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SYMPTOM-BASED CLUSTERING OF MEN IN THE SYMPTOMS OF LOWER URINARY TRACT DYSFUNCTION RESEARCH NETWORK (LURN) OBSERVATIONAL COHORT STUDY.

PURPOSE
Conventional classification of patients with lower urinary tract symptom (LUTS) into diagnostic categories based on a pre-defined symptom complex or predominant symptom appears inadequate, as patients frequently present with multiple urinary symptoms that could not be perfectly categorized into traditional diagnostic groups. We used a novel clustering method to identify male LUTS patient subtypes, based on detailed multi-symptom information.


MATERIALS AND METHODS
Baseline data from 503 care-seeking men in the LURN Observational Cohort study was analyzed. Symptoms and their severity were assessed using the LUTS Tool and AUA Symptom Index (52 questions total). A resampling-based consensus clustering algorithm identified patient subtypes with distinct symptom signatures.


RESULTS
Four distinct symptom clusters were identified. Patients in cluster M1 (n=166) had predominant symptoms of frequency, nocturia, hesitancy, straining, weak stream, intermittency and incomplete bladder emptying, suggestive of bladder outlet obstruction. Patients in cluster M2 (n=93) mainly endorsed post-micturition symptoms (e.g., post-void dribbling, post-void leakage), with some weak stream. Patients in cluster M3 (n=114) reported mostly urinary frequency without incontinence. Patients in cluster M4 (n=130) reported severe frequency, urgency and urgency incontinence. The majority of other urinary symptoms were statistically different between pairs of clusters. Patient reported outcomes of bowel symptoms, mental health, sleep dysfunction, erectile function, and urologic pain were significantly different across the clusters.


CONCLUSIONS
We identified four data-derived clusters among men seeking care for LUTS that were different from traditional diagnostic categories. Further subtype refinement will incorporate clinical data and non-urinary patient-reported outcomes.