Personalized Schedules for Surveillance of Low Risk Prostate Cancer Patients

11/01/2017
by   Anirudh Tomer, et al.
0

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.

READ FULL TEXT
research
07/12/2019

Personalized Decision Making for Biopsies in Prostate Cancer Active Surveillance Programs

Background: Low-risk prostate cancer patients enrolled in active surveil...
research
07/27/2021

Longitudinal Latent Overall Toxicity (LOTox) profiles in osteosarcoma: a new taxonomy based on latent Markov models

In cancer trials, the analysis of longitudinal toxicity data is a diffic...
research
05/06/2018

Automated Diagnosis of Clinic Workflows

Outpatient clinics often run behind schedule due to patients who arrive ...
research
08/31/2022

Personalized Biopsy Schedules Using an Interval-censored Cause-specific Joint Model

Active surveillance (AS), where biopsies are conducted to detect cancer ...
research
02/21/2023

Estimating the optimal time to perform a PET-PSMA exam in prostatectomized patients based on data from clinical practice

Prostatectomized patients are at risk of resurgence: this is the reason ...
research
05/16/2018

Joint longitudinal and time-to-event models for multilevel hierarchical data

Joint modelling of longitudinal and time-to-event data has received much...

Please sign up or login with your details

Forgot password? Click here to reset