Expansion of Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN)

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DESCRIPTION (provided by applicant): Lower urinary tract dysfunction (LUTD) is common, and its incidence and prevalence are increasing as the population ages. Symptoms of LUTD are costly to diagnose and treat; existing therapeutic interventions are neither highly effective nor durable and have side effects of their own. Not surprisingly, unsatisfactory outcomes from the patient perspective are common. Collectively, these challenges represent important targets of research that are consistent with the mission of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Previous efforts to improve patient reported outcomes (PRO) in this area have relied on incomplete symptom measurement scales and have been hampered by imperfect understanding of the origin and natural history of LUTD. Comprehensive re-evaluation of the symptom universe of LUTD and more precise characterization of patients with symptoms of LUTD (phenotyping) may provide significant new insights, leading ultimately to improved patient lives. The NIDDK-sponsored Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) includes a Data Coordinating Center (DCC) to serve as the project and data management nexus for the network. The purpose of this project is to expand the DCC, and increase the number of clinical sites that will enroll patients with symptoms of LUTD into carefully designed studies. There are three specific aims. The first is to expand the infrastructure of the LURN network to accommodate the addition of three to four clinical sites, plus the anticipated increase in complexity in supporting a larger consortium. The second specific aim is to enhance the collaboration between stakeholders by increasing the number of face-to-face meetings of the Steering Committee from one (currently) to three annually. The third aim is to expand the LURN consortium's patient-reported outcome measurement tools to include development and implementation of computerized adaptive testing.