Presentation Authors: Emily L Davidson*, Madison, WI, Viraj A. Master, Atlanta, GA, Jay D. Raman, Brian Sohl, Hershey, PA, Daniel D. Shapiro, Madison, WI, Dattatraya Patil, Atlanta, GA, Glenn O. Allen, E Jason Abel, Madison, WI
Introduction: Although platelet count is a well described risk factor for progression of other cancers, the prognostic value has not been described for non-metastatic renal cell carcinoma (RCC). The purpose of this study was to evaluate the association of preoperative platelet count with recurrence in high risk non-metastatic RCC following surgery at 3 institutions.
Methods: Clinical and pathologic data was collected from â‰¥pT3a non-metastatic RCC patients treated surgically at 3 independent centers from 2000-2016. Univariate and multivariate Cox proportional hazard models were used to identify associations of recurrence with preoperative platelet count or other reported risk factors.
Results: Of 1,074 patients at 3 institutions, 278 (25.9%) had RCC recurrence at median of 9.9 months (IQR 4.3-21.1) following attempted curative surgery. Median overall follow-up for patients without recurrence was 19.3 months (IQR 4.6â€“49.0). Data for preoperative platelet count was available for 98% of patients._x000D_
Platelet count as a continuous variable was associated with recurrence in each cohort on independent analysis (p=0.002, p=0.003, p=0.006). Cut point analysis was performed and PC >250K was chosen as a dichotomous variable associated with risk of recurrence (HR 1.8, 95%CI 1.4-2.3, p < 0.001)_x000D_
Using combined population (n=1074), a multivariate Cox model evaluated the association of recurrence with platelet count >250K or other independent prognostic factors including: nuclear grade, tumor diameter, sarcomatoid features, preoperative hemoglobin, and presence of tumor thrombus. Platelet count >250K was independently predictive of recurrence (HR 1.5, 95%CI 1.1-2.0, p=0.01).
Conclusions: Elevated preoperative platelet count is independently predictive of recurrence in high risk RCC patients. Integration of platelet count into risk stratification models may help identify patients who benefit from adjuvant therapy or clinical trial enrollment.