Blue-Button Regional Trial Screening

Evaluating the Effectiveness of Blue-Button Automated Clinical Trial Prescreening on Regional Enrollment: a Randomized Trial

Enrollment in clinical trials predicts better survival in the most common cancer types including breast cancer, and testing and proving the efficacy of new treatments relies on successfully conducting clinical trials. However, approximately one fifth of cancer clinical trials fail due to insufficient patient enrollment, and only about 6% of adult cancer patients are enrolled onto clinical trials. Barriers remain for patient participation in clinical trials, especially for cancer patients. One specific barrier is trial identification and awareness of trial availability for both patients and providers.

This trial tests the hypothesis that by integrating clinical trial eligibility screening into part of routine care in a way that requires little effort and by making that screening site agnostic, the Blue-Button matching functionality will increase overall cancer clinical trial enrollment, and may also result in more diverse clinical trial participants that better reflect the U.S. cancer population. Moreover, regardless of changes in enrollment, the Blue-button screening may allow screening to be done more quickly with fewer human resources when compared to current methods. Identification of potential trial opportunities, however, is only the first barrier to trial enrollment, so this study includes additional examination of barriers subsequent to the identification of relevant trials by cataloging patient-level barriers that prevent enrollment of patients in identified trials.

Study Overview

• Status: Enrolling by invitation
• Conditions: Cancer
• Intervention / Treatment: Other: Blue-button screening

Detailed Description

The conduct of cancer clinical trials represents a key final step in testing and proving the efficacy of new treatments relies on successfully conducting clinical trials. However, one in five cancer clinical trials fail due to insufficient patient enrollment, and only about 6% of adult cancer patients are enrolled onto clinical trials, despite the fact that the majority of Americans view clinical trial participation favorably.

The large gap between the willingness of patients to participate in trials and actual trial participate rates suggests the prevalence of many barriers to participation in clinical trials, especially for cancer patients. One specific barrier is trial identification and awareness of trial availability for both patients and providers. Identification and recruitment to clinical trials can be difficult and time consuming. Matching cancer patients with trials requires a challenging amount of manual entry and/or manual review of trials, and frequently this is not integrated into existing clinical workflows. As a result, for many patients, a locally available trial may not be identified, or patients who are eligible to participate may not be asked to enroll. Taken together, only about one in four cancer patients will even have the option to participate in a clinical trial at their institution. Providers do not have the means to easily identify trials for their patients that are conducted outside the treating healthcare institution. One solution to help alleviate this problem is to provide basic site-agnostic trial screening capabilities using electronic health records (EHRs), which already exist in nearly all care settings.

ACS CAN, through a collaboration with the MITRE organization, has developed open-source integrated clinical trial screening functionality ("Blue-button") to address a lack of in-workflow tools for providers to prescreen cancer patients for clinical trials. Blue-button was developed through the Common Oncology Data Elements Extensions (CodeX) application of MITRE's Fast Healthcare Interoperability Resource (FHIR) accelerator (FHIR is a draft data standard developed by HL7 International). The Blue-button functionality works within existing EHRs to enable patients or providers to initiate a prescreen for relevant trials for a given patient within a specified radius of the practice. This is done by automatically extracting and sending eight, deidentified single-patient data elements to existing trial matching services which return potential trial matches. The eight patient data elements used for prescreening, referred to as the optimized patient data elements (OPDE), include age, cancer type, cancer subtype, presence of metastasis, stage, biomarkers, prior treatments, and performance status. The user of the application has the ability to add/edit any of the eight data elements that may be missing or incorrect prior to sending to services. The Blue-button tool (more formally known as the Clinical Trial Matching SMART on FHIR App) then sends the patient OPDE to Minimal Common Oncology Data Elements (mCODE) enabled clinical trial matching services.

Currently, many patients who would be willing to participate in a clinical trial are either not currently being screened or are only screened against limited onsite trials. Thus, the goal of this study is to examine whether the use of a Blue-button trial screening tool can increase the participation of patients in cancer clinical trials. The hypothesis is that the routine use of the site agnostic Blue-button matching functionality will make clinical trial screening easier for both sites and patients. In so doing, its use will not only increase overall cancer clinical trial enrollment but will be especially advantageous for increasing enrollment for historically underrepresented populations, resulting in more diverse clinical trial participants that better reflect the U.S. cancer population. Moreover, regardless of changes in enrollment, the Blue-button screening tool may allow screening to be done more quickly with fewer human resources when compared to current methods. Additionally, because this study follows patients longitudinally over time to record key details about trial decision-making, the study will examine patient-level barriers for individuals eligible for an available trial who decline to participate.

