Patient Navigation Program to Improve Clinical Trial Enrollment in Cancer Patients

The goal of this clinical trial is to test the utility of patient navigation by comparing high intensity patient navigation to low intensity navigation approaches to improving cancer trial enrollment of patients treated in academic and community cancer centers. Patient navigation is a strategy for increasing patients access to cancer care by helping the participant overcome barriers in the participants communities and within the health care system by providing a bridge between the patient and the health care system. The primary objective of this study is to determine if a high intensity patient navigation program will improve patients enrollment on clinical trial in comparison to a low intensity patient navigation. Participants who agree to participate and are eligible will be randomly assigned to either the high intensity or low intensity approach.

This study is a pilot randomized two arm prospective study of a high versus low intensity patient navigation program with the primary endpoint of clinical trials enrollment rate between the 2 arms. The hypothesis of the study is that a high intensity patient navigation program will improve the enrollment rates on clinical trials. Candidates for this study will already have been identified by the patient navigator as being potentially eligible for a clinical trial. Randomization will be stratified by the type of site: community versus academic. There will be a single futility analysis after approximately 50% of the patients have been randomized and offered a clinical trial. Randomization and data capture will be via REDCap. The primary endpoint of the study is the enrollment rate on clinical trials. With a sample size of 90 and conservatively assuming a clinical trial enrollment among clinical trial eligible patients of 50%, simulations show the investigators would be able to detect a 25% minimum difference (alternative 75% enrollment) in enrollment rates between the two groups with 84% power using a Z test of proportions with a one-sided alpha level of 0.10.