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Developing a model to predict accrual to cancer clinical trials: Data from an NCI designated cancer center

Praveena Iruku1, Martin Goros2, Jonathan Gelfond2

  • 1Department of Hematology/Oncology, University of Colorado Health, Colorado Springs, CO, USA.

Contemporary Clinical Trials Communications
|August 3, 2019
PubMed
Abstract

Insights

Predicting clinical trial accrual is crucial for cancer centers. A new model identifies factors like sponsor type and trial phase, helping improve accrual rates and resource allocation.

Area of Science:

  • Oncology
  • Clinical Trial Management
  • Biostatistics

Background:

  • Cancer center funding necessitates efficient resource allocation, particularly for clinical trial infrastructure.
  • A significant percentage of clinical trials (20%) fail to meet patient accrual targets, impacting research progress.
  • Identifying factors influencing clinical trial accrual is essential for optimizing institutional performance.

Purpose of the Study:

  • To identify key factors associated with clinical trial patient accrual.
  • To develop a predictive model for clinical trial accrual at a cancer center.

Main Methods:

  • A retrospective analysis of 297 clinical trials conducted between 1999 and 2015 at UT Health Cancer Center San Antonio.
  • Inclusion of both observational and interventional studies, collecting data on study type, malignancy, trial phase, and principal investigator (PI).

Main Results:

  • Several factors significantly correlated with clinical trial accrual, including sponsor type, trial phase, disease category, study type, disease state, and the use of new investigational agents.
  • A predictive model achieved an Area Under the Curve (AUC) of 0.65.
  • Observational, interventional, industry-sponsored trials, and those led by local PIs demonstrated higher likelihoods of meeting accrual goals.

Conclusions:

  • Key factors influencing clinical trial accrual were successfully identified.
  • A predictive model for clinical trial accrual was developed based on these identified factors.
  • The model holds potential to enhance the cancer center's clinical trial portfolio and inform strategic fund allocation.
Keywords:
AccrualCancer centerClinical trialsModelPrediction

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