Impact of the 1998 World Health Organization/International Society of Urological Pathology classification system for urothelial neoplasms of the kidney.
Academic Article
Overview
abstract
The classification of urothelial neoplasms of the kidney traditionally has been similar to that of urinary bladder tumors. Several years ago, the classification of papillary urothelial neoplasms was revised. The current study focuses on the application of the 1998 World Health Organization (WHO)/International Society of Urological Pathology classification system to 102 renal pelvic urothelial neoplasms and compares it to the 1973 WHO classification scheme. In this study, all tumors were classified as urothelial carcinomas, and the majority (85%) were papillary. Most patients with papillary tumors presented with 'superficial' disease (< or = pT1). With the 1998 system, most papillary carcinomas were high grade, and were more often invasive as compared to low-grade tumors. Only 34% were low-grade papillary tumors and, of these, most (93%) were noninvasive. With the 1973 system, most papillary tumors were grade 2 or 3, with invasion more common in grade 3 tumors. By 1973 criteria, grade 2 tumors were a heterogeneous group; with 1998 criteria, nearly one-half were high grade and the other half low grade. The grade of papillary urothelial carcinomas with both the 1973 and 1998 grading methods was associated with stage (P=0.001). Our study reveals that papillomas and papillary urothelial neoplasms of low malignant potential are uncommon tumors in the kidney. Renal pelvic papillary urothelial neoplasms are most often carcinomas and are more commonly high grade than low grade. Although both the 1973 and 1998 systems showed a significant association with tumor stage, grade 2 papillary carcinomas are a heterogeneous group by 1973 criteria. The 1998 system provides useful information in that it more clearly defines a papillary tumor's grade and selects for a group of tumors, namely low-grade papillary urothelial carcinomas, for which a low likelihood of invasion can be predicted.
