Collection of Biostatistics Research Archive

Title

Studying the Optimal Scheduling for Controlling Prostate Cancer under Intermittent Androgen Suppression

Authors

Sunil K. Dhar, Center for Applied Mathematics and Statistics and the Department of Mathematical Sciences, New Jersey Institute of TechnologyFollow
Hans R. Chaudhry, Vetha Center of Transdisciplinary Studies, NJII, NJITFollow
Bruce G. Bukiet, Center for Applied Mathematics and Statistics and the Department of Mathematical Sciences, New Jersey Institute of TechnologyFollow
Zhiming Ji, Department of Mechanical and Industrial Engineering, NJITFollow
Nan Gao, Department of Biological Sciences, Rutgers, The State University of New JerseyFollow
Thomas W. Findley, Cancer Institute of New Jersey, Physical Medicine, New Jersey Medical School, Rutgers, the State University of New JerseyFollow

Comments

• We observe from this study that much more than majority of the patients’ correlation between PSA and that of Testosterone during ON treatment period is at least 0.90.
• We come up with optimal duration between ON and OFF treatment in days.
• If his PSA level is low during ON treatment, when the patients therapy is stopped then the number of days during OFF treatment should be such that ON treatment days plus OFF treatment (during treatment Cycle 1) should be no more than 541 days.

Abstract

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.

Disciplines

Applied Statistics | Biomedical Engineering and Bioengineering | Biostatistics | Clinical Trials | Longitudinal Data Analysis and Time Series | Male Urogenital Diseases | Multivariate Analysis | Therapeutics

Suggested Citation

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.
https://biostats.bepress.com/harvardbiostat/paper214