or urinary tract infections (risks associated with Botox treatment). In addition to medical histories and questionnaires some of the predictive models will incorporate diagnostic measurements, both standard and novel, from tests of bladder function (urodynamics). This approach will allow for the formal assessment of the utility of urodynamics in guiding treatment decisions, something that is currently debated in the field. This project will result in innovative models which can be used to: 1) predict whether a patient will respond to Botox and SNM treatments and the likelihood of adverse events (Botox only); 2) determine the utility of urodynamics data in predicting patient response to treatment and 3) identify patients that are resistant to treatment, so as to guide future research. These models will offer a patient specific, data-driven approach to treatment that will greatly benefit patient care and help reduce costs to the health care system. This project will also provide training in predictive modeling and clinical benign urology under the guidance of an experienced mentoring team. The candidate?s long-term objective is to lead a strong independent research program to design new therapies for patients with (LUTS) informed by both animal and human studies, and to match patients with suitable therapies based on individual patient characteristics (personalized medicine).
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