Prognostic factors for the survival of patients with papillary renal cell carcinoma:: Meaning of histological typing and multifocality

Purpose: We identified prognostic factors of papillary renal cell carcinoma (PRCC) types 1 (PRCC1) and 2 (PRCC2). Materials and Methods: Between 1985 and 1998, 759 patients underwent surgery for renal cell carcinoma, of whom 88 (11.6%), including 69 males and 19 females with a mean age of 61.8 years (range 21.3 to 85.9) who had PRCC. Multifocality was defined as 2 or greater tumors separated by 10 mm or greater. Small basophilic cells defined PRCC1 and large eosinophilic cells defined PRCC2. Mean followup in 79 cases was 71.1 months (range 1 to 196.6). Survival rates were calculated and statistical analyses were done. Results: The 88 patients underwent radical nephrectomy (65) or conservative surgery (28, that is elective in 17 and imperative in 11). Mean tumor size was 62 mm (range 10 to 190) and 41% of lesions were multifocal, independent of PRCC size, stage, grade or type. Comparing the 56 PRCC1s (63.6%) to the 32 PRCC2s (36.4%) showed that PRCC2 grade and stage were significantly higher (p = 0.024 and 0.025, respectively). A total of 51 patients (64.6%) remained relapse-free and progression-free. Local relapses occurred only after imperative conservative surgery in 2 cases (2.5%). Of the 26 deaths 15 (4 PRCC 1 and 11 PRCC 2) were tumor associated. Mean survival was 26.6 months (range 1 to 112.5). The overall 10-year survival rate was 73% with PRCC1 and PRCC2 10-year rates of 80% and 59%, respectively (p <0.003). Univariate analysis identified stage (p <0.0001), grade (p <0.0001) and histological type (p <0.003) as prognostic factors. Multivariate analysis retained stage (p = 0.006) and grade (p = 0.004). Conclusions: PRCC multifocality was not associated with stage, grade or histological type and it seems not to, be an argument against conservative surgery. Univariate analysis of PRCC prognostic factors identified stage, grade and histological type but the latter was not retained on multivariate analysis.