# Advancing the Measurement and Classification of Lower Urinary Tract Dysfunction

> **NIH NIH U01** · DUKE UNIVERSITY · 2020 · $29,999

## Abstract

PROJECT SUMMARY
Lower urinary tract symptoms (LUTS) are common with high economic and social costs and significant effects
on patients’ quality of life. Prevalence of LUTS increases with age, with estimates ranging from 45-70% of U.S.
adults. It is clear from the range of conditions that produce LUTS, and the failure of current therapies to
ameliorate symptoms in large segments of the population that have similar LUTS, that patients with LUTS are
a heterogeneous population even when their symptoms are identical or overlap. Current LUTS treatment
paradigms target narrow symptom groups, largely ignoring the heterogeneity in concomitant symptoms.
Furthermore, clinicians have a limited understanding on how to integrate information from self-reported
symptoms, clinical exam and laboratory results, and urodynamic testing into treatment decision-making.
Improving treatment outcomes for patients with LUTS will require both (1) increased understanding of LUTS
symptom clusters and underlying mechanisms behind the various subtypes and (2) comprehensive, validated,
and responsive measurement tools for defining treatment efficacy. The Symptoms of Lower Urinary Tract
Dysfunction Research Network (LURN) was assembled in 2012, the primary objective of which was to
categorize patients with LUTS into distinct subgroups, a process known as ‘phenotyping’. The Network’s
approach to defining patient subtypes was based on a probability-based consensus clustering approach using
a myriad of patient data, resulting in the identification of novel LUTS-based clusters that are statistically and
clinically distinct. Concurrently, the Network worked to improve the measurement of patient reports of LUTS
through systematic development of a new, high-quality item bank based on qualitative input from patients,
community participants, internists, urologists, urogynecologists, and clinical researchers. LURN II will build on
the knowledge gained through multiple specific aims: to test and refine the original LURN clustering model in a
new cohort including a wider range of symptom severity and a wider range of physical measures (n=1380
participants followed for 3 years); to identify a signature of proteins contained within plasma that can be used
to identify specific subgroups of men and women with LUTS; to determine phenotypic characteristics of women
with LUTS by measuring the functional components of the lower urinary tract; to validate a self-reported
outcome tool for evaluating treatments, based on the comprehensive tool developed for phenotyping in LURN
I; and to explore promising alternative analytic approaches to existing and future LURN data and characterize
the broader experiences of patients with LUTS. This proposal brings together a multidisciplinary team of
urologists, urogynecologists, bladder physiologists, data scientists, epidemiologists, and outcomes
researchers. The proposed work has the potential to transform the diagnosis and treatment of LUTS.

## Key facts

- **NIH application ID:** 10246629
- **Project number:** 3U01DK097780-07S1
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Cindy Amundsen
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $29,999
- **Award type:** 3
- **Project period:** 2012-09-30 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10246629

## Citation

> US National Institutes of Health, RePORTER application 10246629, Advancing the Measurement and Classification of Lower Urinary Tract Dysfunction (3U01DK097780-07S1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10246629. Licensed CC0.

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