Modeling Clinical Failure in Prostate Cancer Patients Based on a Two-stage Statistical Model (PREDYC)

December 30, 2020 updated by: Institut Bergonié

Biomarker series can indicate disease progression and predict clinical endpoints. When a treatment is prescribed depending on the biomarker, confounding by indication might be introduced if the treatment modifies the marker profile and risk of failure.

The two-stage model fitted within a Bayesian Markov Chain Monte Carlo framework is particularly flexible to account for such data. Prostate-specific antigens in prostate cancer patients treated with external beam radiation therapy can be monitored. In the presence of rising prostate-specific antigens after external beam radiation therapy, salvage hormone therapy can be prescribed to reduce both the prostate-specific antigens concentration and the risk of clinical failure, an illustration of confounding by indication. The prognostic value of hormone therapy and prostate-specific antigens trajectory on the risk of failure based on a two-stage model within a Bayesian framework to assess the role of the prostate-specific antigens profile on clinical failure while accounting for a secondary treatment prescribed by indication. the aim of this research is to model prostate specific antigens using a hierarchical piecewise linear trajectory with a random changepoint. Residual prostate-specific antigens variability can be expressed as a function of prostate-specific antigens concentration. Covariates in the survival model can include : hormone therapy, baseline characteristics, and individual predictions of the prostate-specific antigens nadir and timing and prostate-specific antigens slopes before and after the nadir as provided by the longitudinal process.

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

The two-stage modeling approach allows estimation of the regression coefficients in a time-dependent Cox model, while addressing the limitations with the knowledge of the true marker trajectory. In the first stage, the longitudinal process is modeled using a repeated measures component model, such as a random effects model. In the second stage, estimated characteristics of the longitudinal marker trajectory, such as slopes, are included as covariates in a survival model to assess their prognostic value.

Our aim was to highlight the flexibility of a two-stage model fitted within a Bayesian Markov Chain Monte Carlo (MCMC) framework. We applied this model to assess the prognostic value of the prostate-specific antigens (PSA) profile (level and timing of the nadir; pre- and post-nadir slopes) as well as salvage hormonal treatment (HT) on the risk of clinical failure following external beam radiation therapy (EBRT) in the presence of confounding by indication. We first present the longitudinal hierarchical PSA model that we developed earlier. This model was particularly flexible since it allowed us to account for the presence of a random changepoint as well as the modeling of the residual variability as a function of the PSA concentration. We next extend the longitudinal model to a two-stage model by using estimated parameters of the longitudinal process as covariates in a Cox proportional hazards model to assess prognostic factors of clinical failure including baseline characteristics, PSA trajectory, and HT.

Study Type

Observational

Enrollment (Actual)

2384

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • France
      • Bordeaux, France
        • INSERM

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

Male

Sampling Method

Non-Probability Sample

Study Population

Dataset of 2384 men included in three cohorts: University of Michigan, Ann Arbor, MI, USA (UM); Radiation Therapy Oncology Group (RTOG 9406); and William Beaumont Hospital, Detroit, MI, USA.

Description

Inclusion Criteria:

  • clinically localized prostate cancer
  • Clinical stage T1 to T4
  • Node and metastasis negative
  • Treated with external beam radiation therapy (RT).

Exclusion Criteria:

  • Patients with baseline or planned hormonotherapy

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Number of Participants With Clinical Failure After Initiation of Radiotherapy
Time Frame: within 10 years following initiation of radiotherapy
Clinical failure is defined as any of the following events following initiation of radiotherapy: distant metastases, nodal recurrence, or any palpable or biopsy-detected local recurrence three years after radiation; any local recurrence within three years of RT if the most previous PSA was>2 ng/ml; and death from prostate cancer.
within 10 years following initiation of radiotherapy

Secondary Outcome Measures

Outcome Measure
Time Frame
Number of Participants With Initiation of Salvage Therapy After Radiotherapy
Time Frame: within 10 years following initiation of radiotherapy
within 10 years following initiation of radiotherapy

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Institut Bergonié

Collaborators

Institut National de la Santé Et de la Recherche Médicale, France

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2010

Primary Completion (Actual)

January 1, 2017

Study Completion (Actual)

January 1, 2017

Study Registration Dates

First Submitted

June 4, 2019

First Submitted That Met QC Criteria

June 6, 2019

First Posted (Actual)

June 7, 2019

Study Record Updates

Last Update Posted (Actual)

January 25, 2021

Last Update Submitted That Met QC Criteria

December 30, 2020

Last Verified

December 1, 2020

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • IB2010-PREDYC

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

Undecided

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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