BACKGROUND: The loss of PBRM1 expression (as identified by immunohistochemistry) is associated with a high risk of postoperative recurrence for patients with clear cell renal cell carcinoma (ccRCC). The authors developed a scoring system to predict recurrence based on clinicopathologic factors incorporating PBRM1 expression. METHODS: This study retrospectively reviewed 479 ccRCC patients who underwent radical surgery between 2006 and 2017. The study extracted a subset of 389 non-metastatic ccRCC patients for whom relevant clinicopathologic factors were available. The primary end point was recurrence-free survival (RFS). The Kaplan-Meier method and the Cox proportional hazards model were used for statistical analysis. Leibovich score, SSIGN score, and University of California, Los Angeles (UCLA) Integrated Staging System were included as conventional prediction models. RESULTS: Of the 389 patients, 53 (13.6%) experienced recurrence during a median period of 61 months. Multivariable analyses showed that that the independent factors for RFS were ≥ pT3 (hazard ratio [HR] 3.64; P < 0.001), sarcomatoid or rhabdoid component (HR 3.29; P = 0.005), PBRM1 negativity (HR 3.39; P = 0.001), and necrosis (HR 3.60; P < 0.001). A scoring system calculated with these factors, named the SSPN (stage, sarcomatoid, PBRM1 expression, and necrosis) score, showed significant differences in RFS among the following four groups; low-risk group (0 factors), intermediate-risk group (1 factor), high-risk group (2 to 3 factors), and very high-risk group (4 factors) (P < 0.001). The authors' model also showed a greater predictive accuracy for 5-year RFS than the conventional models (0.841 vs 0.747-0.792). CONCLUSIONS: The SSPN score, which integrates clinicopathologic findings and PBRM1 expression, can accurately predict postoperative recurrence for patients with non-metastatic ccRCC after radical surgery.
BACKGROUND: The loss of PBRM1 expression (as identified by immunohistochemistry) is associated with a high risk of postoperative recurrence for patients with clear cell renal cell carcinoma (ccRCC). The authors developed a scoring system to predict recurrence based on clinicopathologic factors incorporating PBRM1 expression. METHODS: This study retrospectively reviewed 479 ccRCC patients who underwent radical surgery between 2006 and 2017. The study extracted a subset of 389 non-metastatic ccRCC patients for whom relevant clinicopathologic factors were available. The primary end point was recurrence-free survival (RFS). The Kaplan-Meier method and the Cox proportional hazards model were used for statistical analysis. Leibovich score, SSIGN score, and University of California, Los Angeles (UCLA) Integrated Staging System were included as conventional prediction models. RESULTS: Of the 389 patients, 53 (13.6%) experienced recurrence during a median period of 61 months. Multivariable analyses showed that that the independent factors for RFS were ≥ pT3 (hazard ratio [HR] 3.64; P < 0.001), sarcomatoid or rhabdoid component (HR 3.29; P = 0.005), PBRM1 negativity (HR 3.39; P = 0.001), and necrosis (HR 3.60; P < 0.001). A scoring system calculated with these factors, named the SSPN (stage, sarcomatoid, PBRM1 expression, and necrosis) score, showed significant differences in RFS among the following four groups; low-risk group (0 factors), intermediate-risk group (1 factor), high-risk group (2 to 3 factors), and very high-risk group (4 factors) (P < 0.001). The authors' model also showed a greater predictive accuracy for 5-year RFS than the conventional models (0.841 vs 0.747-0.792). CONCLUSIONS: The SSPN score, which integrates clinicopathologic findings and PBRM1 expression, can accurately predict postoperative recurrence for patients with non-metastatic ccRCC after radical surgery.
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Authors: Samuel Peña-Llopis; Silvia Vega-Rubín-de-Celis; Arnold Liao; Nan Leng; Andrea Pavía-Jiménez; Shanshan Wang; Toshinari Yamasaki; Leah Zhrebker; Sharanya Sivanand; Patrick Spence; Lisa Kinch; Tina Hambuch; Suneer Jain; Yair Lotan; Vitaly Margulis; Arthur I Sagalowsky; Pia Banerji Summerour; Wareef Kabbani; S W Wendy Wong; Nick Grishin; Marc Laurent; Xian-Jin Xie; Christian D Haudenschild; Mark T Ross; David R Bentley; Payal Kapur; James Brugarolas Journal: Nat Genet Date: 2012-06-10 Impact factor: 38.330