Classification of interstitial cystitis/bladder pain syndrome (ic/bps) using a machine learning based symptom score constructed on inflammatory urine cytokines and patient-reported outcomes improves diagnosis

You have accessJournal of UrologyCME1 Apr 2023MP39-01 CLASSIFICATION OF INTERSTITIAL CYSTITIS/BLADDER PAIN SYNDROME (IC/BPS) USING A MACHINE LEARNING BASED SYMPTOM SCORE CONSTRUCTED ON INFLAMMATORY URINE CYTOKINES AND PATIENT-REPORTED OUTCOMES IMPROVES DIAGNOSIS Laura Lamb, Joseph Janicki, Nitya Abraham, Melissa Laudano, Christopher Smith, Sarah Bartolone, Elijah Ward, Kenneth Peters, Bernadette Zwaans, Michael, and Chancellor Laura LambLaura Lamb More articles by this author , Joseph JanickiJoseph Janicki More articles by this author , Nitya AbrahamNitya Abraham More articles by this author , Melissa LaudanoMelissa Laudano More articles by this author , Christopher SmithChristopher Smith More articles by this author , Sarah BartoloneSarah Bartolone More articles by this author , Elijah WardElijah Ward More articles by this author , Kenneth PetersKenneth Peters More articles by this author , Bernadette ZwaansBernadette Zwaans More articles by this author , MichaelMichael More articles by this author , and Chancellor Chancellor More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003277.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: IC/BPS is a multifactorialsyndrome of severe pelvic and genitalia pain. Diagnosis of IC/BPS currentlyutilizes patient-reported outcomes (PRO) instruments to assess symptoms, howeveroverlapping symptoms with other diseases can delay proper diagnosis and symptomrelief. The objective of this study isto develop an improved IC/BPS risk classification, using machine learningalgorithm to leverage both urine inflammatory cytokines and PROs. METHODS: A national crowdsourcing resulted in 442 clinical urine samples consisting of 153 IC patients (146 female, 7 male), and 289 asymptomatic age-matched controls (155 female, 134 male) with corresponding PRO pain and symptom scores. This included 53 patients with a bladder-centric dysfunction as defined by presence of Hunner’s lesions. An independent validation cohort was also collected. Urinary cytokine levels were determined using Luminex assay. A predictive classification model, termed the Personalized Inflammation Symptom (PIS) Score, was generated from this data into three classification: 1) normal/low IC risk; 2) moderate to high risk for IC with bladder centric dysfunction; and 3) moderate to high risk of IC without bladder centric dysfunction. RESULTS: In the training set, the PIS Score correctly classified all controls, all IC patients without Hunner’s lesions, and 98% (52/53) IC patients with Hunner’s lesions. In the independent validation set, the PIS Score correctly classified 26 of 27 (96%), 14 of 19 (73.7%) IC without Hunner’s lesions, and all IC patient’s with Hunner’s lesions. CONCLUSIONS: In one of the largest collection of urine samples of IC/BPS patients from across all 50 states of US, two key findings emerged: 1) A standardized LUMINEX laboratory urine assay based IC-Risk Score is comparable to ICSI/ICPI or pain VAS in accuracy of diagnosis; 2) PIS, using laboratory-based objective data in combination with PROs, improves the AUC and accuracy of IC/BPS diagnosis. An objective laboratory test for IC/BPS, similar to tests that have been developed to improve cancer diagnosis, may help expand access, accelerate proper diagnosis, and improve care for IC/BPS, a disease with great unmet needs.Figure 1 Source of Funding: This work was supported by the Office of the Assistant Secretary ofDefense for Health Affairs through the Technology/Therapeutic DevelopmentResearch Program under Award No. W81XWH-19-1-0288. The opinions,interpretations, conclusions, and recommendations are those of the authors andare not necessarily endorsed by the Department of Defense. © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e534 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Laura Lamb More articles by this author Joseph Janicki More articles by this author Nitya Abraham More articles by this author Melissa Laudano More articles by this author Christopher Smith More articles by this author Sarah Bartolone More articles by this author Elijah Ward More articles by this author Kenneth Peters More articles by this author Bernadette Zwaans More articles by this author Michael More articles by this author Chancellor More articles by this author Expand All Advertisement PDF downloadLoading ...