Modelling associations between time-to-event responses in pilot cancer clinical trials using a Plackett-Dale model.
This work was motivated by the need to find surrogate endpoints for survival of patients in oncology studies. The goal of this article is to determine associations between five time-to-event outcomes coming from three clinical trials for non-small cell lung cancer. To this end, we propose to use the multivariate Dale model for time-to-event data introduced by Tibaldi et al. (Stat. Med. 2003). We fit the model to these data, using a pseudo-likelihood approach to estimate the model parameters. We evaluate and compare the performance of different dimensional models and we relate the Dale model association parameter, i.e. the odds ratio, to well-known quantities such as Kendall's tau and Spearman's rho. Finally, the results are discussed with a perspective on surrogate marker validation. Some suggestions are made regarding further studies in this field.
Tibaldi
Fabián
F
Center for Statistics, Limburgs Universitair Centrum, Transnationale Universiteit Limburg, Universitaire Campus, Diepenbeek B3590, Belgium. fabian.tibaldi@luc.ac.be
Barbosa
Franz Torres
FT
Molenberghs
Geert
G
D000276:Adjuvants, Immunologic / Q000494:pharmacology; D015415:Biomarkers; D019496:Cancer Vaccines / Q000009:adverse effects / Q000276:immunology / Q000627:therapeutic use*; D002289:Carcinoma, Non-Small-Cell Lung / Q000276:immunology / Q000628:therapy*; D004815:Epidermal Growth Factor / Q000276:immunology; D006801:Humans; D016013:Likelihood Functions; D008175:Lung Neoplasms / Q000276:immunology / Q000628:therapy*; D008875:Middle Aged; D018448:Models, Immunological; D015233:Models, Statistical; D015999:Multivariate Analysis; D010865:Pilot Projects; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D016019:Survival Analysis
D000276:Adjuvants, Immunologic; D015415:Biomarkers; D019496:Cancer Vaccines; D004815:Epidermal Growth Factor