Model-based Prediction of Progression-Free Survival for Combination Therapies in Oncology

M. Baaz, T. Cardilin, M. Jirstrand. 31st PAGE Meeting, A Coruña, Spain, 27-30 June 2023.


Progression-free survival (PFS) is a clinical metric for comparing similar oncology treatments. Using RECIST v1.1 tumor lesions are classified as target or non-target lesions [1]. A patient’s PFS time is set by target progression (TP) if there is at least a 20% and 5 mm increase of the sum of the largest target lesions’ diameters (SLD) compared to the nadir or by non-target progression (NTP) if the non-target lesions are qualitatively proliferating. Patients are right censored if neither event occur prior trial departure. We present a nonlinear mixed effects joint modeling approach for predicting PFS for combination therapies building upon the model by Yu et al [2]. The model links the risk of progression events, such as tumor metastasis or death, with the rate of change of SLD. We calibrate the model with data (ProjectDataSphere) from a clinical study comparing FOLFOX (N=127) to panitumumab (pani) every 2 weeks + FOLFOX (N=121) in WT RAS mutated mCRC patients [3,4].

Photo credits: Nic McPhee