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

Publication ,  Journal Article
Andreev, VP; Liu, G; Yang, CC; Smith, AR; Helmuth, ME; Wiseman, JB; Merion, RM; Weinfurt, KP; Cameron, AP; Lai, HH; Cella, D; Gillespie, BW ...
Published in: J Urol
December 2018

PURPOSE: Women with lower urinary tract symptoms are often diagnosed based on a predefined symptom complex or a predominant symptom. There are many limitations to this paradigm as often patients present with multiple urinary symptoms which do not perfectly fit the preestablished diagnoses. We used cluster analysis to identify novel, symptom based subtypes of women with lower urinary tract symptoms. MATERIALS AND METHODS: We analyzed baseline urinary symptom questionnaire data obtained from 545 care seeking female participants enrolled in the LURN (Symptoms of Lower Urinary Tract Dysfunction Research Network) Observational Cohort Study. Symptoms were measured with the LUTS (lower urinary tract symptoms) Tool and the AUA SI (American Urological Association Symptom Index), and analyzed using a probability based consensus clustering algorithm. RESULTS: Four clusters were identified. The 138 women in cluster F1 did not report incontinence but experienced post-void dribbling, frequency and voiding symptoms. The 80 women in cluster F2 reported urgency incontinence as well as urgency and frequency but minimal voiding symptoms or stress incontinence. Cluster F3 included 244 women who reported all types of incontinence, urgency, frequency and mild voiding symptoms. The 83 women in cluster F4 reported all lower urinary tract symptoms at uniformly high levels. All but 2 of 44 LUTS Tool and 8 AUA SI questions significantly differed between at least 2 clusters (p <0.05). All clusters contained at least 1 member from each conventional group, including continence, and stress, urgency, mixed and other incontinence. CONCLUSIONS: Women seeking care for lower urinary tract symptoms cluster into 4 distinct symptom groups which differ from conventional clinical diagnostic groups. Further validation is needed to determine whether management improves using this new classification.

Duke Scholars

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Published In

J Urol

DOI

EISSN

1527-3792

Publication Date

December 2018

Volume

200

Issue

6

Start / End Page

1323 / 1331

Location

United States

Related Subject Headings

  • Urology & Nephrology
  • Urinary Bladder
  • Surveys and Questionnaires
  • Middle Aged
  • Lower Urinary Tract Symptoms
  • Humans
  • Female
  • Cohort Studies
  • Cluster Analysis
  • Algorithms
 

Citation

APA
Chicago
ICMJE
MLA
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Andreev, V. P., Liu, G., Yang, C. C., Smith, A. R., Helmuth, M. E., Wiseman, J. B., … LURN Study Group, . (2018). Symptom Based Clustering of Women in the LURN Observational Cohort Study. J Urol, 200(6), 1323–1331. https://doi.org/10.1016/j.juro.2018.06.068
Andreev, Victor P., Gang Liu, Claire C. Yang, Abigail R. Smith, Margaret E. Helmuth, Jonathan B. Wiseman, Robert M. Merion, et al. “Symptom Based Clustering of Women in the LURN Observational Cohort Study.J Urol 200, no. 6 (December 2018): 1323–31. https://doi.org/10.1016/j.juro.2018.06.068.
Andreev VP, Liu G, Yang CC, Smith AR, Helmuth ME, Wiseman JB, et al. Symptom Based Clustering of Women in the LURN Observational Cohort Study. J Urol. 2018 Dec;200(6):1323–31.
Andreev, Victor P., et al. “Symptom Based Clustering of Women in the LURN Observational Cohort Study.J Urol, vol. 200, no. 6, Dec. 2018, pp. 1323–31. Pubmed, doi:10.1016/j.juro.2018.06.068.
Andreev VP, Liu G, Yang CC, Smith AR, Helmuth ME, Wiseman JB, Merion RM, Weinfurt KP, Cameron AP, Lai HH, Cella D, Gillespie BW, Helfand BT, Griffith JW, DeLancey JOL, Fraser MO, Clemens JQ, Kirkali Z, LURN Study Group. Symptom Based Clustering of Women in the LURN Observational Cohort Study. J Urol. 2018 Dec;200(6):1323–1331.
Journal cover image

Published In

J Urol

DOI

EISSN

1527-3792

Publication Date

December 2018

Volume

200

Issue

6

Start / End Page

1323 / 1331

Location

United States

Related Subject Headings

  • Urology & Nephrology
  • Urinary Bladder
  • Surveys and Questionnaires
  • Middle Aged
  • Lower Urinary Tract Symptoms
  • Humans
  • Female
  • Cohort Studies
  • Cluster Analysis
  • Algorithms