TY - DATA T1 - Dataset for: Multivariate joint frailty model for the analysis of nonlinear tumor kinetics and dynamic predictions of death PY - 2018/05/07 AU - Agnieszka Król AU - Christophe Tournigand AU - Stefan Michiels AU - Virginie Rondeau UR - https://wiley.figshare.com/articles/dataset/Dataset_for_Multivariate_joint_frailty_model_for_the_analysis_of_nonlinear_tumor_kinetics_and_dynamic_predictions_of_death/5857752 DO - 10.6084/m9.figshare.5857752.v1 L4 - https://ndownloader.figshare.com/files/10397553 KW - Joint modeling KW - Longitudinal data KW - Ordinary differential equation KW - Survival analysis KW - Tumor measurement KW - Statistics KW - Medicine N2 - The RECIST criteria are used as standard guidelines for the clinical evaluation of cancer treatments. The assessment is based on the anatomical tumor burden: change in size of target lesions and evolution of non-target lesions (NTL). Despite unquestionable advantages of this standard tool, RECIST are subject to some limitations such as categorization of continuous tumor size or negligence of its longitudinal trajectory. In particular, it is of interest to capture its nonlinear shape and model it simultaneously with recurrent progressions of NTL and overall survival. We propose a mechanistic joint frailty model for longitudinal data, recurrent events and a terminal event. In the model, the tumor size trajectory is described using an ordinary differential equation that accounts for the natural growth and treatment-induced decline. We perform a simulation study to validate the method and apply the model to a phase III clinical trial in colorectal cancer. In the results of the analysis, we determine on which component, tumor size, NTL or death, the treatment acts mostly and perform dynamic predictions of death. We compare the model with other models that consider parametric functions or splines for the tumor size trajectory in terms of goodness-of-fit and predictive accuracy. ER -