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Urology. 2001 Jun;57(6 Suppl 1):67-81.

Biopsy features are associated with primary symptoms in interstitial cystitis: results from the interstitial cystitis database study.

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University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104-6021, USA.


The purpose of this study was to investigate associations between bladder biopsy features and urinary symptoms for patients enrolled in the Interstitial Cystitis Database (ICDB) Study. Bladder biopsies were obtained during baseline screening in the ICDB Study and were evaluated for histopathologic features. Multivariable models for nighttime voiding frequency, urinary urgency, and pain were developed, incorporating biopsy features from the most diseased area of the bladder as predictors, adjusting for significant clinical factors, and clinical center variation. Among 204 interstitial cystitis (IC) patients providing biopsy specimens, cystoscopic pathology findings were not statistically associated (P >0.1) with primary IC symptoms, although the presence of Hunner's ulcer (n = 12) was suggestive of increased urinary frequency. Within a multivariable predictive model for nighttime voiding frequency, adjusting for age and minimum volume per void, 4 pathology features were noted: (1) mast cell count in lamina propria on tryptase stain; (2) complete loss of urothelium; (3) granulation tissue in lamina propria; and (4) vascular density in lamina propria on factor VIII (F8) stain were statistically significant (P <0.01). Similarly, in a multivariable model for urinary urgency, minimum volume, and percentage of submucosal granulation tissue remained statistically significant (P <0.01). Finally, the percentage of mucosa denuded of urothelium and the percentage of submucosal hemorrhage remained highly associated (P <0.01) with pain in a multivariable predictive model. The fact that the presence or severity of glomerulations was not selected for any of these predictive models suggests that cystoscopic findings of glomerulations are not predictive of IC symptoms. Furthermore, these results suggest an important role for certain pathologic features in the predictive modeling of IC symptoms.

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