Interstitial cystitis/bladder pain syndrome (IC/BPS) is a condition causing bladder inflammation, and bladder pain symptoms. Urinary biomarkers have been assessed suitable for the diagnosis and treatment guidance for lower urinary tract dysfunctions. This study aimed at investigating the diagnostic role of urinary biomarkers in identifying different phenotypes and bladder conditions in women with IC/BPS.

A total of 376 patients with established diagnosis of IC/BPS, 16 bladder hypersensitivity, and 30 controls were retrospectively enrolled in this study. All patients underwent a comprehensive urological workup of IC symptoms, physical examinations, pain severity, video urodynamic study, and cystoscopic hydrodistention findings including maximal bladder capacity (MBC) and glomerulation grade. Urine samples were collected at baseline to investigate the levels of 15 urinary cytokines, chemokines, and oxidative stress biomarkers. Patients with IC/BPS were further classified into the Hunner’s IC (HIC) and non-HIC (NHIC) groups, according to MBC and glomerulation grade. The dataset from the entire cohort was randomly split once, allocating 70% to the training set and 30% to the test set to support both internal and external validation processes. The median level of urinary biomarkers in the cohort of controls and bladder hypersensitivity were used as the normal cut-off value, and the urinary levels of urinary biomarkers locating at the range of quartile > Q3 or ≥ Q4 were considered as having mildly or moderately higher levels. Logistic regression was employed to determine the most significant urinary biomarker for identifying IC subtypes or bladder conditions, and the cut-off value of the biomarkers. Moreover, treatment response was graded according to global response assessment (GRA) scores, and urinary biomarker levels were analyzed.

Among the training set with 263 IC/BPS and 20 control women, urinary biomarker TNF-α and 8-OHdG were most significant biomarkers to identify IC/BPS from the cohort. The sensitivity and specificity using TNF-α ≥Q4 or 8-OHdG ≥Q4 were 99.2% and 70.0% in training set, and 99.1% and 50% in test set, respectively. (Figure 1) Among 376 women with IC/BPS, the urinary biomarker CXCL10 had the most significant AUC among urinary biomarkers, (0.803 ± 0.047) to identify HIC and NHIC. The sensitivity and specificity were 81.5% and 55.9% in the training set, and 73.3% and 68.4% in the test set, respectively. Patients with IC/BPS and higher urinary CXCL1 level in the Q4 (54.0%) and Q3 (47.8%) had higher grade of glomerulation than patients with CXCL1 level in the normal range (Q2 43.9%, Q1 27.4%), both in the training and test set. The CXCL1 level was also significantly higher in women with HIC than NHIC, both in the training and test set. (Figure 2)

Using urinary biomarker TNF-α and 8-OHdG, women with TNF-α ≥Q4 or 8-OHdG ≥Q4 had a high sensitivity to identify IC/BPS from the cohort of patients with frequency and bladder discomfort. Among patients with IC/BPS, CXCL1 can provide a diagnostic aid to identify HIC, and the higher urinary level of CXCL1 imply a higher grade of glomerulation and small MBC under cystoscopic hydrodistention. However, this cluster of urinary biomarkers did not predict treatment outcome.
Figure. The diagnosis of IC/BPS and differentiate subtypes and bladder condition by cluster of urinary biomarkers.

This study, for the first time, selected a cluster of urinary biomarkers such as TNF-α, 8-OHdG, and 8-isoprostane through machine learning to predict IC/BPS and added urinary IP-10 to identify HIC. These urinary biomarkers were strongly associated with chronic inflammation in the HIC and NHIC. Using a cluster of urinary biomarkers, namely, TNF-α or 8-OHdG and 8-isoprostane, can identify patients with IC/BPS from a study cohort, and adding the urinary IP-10 can detect patients with HIC from a IC/BPS cohort.

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