Joint Frailty-Copula Models for Tumour Progression and Death in
Meta-Analysis
Description
Fit survival data and perform dynamic prediction under joint frailty-copula models for tumour progression and death.
Likelihood-based methods are employed for estimating model parameters, where the baseline hazard functions are modeled by the cubic M-spline or the Weibull model.
The methods are applicable for meta-analytic data containing individual-patient information from several studies.
Survival outcomes need information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression).
Methodologies were published in
Emura et al. (2017) , Emura et al. (2018) ,
Emura et al. (2020) , Shinohara et al. (2020) ,
Wu et al. (2020) , and Emura et al. (2021) .
See also the book of Emura et al. (2019) .
Survival data from ovarian cancer patients are also available.