Background: Histologic grade is the most important predictor of the clinical outcome of non-muscle invasive (Ta, T1) papillary urothelial carcinoma (NMIPUCa), but its ambiguous criteria diminish its power to predict recurrence/progression for individual patients. We attempted to find an objective and reproducible histologic predictor of NMIPUCa that correlates well with the clinical outcome. Methods: A total of 296 PUCas were collected from the Departments of Surgical Pathology of 11 institutions in South Korea. The clinical outcome was grouped into no event (NE), recurrence (R), and progression (P) categories. All 25 histological parameters were numerically redefined. The clinical pathology of each case was reviewed individually by 11 pathologists from 11 institutions based on the 2004 WHO criteria and afterwards blindly evaluated by two participants, based on our proposed parameters. Univariate and multivariate logistic regression analyses were performed using the R software package. Results: The level of mitoses was the most reliable parameter for predicting the clinical outcome. We propose a four-tiered grading system based on mitotic count (> 10/10 high-power fields), nuclear pleomorphism (smallest-to-largest ratio of tumor nuclei >20), presence of divergent histology, and capillary proliferation (> 20 capillary lumina per papillary core). Conclusions: The level of mitoses at the initial bladder biopsy and transurethral resection (TUR) specimen appeared to be an independent predictor of the Ta PUCa outcome. Other parameters include the number of mitoses, nuclear pleomorphism, divergent histology, and capillary proliferation within the fibrovascular core. These findings may improve selection of patients for a therapeutic strategy as compared to previous grading systems.
|Publication status||Published - 2017 Jul 24|
Bibliographical noteFunding Information:
The Korean Society of Urology Oncology supported the cost for data collection, labor costs, statistical analysis, and publication costs (KUOS 2014-05). Inje University Research Foundation supported labor costs and publication costs (20100557).
© 2017 The Author(s).
All Science Journal Classification (ASJC) codes
- Pathology and Forensic Medicine