Personalized Schedules for Surveillance of Low Risk Prostate Cancer Patients

TL;DR

This paper introduces personalized biopsy scheduling for low risk prostate cancer patients in active surveillance, aiming to reduce unnecessary biopsies and improve compliance by using joint models of PSA levels and biopsy results.

Contribution

It develops a novel method using joint models to personalize biopsy schedules based on individual patient data, improving over fixed schedules.

Findings

Personalized schedules reduce the number of unnecessary biopsies.

The method improves detection timing of cancer progression.

Personalized schedules outperform fixed schedules in simulations.

Abstract

Low risk prostate cancer patients enrolled in active surveillance (AS) programs commonly undergo biopsies on a frequent basis for examination of cancer progression. AS programs employ a fixed schedule of biopsies for all patients. Such fixed and frequent schedules, may schedule unnecessary biopsies for the patients. Since biopsies have an associated risk of complications, patients do not always comply with the schedule, which increases the risk of delayed detection of cancer progression. Motivated by the world's largest AS program, Prostate Cancer Research International Active Surveillance (PRIAS), in this paper we present personalized schedules for biopsies to counter these problems. Using joint models for time to event and longitudinal data, our methods combine information from historical prostate-specific antigen (PSA) levels and repeat biopsy results of a patient, to schedule the next biopsy. We also present methods to compare personalized schedules with existing biopsy schedules.