Abstract 5169: Simple perioperative algorithm for serum C-reactive protein: A potent, independent, adverse prognostic factor for renal cell carcinoma

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Introduction: Approximately 20 to 30% of patients who undergo nephrectomy with curative intent for kidney cancer will recur and die of the disease. No adjuvant therapy has been shown to reduce the risk of relapse. Risk of recurrence is largely based on T stage, Fuhrman nuclear grade and nodal status allowing the frequency of surveillance to be adjusted based on low, intermediate and high risk categories. Though C-reactive protein (CRP) has long been recognized as an adverse prognostic factor for clear cell renal cell carcinoma (ccRCC), it has not been incorporated into the risk stratification protocols of current adjuvant clinical trials. Methods: Patients with clinically localized (T1-T3N0M0) ccRCC were followed for 1 year postoperatively. Metastases were identified radiographically and mortality confirmed with the social security death registry. Univariate and multivariate binary logistic regression analyses examined 1-year relapse-free survival (RFS) and overall survival (OS) across patient and disease characteristics. Serum CRP levels were measured prior to nephrectomy and approximately one month after surgery. Patients were assigned retrospectively to the pCRP(+) group if the perioperative (either preoperative or postoperative) serum CRP level was >10 mg/L. All others were assigned to the pCRP(−) group. Results: Of the 109 patients in the study, 17 patients (15.6%) developed metastases and 6 died (5.5%). The pCRP algorithm was employed to ascertain risk of recurrence with 25 patients assigned to the high risk category and 84 patients to the low risk category. Fourteen of 25 patients in the pCRP(+) group recurred at 1 year including all 6 who died. Only 3 of the remaining 84 patients in the pCRP(−) group recurred with no deaths. The sensitivity and specificity of the pCRP algorithm for metastasis were 82% and 88%, respectively, with a positive predictive value (PPV) of 56% and a negative predictive value (NPV) of 96%. The sensitivity and specificity of the pCRP algorithm for mortality were 100% and 82%, respectively, with a PPV of 24% and a NPV of 100%. The p values for metastasis and mortality were both <0.0001. The pCRP algorithm appears to be independent of T-stage and Furhman nuclear grade. Conclusions: When applied retrospectively, the pCRP algorithm accurately identified patients among those considered to be at low risk of recurrence whose actual risk was, in fact, extremely high. The pCRP algorithm also identified patients considered to be at high risk whose actual risk may be somewhat lower. The high NPV of the pCRP algorithm may allow patients in the pCRP(−) group to be spared the potential toxicity and expense of adjuvant therapy. External validation of the pCRP algorithm is needed to establish CRP as a clinically relevant biomarker with a potential role as a novel therapeutic target for ccRCC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5169. doi:10.1158/1538-7445.AM2011-5169