Brian T. Helfand, Ph.D. - US grants

DESCRIPTION (provided by applicant): This proposal is in response to the Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) (U01) (RFA-DK-11-026) Funding Opportunity Announcement. Lower urinary tract dysfunction (LUTD) is found in many pathologic conditions. Measurement tools that are not disease-specific can help better characterize symptoms of LUTD across conditions; potentially linking those symptoms to genetic variants and clinical subtypes. This in turn can improve care for patients with LUTD. New measurement tools need to be expanded to include men and woman alike. Effective LUTD symptom reporting can help better characterize urology patients, more effectively guide treatment, and clarify relationships between phenotype and biological substrates (e.g., genotype, neurophysiology). This is an important aim of the NIDDK's Prostate Strategic Plan. Existing self-report tools measure different symptoms with varying reliability and validity; this proposal will redress inconsistencies and deficiencies found in existing measures of urinary symptoms. Using methods we developed in PROMIS and related projects, we propose to develop a state-of-the art self-report measure of LUTD as well as their associated features and common comorbidities. Because our newly-created self-report measure will employ item response theory (IRT)-calibrated item banks where possible, we will create both static and adaptive, computer-based versions of the test. Computer adaptive testing (CAT) allows for brief-yet-precise measurement, reducing patient burden. Measures that are responsive to treatment impact are needed for clinical research and clinical practice aimed to manage symptoms of LUTD. Our methods include two aims: Instrument development/calibration; and clinical validation. To develop and calibrate the instrument, we will conduct two phases of qualitative research with approximately 40 urology patients, conduct a systematic and comprehensive literature review, collect input from 15 experts, and conduct state-of-the-science psychometric analysis of data collected from an Internet-based study of 800 individuals with LUTD, sleep disorder, obesity, or healthy controls. We will evaluate item response theory parameters, convergent validity with established self-report measures, and the relationships among LUTD and two emerging risks for LUTD: obesity and sleep disorders. We will then validate our new tools against conventionally-used questionnaires (e.g., International Prostate Scoring System), known biometric correlates of LUTD, such as urinary flow rate (Qmax), and newly-identified candidate genes for LUTD. Specifically, we will examine the ability of our new scale, and existing scales, to detect differences across, and associations within, four groups: obesity (n = 64), sleep dysfunction (n = 64), people with a history of LUTD (n = 160); and healthy controls (n = 64). This phase of the project will provide information about patient phenotype, and advance our knowledge on genotype-phenotype relationships.

The Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) was assembled in 2012 to increase our understanding of lower urinary tract symptoms (LUTS) by identifying important subtypes of patients with LUTS, and improving the measurement of patient experiences of LUTS. The Network's approach to defining patient subtypes was based on a re-sampling-based consensus clustering approach using self- reported patient data, resulting in the identification of novel LUTS-based clusters that are statistically and clinically distinct. The approach to improving the measurement of patient reports of LUTS was to systematically develop a new, high-quality item bank based on qualitative input from patient, community participants, internists, urologists, urogynecologists, and clinical researchers. Finally, in order to understand some of the pathophysiologic basis underlying lower urinary tract dysfunction, biologic information was obtained and analyzed from patient samples and imaging. After a successful initial 5-year funding cycle, LURN is prepared to build on the knowledge gained and take the next steps with the following Specific Aims: 1) To test and refine the original clustering model with a cohort including a wider range of symptom severity and a wider range of physiological measures, 2) To identify protein biomarker signatures contained within plasma that can be used to identify specific subgroups of men and women with LUTS 3) To determine phenotypic characteristics of women with lower urinary tract symptoms (LUTS) by measuring the functional components of the lower urinary tract, 4) To validate a comprehensive outcome tool for men and women with LUTS, and 5) To determine the role of psychosocial stress ? especially adverse childhood experiences ? in the severity and course of LUTS. The LURN II will recruit 1380 patients, stratified by sex. Our site will recruit 1/6 of these participants (N = 230). We have a multi-method approach to phenotyping patients with LUTS, which will include questionnaires, laboratory tests, mobile apps, and urodynamics of the bladder and urethra. Data will be analyzed using resampling-based cluster analyses, as well as longitudinal modelling of symptoms over time. We hypothesize that our biopsychosocial approach to assessing patients with LUTS will yield clinically- meaningful patient clusters, which in turn can be linked to causal mechanisms as well as treatment options. Moreover, we hypothesize that modifiable risk factors will be related to the course of LUTS over time, creating novel avenues for treatment. The impact of this study will lend itself to an improved understanding of the causes and nature of LUTS, which will set the stage for clinical trials to improve quality of life for these patients.