Multiple prognostic models exist to assess survival among patients with metastatic clear cell renal cell carcinoma (m-ccRCC). However, the relative contribution of histopathologic features of the metastasis has not been extensively studied. Herein, we compared models using clinical, primary tumor, and metastatic features to predict cancer-specific survival (CSS) for patients with surgically resected m-ccRCC.
We studied 266 patients who had undergone nephrectomy between 1970 and 2019 and who had a single site of metastasis completely resected. Two versions of the m-ccRCC score published by Leibovich et al were calculated: using grade and necrosis from the primary tumor and using grade and necrosis from the metastasis. Predictive abilities of these 2 versions and a third model that included metastatic features only were compared using c-indexes from Cox proportional hazards models.
A total of 197 patients died from RCC at a median of 2.3 years (IQR 1.1-4.5); median follow-up among survivors was 13.2 years (IQR 10.0-14.5). The Leibovich score using grade and necrosis from the metastasis (c=0.679) had similar predictive ability compared to the original Leibovich score using grade and necrosis from the primary tumor (c=0.675). A third model (c=0.707) demonstrated that metastasectomy within 2 years after nephrectomy, presence of bone metastasis, high grade, and sarcomatoid differentiation in the metastasis were significantly associated with CSS.
Scoring algorithms calculated using histopathologic features of the metastasis can be used to predict CSS for patients with surgically resected m-ccRCC. These findings are of particular importance for instances when primary tumor histopathology is not readily available.
The Journal of urology. 2023 Jun 20 [Epub ahead of print]
Rodrigo Rodrigues Pessoa, Reza Nabavizadeh, Fernando Quevedo, Daniel D Joyce, Christine M Lohse, Vidit Sharma, Brian A Costello, Stephen A Boorjian, R Houston Thompson, Bradley C Leibovich, John C Cheville
Department of Urology, Mayo Clinic, Rochester, Minnesota., Division of Medical Oncology, Mayo Clinic, Rochester, Minnesota., Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota., Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota.