Patients presenting with lower urinary tract symptoms (LUTS) are historically classified to several symptom clusters, primarily overactive bladder (OAB) and interstitial cystitis/bladder pain syndrome (IC/BPS). Accurate diagnosis, however, is challenging due to overlapping symptomatic features, and many patients do not readily fit into these categories. To enhance diagnostic accuracy, we previously described an algorithm differentiating OAB from IC/BPS. Herein, we sought to validate the utility of this algorithm for identifying and classifying a real-world population of individuals presenting with OAB and IC/BPS and characterize patient subgroups outside the traditional LUTS diagnostic paradigm.