AB94. An easy model for prediction of human renal clear cell carcinoma—curve fitting for 3 kidney tumors observed for over 10 years

Objective: To accurately describe the growth of human renal clear cell carcinoma. In our earlier research, the growth model of renal tumors is linear and is not accurate. A better growth model is needed. Methods: There patients under surveillance for more than ten years with renal tumors were analyzed. Tumor size and time were recorded in each observation. Curve fitting of renal tumor growth was performed in Growth model (L=e). Logarithmic transformation was used to linearize the curves. Through linear mixed model, regression analysis was completed with the initial tumor size and observation time as independent variables. Results: Tumor A&B growth rates are 0.32 and 0.25 cm/year with initial tumor sizes 1.30 and 1.60 cm. Tumor C grew faster (0.70 cm/year) with larger initial size (3 cm). All cases are confirmed pathologically to be clear cell carcinoma with volume doubling time (VDT) more than 2 years. The pathological grade of patients A and B is G2, patient C is G1. The growth curve for tumor A is L=e (R=0.980, P<0.001); for tumor B is L=e (R=0.984, P<0.001); for tumor C is L=e (R=0.971, P<0.001). The growth model is InL= 1.101908×InL0+0.0090397×T-0.1478777. The ultimate size of tumor has a significant relationship with initial size (P<0.001) and duration of growth (P<0.001). Conclusions: The growth model of RCC is InL=1.101908 ×InL0+0.0090397×T-0.1478777. The ultimate size of tumor has a significant relationship with initial size (P<0.001) and duration of growth (P<0.001), but more cases are needed to prove the model.