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Urinary tract cytology: a cytologic-histopathologic correlation with The Paris System, an institutional study
Alexandra Danakas1, Melissa Sweeney1, Sachica Cheris1
1Department of Pathology, University of Rochester Medical Center (URMC), Rochester, New York.
Introduction:
Urothelial carcinoma (UC) requires lifelong monitoring, commonly through urinary cytology and cystoscopy. Urine cytology has a relatively high sensitivity for detecting high-grade urothelial carcinoma (HGUC); however, its sensitivity for low-grade urothelial neoplasm (LGUN) is significantly lower with wide interobserver variability. The Paris System (TPS) was proposed to create standardized diagnostic categories with defined cytomorphologic criteria. We attempt to evaluate diagnostic efficacy of identifying UC using TPS through cytologic-histologic correlation.
Materials And Methods:
A retrospective search identified 170 cases of urine cytology cases with concurrent biopsies collected during a 2-year time period at University of Rochester Medical Center. Patient age, sex, smoking history, prior malignancy diagnoses, cystoscopy findings, specimen collection method, UroVysion results, and 1-year follow-up of surgical pathology cases were included.
Results:
Cytologic-histologic correlation was identified in 59% of cases, with 18% true positives and 41% true negatives. Discordant results were identified in 41% of cases; of these, 4% were false positives, 11% false negatives, 12% potential sampling bias, and 14% were low-grade urothelial carcinoma (LGUC). The analysis of this 2-year study finds a positive predictive value of urine cytology for HGUC to be 81%, a negative predictive value of 79%, a sensitivity of 61%, a specificity of 91%, and an accuracy of 79%.
Conclusions:
Our results support TPS's ability to improve the reliability and accuracy of interpretations in urine cytology for HGUC. Nevertheless, additional studies are essential to improve the diagnostic accuracy of LGUN, and urine adequacy, in order to improve patient care and early detection, while identifying potential sampling bias.
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