Predicting time to castration resistance in hormone sensitive prostate cancer by a personalization algorithm based on a mechanistic model integrating patient data

Prostate cancer (PCa) is a leading cause of cancer death of men worldwide. 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.

A mathematical mechanistic model for HSPC progression and treatment was developed based on the underlying disease dynamics (represented by prostate-specific antigen; PSA) as affected by ADT. Following fine-tuning by a dataset of ADT-treated HSPC patients, the model was embedded in an algorithm, which predicts the patient's time to biochemical failure (BF) based on clinical metrics obtained before or early in-treatment.

The mechanistic model, including a tumor growth law with a dynamic power and an elaborate ADT-resistance mechanism, successfully retrieved individual time-courses of PSA (R(2)  = 0. 783). Using the personal Gleason score (GS) and PSA at diagnosis, as well as PSA dynamics from 6 months after ADT onset, and given the full ADT regimen, the personalization algorithm accurately predicted the individual time to BF of ADT in 90% of patients in the retrospective cohort (R(2)  = 0. 98).

The algorithm we have developed, predicting biochemical failure based on routine clinical tests, could be especially useful for patients destined for short-lived ADT responses and quick progression to CRPC. Prospective studies must validate the utility of the algorithm for clinical decision-making. Prostate © 2015 Wiley Periodicals, Inc.

The Prostate. 2015 Sep 30 [Epub ahead of print]

Moran Elishmereni, Yuri Kheifetz, Ilan Shukrun, Graham H Bevan, Debashis Nandy, Kyle M McKenzie, Manish Kohli, Zvia Agur

Institute for Medical Biomathematics (IMBM), Bene Ataroth, Israel. , Optimata Ltd. , Bene Ataroth, Israel. , Optimata Ltd. , Bene Ataroth, Israel. , Mayo Clinic, Rochester, Minnesota. , Mayo Clinic, Rochester, Minnesota. , Mayo Clinic, Rochester, Minnesota. , Mayo Clinic, Rochester, Minnesota. , Institute for Medical Biomathematics (IMBM), Bene Ataroth, Israel.



Newsletter subscription

Free Daily and Weekly newsletters offered by content of interest

The fields of GU Oncology and Urology are rapidly advancing. Sign up today for articles, videos, conference highlights and abstracts from peer-review publications by disease and condition delivered to your inbox and read on the go.