This retrospective study shows that the majority of patients’ correlations between PSA and Testosterone during the on-treatment period is at least 0.90. Model-based duration calculations to control PSA levels during off-treatment are provided. There are two pairs of models. In one pair, the Generalized Linear Model and Mixed Model are both used to analyze the variability of PSA at the individual patient level by using the variable “Patient ID” as a repeated measure. In the second pair, Patient ID is not used as a repeated measure but additional baseline variables are included to analyze the variability of PSA.
Applied Statistics | Biomedical Engineering and Bioengineering | Biostatistics | Clinical Trials | Longitudinal Data Analysis and Time Series | Male Urogenital Diseases | Multivariate Analysis | Therapeutics
Dhar, Sunil K.; Chaudhry, Hans R.; Bukiet, Bruce G.; Ji, Zhiming; Gao, Nan; and Findley, Thomas W., "Studying the Optimal Scheduling for Controlling Prostate Cancer under Intermittent Androgen Suppression" (January 2017). Harvard University Biostatistics Working Paper Series. Working Paper 214.
Applied Statistics Commons, Biomedical Engineering and Bioengineering Commons, Biostatistics Commons, Clinical Trials Commons, Longitudinal Data Analysis and Time Series Commons, Male Urogenital Diseases Commons, Multivariate Analysis Commons, Therapeutics Commons