Analyzing the distribution of progression-free survival for combination therapies: A study of model-based translational predictive methods in oncology.
Eur J Pharm Sci
; 203: 106901, 2024 Sep 10.
Article
en En
| MEDLINE
| ID: mdl-39265706
ABSTRACT
Progression-free survival (PFS) is an important clinical metric in oncology and is typically illustrated and evaluated using a survival function. The survival function is often estimated post-hoc using the Kaplan-Meier estimator but more sophisticated techniques, such as population modeling using the nonlinear mixed-effects framework, also exist and are used for predictions. However, depending on the choice of population model PFS will follow different distributions both quantitatively and qualitatively. Hence the choice of model will also affect the predictions of the survival curves. In this paper, we analyze the distribution of PFS for a frequently used tumor growth inhibition model with and without drug-resistance and highlight the translational implications of this. Moreover, we explore and compare how the PFS distribution for combination therapy differs under the hypotheses of additive and independent-drug action. Furthermore, we calibrate the model to preclinical data and use a previously calibrated clinical model to show that our analytical conclusions are applicable to real-world setting. Finally, we demonstrate that independent-drug action can effectively describe the tumor dynamics of patient-derived xenografts (PDXs) given certain drug combinations.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Eur J Pharm Sci
Asunto de la revista:
FARMACIA
/
FARMACOLOGIA
/
QUIMICA
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Países Bajos