• Study Type: Interventional
• Enrollment (Estimated): 1050
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Florida
    • Tampa, Florida, United States, 33602
      • University of South Florida
  • Texas
    • Dallas, Texas, United States, 75390
      • University of Texas Southwestern Simmons Comprehensive Cancer Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Adult cancer patients attending clinic visit at which they would be screened for clinical trial participation

Exclusion Criteria:

• under age 18 years

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: Standard of Care; Subjects in this arm will receive the standard of care, either routine screening for clinical trials or no screening, according to standard institutional protocol. Potential clinical trials, if identified, will be offered to subjects according to the usual institutional process.
Experimental: Blue-button screening; Subjects assigned to this arm will have deidentified data elements transferred from their EHR to the Blue-button tool for identification of clinical trials for which they may be eligible. After review by clinical research staff, appropriate trials will be offered to subjects.	Other: Blue-button screening; Patients will be screened for clinical trial matches using the Blue-button tool

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Rate of clinical trial participation	To evaluate the effectiveness of an automated clinical trial prescreening tool ("Blue-button") in increasing enrollment in clinical trials compared to standard practice.	Trial participation will be recorded for each patient for the duration of the trial, up to 24 months.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Participant reports on Blue-button tool usability	Providers and research coordinators will complete surveys to report the ease of use of the Blue-button prescreening tool as well as the time and effort involved..	Quarterly surveys of research staff for the duration of the trial, up to 24 months.
Patient reasons for non-enrollment	Patients who are offered matched clinical trials but choose not to enroll will complete a survey describing the reasons for their choice to not enroll.	Surveys will be administered within 15 days (+/- 10 days) after patients inform their provider of their choice not to enroll, through study completion (up to 24 months).

Collaborators and Investigators

• Sponsor: American Cancer Society Cancer Action Network
• Investigators: Principal Investigator: Mark Fleury, PhD, ACS CAN

Publications and helpful links

General Publications

• Zelen M. A new design for randomized clinical trials. N Engl J Med. 1979 May 31;300(22):1242-5. doi: 10.1056/NEJM197905313002203.
• Unger JM, Hershman DL, Till C, Minasian LM, Osarogiagbon RU, Fleury ME, Vaidya R. "When Offered to Participate": A Systematic Review and Meta-Analysis of Patient Agreement to Participate in Cancer Clinical Trials. J Natl Cancer Inst. 2021 Mar 1;113(3):244-257. doi: 10.1093/jnci/djaa155.
• Comis RL, Miller JD, Aldige CR, Krebs L, Stoval E. Public attitudes toward participation in cancer clinical trials. J Clin Oncol. 2003 Mar 1;21(5):830-5. doi: 10.1200/JCO.2003.02.105.
• Fogel DB. Factors associated with clinical trials that fail and opportunities for improving the likelihood of success: A review. Contemp Clin Trials Commun. 2018 Aug 7;11:156-164. doi: 10.1016/j.conctc.2018.08.001. eCollection 2018 Sep.
• Melisko ME, Hassin F, Metzroth L, Moore DH, Brown B, Patel K, Rugo HS, Tripathy D. Patient and physician attitudes toward breast cancer clinical trials: developing interventions based on understanding barriers. Clin Breast Cancer. 2005 Apr;6(1):45-54. doi: 10.3816/CBC.2005.n.008.
• Torgerson DJ, Roland M. What is Zelen's design? BMJ. 1998 Feb 21;316(7131):606. doi: 10.1136/bmj.316.7131.606. No abstract available.
• Unger, JM, and Fleury, ME. Nationally representative estimates of the participation of cancer patients in clinical research studies according to the commission on cancer. Journal of Clinical Oncology 39, no. 28_suppl (October 01, 2021) 74-74
• Unger JM, Vaidya R, Hershman DL, Minasian LM, Fleury ME. Systematic Review and Meta-Analysis of the Magnitude of Structural, Clinical, and Physician and Patient Barriers to Cancer Clinical Trial Participation. J Natl Cancer Inst. 2019 Mar 1;111(3):245-255. doi: 10.1093/jnci/djy221.

Study record dates

Study Major Dates

• Study Start (Actual): December 1, 2023
• Primary Completion (Estimated): December 1, 2025
• Study Completion (Estimated): June 1, 2026

Study Registration Dates

• First Submitted: May 12, 2023
• First Submitted That Met QC Criteria: May 31, 2023
• First Posted (Actual): June 2, 2023

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: January 27, 2025
• Last Verified: January 1, 2025

More Information

Terms related to this study

• Keywords: Cancer clinical trials; clinical trials screening; electronic health records (EHR)
• Other Study ID Numbers: 2018254-4

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: We will share all IPD that underlie results in a publication.
• IPD Sharing Time Frame: Beginning 3 months and ending 3 years after the publication of results
• IPD Sharing Access Criteria: IPD will be shared following review and approval of planned analyses and execution of data sharing agreement.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ICF

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