Symptom-Based Clustering of Women in the Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN) Observational Cohort Study

Women with lower urinary tract symptoms (LUTS) are often diagnosed based on a pre-defined symptom complex, or on a predominant symptom. There are many limitations to this paradigm, as often patients present with multiple urinary symptoms that do not perfectly fit the pre-established diagnoses. We utilized cluster analysis to identify novel symptom-based subtypes of women with LUTS.

Baseline urinary symptom questionnaire data were analyzed from 545 care-seeking female participants enrolled in the LURN Observational Cohort Study. Symptoms were measured using the LUTS Tool and the AUA Symptom Index and analyzed using a probability-based consensus clustering algorithm.

Four clusters were identified. Women in cluster F1 (n=138) do not report incontinence, but experience post-void dribbling, frequency, and voiding symptoms. Women in cluster F2 (n=80) report urgency incontinence, as well as urgency and frequency, and very minimal voiding symptoms or stress incontinence. Cluster F3 (n=244) includes women who report all types of incontinence, urgency, frequency, and very mild voiding symptoms. Women in cluster F4 (n=83) report all LUTS at uniformly high levels. All but two of 44 LUTS Tool and 8 AUA symptom questions were significantly (p<0.05) different between at least two clusters, and all clusters contained at least one member from each conventional group (continent, stress incontinence, urgency incontinence, mixed incontinence, and other incontinence).

Women seeking care for LUTS cluster into four distinct symptom groups that differ from conventional clinical diagnostic groups. Further validation is needed to determine whether management improves with this new classification.

The Journal of urology. 2018 Jul 07 [Epub ahead of print]

Victor P Andreev, Gang Liu, Claire C Yang, Abigail R Smith, Margaret E Helmuth, Jonathan B Wiseman, Robert M Merion, Kevin P Weinfurt, Anne P Cameron, H Henry Lai, David Cella, Brenda W Gillespie, Brian T Helfand, James W Griffith, John O L DeLancey, Matthew O Fraser, J Quentin Clemens, Ziya Kirkali, LURN Study Group

Arbor Research Collaborative for Health, Ann Arbor, MI. Electronic address: ., Arbor Research Collaborative for Health, Ann Arbor, MI., University of Washington, Seattle, WA., Duke University Medical Center., University of Michigan, Ann Arbor, MI., Washington University School of Medicine, St. Louis, MO., Northwestern University Feinberg School of Medicine, Chicago, IL., NorthShore University Health System, Glenview, IL., National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD.