Baseline and treatment effect heterogeneity for survival times between centers using a random effects accelerated failure time model with flexible error distribution.
Nowadays, most clinical trials are conducted in different centers and even in different countries. In most multi-center studies, the primary analysis assumes that the treatment effect is constant over centers. However, it is also recommended to perform an exploratory analysis to highlight possible center by treatment interaction, especially when several countries are involved. We propose in this paper an exploratory Bayesian approach to quantify this interaction in the context of survival data. To this end we used and generalized a random effects accelerated failure time model. The generalization consists in using a penalized Gaussian mixture as an error distribution on top of multivariate random effects that are assumed to follow a normal distribution. For computational convenience, the computations are based on Markov chain Monte Carlo techniques. The proposed method is illustrated on the disease-free survival times of early breast cancer patients collected in the EORTC trial 10854.
Komárek
Arnost
A
Biostatistical Centre, Katholieke Universiteit Leuven, Kapucijnenvoer 35, 3000 Leuven, Belgium.
Lesaffre
Emmanuel
E
Legrand
Catherine
C
D000971:Antineoplastic Combined Chemotherapy Protocols / Q000627:therapeutic use; D001499:Bayes Theorem; D015982:Bias; D001699:Biometry / Q000379:methods; D001943:Breast Neoplasms / Q000188:drug therapy / Q000401:mortality; D005060:Europe / Q000453:epidemiology; D006801:Humans; D008137:Longitudinal Studies; D008390:Markov Chains; D009010:Monte Carlo Method; D015337:Multicenter Studies as Topic / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D019990:Perioperative Care; D012016:Reference Values; D012107:Research Design; D013019:South Africa / Q000453:epidemiology; D013029:Space-Time Clustering; D016008:Statistical Distributions; D016019:Survival Analysis; D013995:Time; D016896:Treatment Outcome