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Principal Investigator
Ari Robinson
The Institute for Medical BioMathematics (IMBM)
Position Title
Project Manager
About this CDAS Project
PLCO (Learn more about this study)
Project ID
Initial CDAS Request Approval
Oct 22, 2020
Predicting time to castration resistance in hormone sensitive prostate cancer
In hormone-sensitive prostate cancer (HSPC), androgen deprivation therapy (ADT) is widely used, but an eventual failure on ADT heralds the passage to the castration-resistant prostate cancer (CRPC) stage. Because predicting time to failure on ADT would allow improved planning of personal treatment strategy, we aimed to develop a predictive personalization algorithm for ADT efficacy in HSPC patients. The personalization algorithm focused on the clinically meaningful goal of predicting biochemical failure (BF) during therapy, after which patients are typically evaluated for CRPC progression and treated by therapeutics for this terminal stage. The algorithm foresee BF in the retrospective HSPC cohort, by incorporating clinical information at diagnosis (GS and PSA), PSA collected during initial monitoring at the HSPC stage, and the ADT regimen actually applied to the patient.

The specific aim of this project is to train the algorithm on additional prostate cancer patient clinical data and to validate it with independent dataset from the dataset we used at the following paper:


Yuri kogan - The Institute for Medical BioMathematics (IMBM)