JOURNAL ARTICLE
Clustering of Patients with Interstitial Cystitis/Bladder Pain Syndrome and Chronic Prostatitis/Chronic Pelvic Pain Syndrome.
Journal of Urology 2019 September
PURPOSE: We performed clustering analysis of patient symptoms to discover common patient subtypes in females and males with interstitial cystitis/bladder pain syndrome or chronic prostatitis/chronic pelvic pain syndrome.
MATERIALS AND METHODS: The clinical variables included in k-means clustering were urological pain severity, urinary urgency, frequency and nonurological pain, each on a 0 to 10 numerical rating scale, and a yes or no response to each of the 6 UPOINT (Urological Treatment Program for Chronic Prostatitis) domains, including the urinary, psychosocial, organ specific, infection, neurological/systemic and skeletal muscle tenderness domains.
RESULTS: Included in study were 211 patients seeking care of interstitial cystitis/bladder pain syndrome or chronic prostatitis/chronic pelvic pain syndrome. The k-means clustering algorithm identified 3 clusters of patients with interstitial cystitis/bladder pain syndrome and chronic prostatitis/chronic pelvic pain syndrome, including 1) a mild pelvic symptom cluster in about 30% of patients, 2) a severe pelvic symptom cluster in about 40% and 3) a systemic symptom cluster in about 30%. Patients in the systemic cluster were younger by about 5 to 7 years and more likely to be female. They had the most severe urinary symptoms (urgency, frequency and painful bladder filling), and the most severe pelvic and nonpelvic pain. They were also more likely to have chronic overlapping pain conditions, psychosocial issues (depression, anxiety and somatic symptoms) and poorer quality of life than patients in the 2 other pelvic clusters. They were not less likely to have Hunner lesions in the bladder.
CONCLUSIONS: Symptom based clustering identified 3 clusters of patients with interstitial cystitis/bladder pain syndrome and chronic prostatitis/chronic pelvic pain syndrome. These patient subtypes had different pelvic and systemic presentations. Patients in the systemic cluster may benefit from interdisciplinary therapies. Future studies are needed to elucidate differences in pathophysiology among these clusters.
MATERIALS AND METHODS: The clinical variables included in k-means clustering were urological pain severity, urinary urgency, frequency and nonurological pain, each on a 0 to 10 numerical rating scale, and a yes or no response to each of the 6 UPOINT (Urological Treatment Program for Chronic Prostatitis) domains, including the urinary, psychosocial, organ specific, infection, neurological/systemic and skeletal muscle tenderness domains.
RESULTS: Included in study were 211 patients seeking care of interstitial cystitis/bladder pain syndrome or chronic prostatitis/chronic pelvic pain syndrome. The k-means clustering algorithm identified 3 clusters of patients with interstitial cystitis/bladder pain syndrome and chronic prostatitis/chronic pelvic pain syndrome, including 1) a mild pelvic symptom cluster in about 30% of patients, 2) a severe pelvic symptom cluster in about 40% and 3) a systemic symptom cluster in about 30%. Patients in the systemic cluster were younger by about 5 to 7 years and more likely to be female. They had the most severe urinary symptoms (urgency, frequency and painful bladder filling), and the most severe pelvic and nonpelvic pain. They were also more likely to have chronic overlapping pain conditions, psychosocial issues (depression, anxiety and somatic symptoms) and poorer quality of life than patients in the 2 other pelvic clusters. They were not less likely to have Hunner lesions in the bladder.
CONCLUSIONS: Symptom based clustering identified 3 clusters of patients with interstitial cystitis/bladder pain syndrome and chronic prostatitis/chronic pelvic pain syndrome. These patient subtypes had different pelvic and systemic presentations. Patients in the systemic cluster may benefit from interdisciplinary therapies. Future studies are needed to elucidate differences in pathophysiology among these clusters.
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