title: Effect of censoring due to progressive disease on tumor size kinetic parameter estimates.
abstract: Tumor growth profiles were simulated for 2 years using the Wang and Claret models under a phase 3 clinical trial design. Profiles were censored when tumor size increased >20% from nadir similar to clinical practice. The percent of patients censored varied from 0% (perfect case) to 100% (real-life case). The model used to generate the data was then fit to the censored data using FOCE in NONMEM. The percent bias in the estimated model parameters determined with censored data was compared to the true values. A total of 100 simulation replicates was used. For the Wang model, under clinical conditions (100% censoring), the parameter related to tumor reduction SR was underpredicted by 30% and the parameter related to tumor growth PR was underpredicted by ∼45%. Most of the variance components in the model were within ±20% of the true values. However, biased parameter estimates in the Wang model did not translate to biased tumor size predictions as the mean percent prediction error between true and model predicted tumor size never exceeded 10%. For the Claret model, at 100% censoring, the tumor growth parameter KL was unaffected by censoring. Both tumor shrinkage parameters, KD and λ, were overestimated by ∼20% in both cases. Future research needs to be directed to develop less empirically based models and to use simulation as a way to improve clinical oncology trials designs.
authors.affiliation: Astellas, 1 Astellas Way, Northbrook, IL 60062, USA. peter.bonate@us.astellas.com
authors.forename: Peter L
authors.initials: PL
authors.lastname: Bonate
authors.forename: Ben
authors.initials: B
authors.lastname: Suttle
mesh_terms: D018450:Disease Progression; D005544:Forecasting; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D009369:Neoplasms / Q000737:chemistry / Q000378:metabolism* / Q000473:pathology*