Abstract
703 Background: Clinical and pathologic factors alone have limited prognostic ability in patients with metastatic clear cell renal cell carcinoma (ccRCC). We sought to determine if tissue biomarkers, along with our previously reported clinical metastases score, can be used to predict cancer specific survival (CSS) in patients with metastatic ccRCC. Methods: Patients with metastatic ccRCC who underwent nephrectomy between 1990-2004 were identified using the Mayo Clinic Nephrectomy Registry. Sections from paraffin-embedded primary tumor tissue blocks were used for immunohistochemistry staining for PD-1, B7-H1 (PD-L1), B7-H3, Bim (downstream pro-apoptotic signaling molecule in PD-1 pathway), CA-IX, IMP3, Ki67, and survivin. CSS was the primary outcome. Biomarkers that were significantly associated with CSS after adjusting for the metastases score were used to develop a biomarker-specific multivariable model using a bootstrap resampling approach and forward selection. Predictive ability was summarized using a bootstrap-corrected c-index. Results: The cohort included 602 patients, 192 (32%) with metastases at diagnosis and 410 (68%) who developed metastases after nephrectomy. Median follow-up among survivors was 9.6 years (IQR 4.2,12.8) and 504 patients died of RCC. Bim, IMP3, Ki67, and survivin expression were significantly associated with CSS after adjusting for the metastases score and were used to develop a biomarker-specific model. High Bim (HR 1.44; 95%CI 1.16-1.78; p < 0.001), high survivin (HR 1.35; 95%CI 1.08-1.68; p = 0.008), and the metastases score (HR 1.13 per one point; 95%CI 1.10-1.16; p < 0.001) were retained as independent predictors in the final multivariable model (c-index 0.69). Conclusions: We created a prognostic model combining the clinical metastases score and two primary tissue expression biomarkers, Bim and survivin, for patients with metastatic RCC who underwent nephrectomy. External validation will be required prior to clinical use.
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