.png)
194 – Contributed Oral Poster Presentations: Biometrics Section
Kaplan-Meier Method in Tumor Size Doubling Time Estimation
Yufeng Li
University of Alabama at Birmingham
Hui-Chien Kuo
University of Alabama at Birmingham
Choo Hyung Lee
University of Alabama at Birmingham
Patsy Oliver
University of Alabama at Birmingham
Donald Buchsbaum
University of Alabama at Birmingham
The assessment of tumor response to treatment is a typical task of experimental cancer research. Usually tumor growth delay data in vivo consist of at least two groups of animals: control and treatment. Tumor Doubling Time (TDT) is widely used for quantification of tumor growth rate for prognostic purposes and can quantify therapeutic effects of different treatment modalities. Some studies assume that the growth of an unperturbed tumor follows the Gompertz curve, and the TDT is determined from two volume estimations with measurement time intervals using the first derivative of the Gompertz model; others assume that tumor growth follows an exponential function and TDT is estimated with a nonlinear function. However, in the case of the Xenograft Tumor Model, neither models fit the tumor growth with different treatment strategy, so that the TDT will have a biased estimation. Thus we investigate using model free Kaplan-Meier estimates in TDT estimation. The simulation results show that the KM method in TDT estimation is more robust than other model based methods. The KM method can also provide a comparison between treatments in TDT simultaneously.