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Symptom Based Clustering of Men in the LURN Observational Cohort Study.

Authors
  • Liu, Gang1
  • Andreev, Victor P1
  • Helmuth, Margaret E1
  • Yang, Claire C2
  • Lai, H Henry3
  • Smith, Abigail R1
  • Wiseman, Jonathan B1
  • Merion, Robert M1
  • Erickson, Bradley A4
  • Cella, David5
  • Griffith, James W5
  • Gore, John L2
  • DeLancey, John O L6
  • Kirkali, Ziya7
  • 1 Arbor Research Collaborative for Health, Ann Arbor, Michigan.
  • 2 University of Washington, Seattle, Washington.
  • 3 Washington University School of Medicine, St. Louis, Missouri.
  • 4 University of Iowa, Iowa City, Iowa.
  • 5 Northwestern University, Chicago, Illinois.
  • 6 University of Michigan, Ann Arbor, Michigan.
  • 7 National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland.
Type
Published Article
Journal
The Journal of urology
Publication Date
Dec 01, 2019
Volume
202
Issue
6
Pages
1230–1239
Identifiers
DOI: 10.1097/JU.0000000000000354
PMID: 31120372
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Conventional classification of patients with lower urinary tract symptoms into diagnostic categories based on a predefined symptom complex or predominant symptom appears inadequate. This is due to the frequent presentation of patients with multiple urinary symptoms which could not be perfectly categorized into traditional diagnostic groups. We used a novel clustering method to identify subtypes of male patients with lower urinary tract symptoms based on detailed multisymptom information. We analyzed baseline data on 503 care seeking men in the LURN (Symptoms of Lower Urinary Tract Dysfunction Research Network) Observational Cohort Study. Symptoms and symptom severity were assessed using the LUTS (Lower Urinary Tract Symptoms) Tool and the AUA SI (American Urological Association Symptom Index), which include a total of 52 questions. We used a resampling based consensus clustering algorithm to identify patient subtypes with distinct symptom signatures. Four distinct symptom clusters were identified. The 166 patients in cluster M1 had predominant symptoms of frequency, nocturia, hesitancy, straining, weak stream, intermittency and incomplete bladder emptying suggestive of bladder outlet obstruction. The 93 patients in cluster M2 mainly endorsed post-micturition symptoms (eg post-void dribbling and post-void leakage) with some weak stream. The 114 patients in cluster M3 reported mostly urinary frequency without incontinence. The 130 patients in cluster M4 reported severe frequency, urgency and urgency incontinence. Most other urinary symptoms statistically differed between cluster pairs. Patient reported outcomes of bowel symptoms, mental health, sleep dysfunction, erectile function and urological pain significantly differed across the clusters. We identified 4 data derived clusters among men seeking care for lower urinary tract symptoms. The clusters differed from traditional diagnostic categories. Further subtype refinement will be done to incorporate clinical data and nonurinary patient reported outcomes.

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