Trial in progress: Evaluating the effectiveness of Blue-button—A tool for institution-agnostic, EHR-integrated regional automated clinical trial prescreening and matching.

TPS1658 Background: Clinical trial enrollment is essential for advancing cancer treatment and improving patient outcomes. Despite the benefits, only 7% of adult cancer patients in the US enroll in clinical trials due to barriers such as limited awareness, the time-intensive nature of manual prescreening and lack of relevant on-site clinical trials. This contributes to insufficient enrollment, causing approximately 20% of trials to fail. Automated prescreening using electronic health records (EHRs) offers a promising solution to streamline trial identification and improve access. This study builds on our published feasibility study (Cancer 2023; doi: 10.1002/cncr.35022 ) that demonstrated the potential of an open-source clinical trial matching tool, developed in collaboration with ACS CAN and MITRE Corporation, to improve locoregional trial identification for patients. Methods: Trial Design: This prospective, randomized, two-arm pilot study is being conducted at two sites: University of Texas Southwestern Medical Center (UTSW), an academic center, and Tampa General Hospital (TGH), a community hospital. Patients are randomized to usual care or an intervention arm utilizing Blue-button, an automated prescreening tool. This SMART-on-FHIR tool automatically extracts deidentified patient data (e.g., cancer type, stage, biomarkers) from the site EHR system and uses them to query external matching services via the FHIR mCODE standard. Using the standard FHIR ResearchStudy resource format, research coordinators review potential trial matches returned within a specified radius of the practice for eligibility and discuss them with patients. At UTSW, this includes prostate, bladder, breast cancer and colon cancer cohorts. At TGH, the trial includes breast, prostate, and colorectal cancers, as well as glioblastoma and multiple myeloma. Statistical Methods:The primary endpoint is the proportion of patients enrolling in trials, comparing intervention and usual care arms. Secondary objectives include evaluating usability, barriers to enrollment, and participant diversity. A total of 1200 patients (600 per arm) will be enrolled, with 81% power to detect a 75% relative increase in enrollment from 9.0% (control) to 15.8% (intervention) at a one-sided alpha of 0.05. Trial Progress:The first phase of the trial addressed institutional approvals, security compliance, and complex server and EHR integrations. The later phase addressed integration of the automated tool into diverse clinical workflows, engagement with site staff and participating patients. Both sites have enrolled approximately 200 patients to date, half on the intervention arm. The final phase will address primary and secondary outcomes as per trial design. Clinical trial information: NCT05885880 .

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.tps1658
Primary Topic
Statistical Methods in Clinical Trials
Type
article
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article

Trial in progress: Evaluating the effectiveness of Blue-button—A tool for institution-agnostic, EHR-integrated regional automated clinical trial prescreening and matching.

Muhammad Shaalan Beg, Salim Semy, Waddah Arafat, Richard Tuli et al.
Journal of Clinical Oncology
Statistical Methods in Clinical Trials
article

Trial in progress: Evaluating the effectiveness of Blue-button—A tool for institution-agnostic, EHR-integrated regional automated clinical trial prescreening and matching.

Muhammad Shaalan Beg, Salim Semy, Waddah Arafat, Richard Tuli, Mujeeb Basit, S. Shriver, Melanie Hullings, Jennifer Burgess, Mark E. Fleury, Joseph M. Unger, Zach Lister, Charles-Michael E. Uzuegbunam, Sarah Bittle
article en

Abstract

TPS1658 Background: Clinical trial enrollment is essential for advancing cancer treatment and improving patient outcomes. Despite the benefits, only 7% of adult cancer patients in the US enroll in clinical trials due to barriers such as limited awareness, the time-intensive nature of manual prescreening and lack of relevant on-site clinical trials. This contributes to insufficient enrollment, causing approximately 20% of trials to fail. Automated prescreening using electronic health records (EHRs) offers a promising solution to streamline trial identification and improve access. This study builds on our published feasibility study (Cancer 2023; doi: 10.1002/cncr.35022 ) that demonstrated the potential of an open-source clinical trial matching tool, developed in collaboration with ACS CAN and MITRE Corporation, to improve locoregional trial identification for patients. Methods: Trial Design: This prospective, randomized, two-arm pilot study is being conducted at two sites: University of Texas Southwestern Medical Center (UTSW), an academic center, and Tampa General Hospital (TGH), a community hospital. Patients are randomized to usual care or an intervention arm utilizing Blue-button, an automated prescreening tool. This SMART-on-FHIR tool automatically extracts deidentified patient data (e.g., cancer type, stage, biomarkers) from the site EHR system and uses them to query external matching services via the FHIR mCODE standard. Using the standard FHIR ResearchStudy resource format, research coordinators review potential trial matches returned within a specified radius of the practice for eligibility and discuss them with patients. At UTSW, this includes prostate, bladder, breast cancer and colon cancer cohorts. At TGH, the trial includes breast, prostate, and colorectal cancers, as well as glioblastoma and multiple myeloma. Statistical Methods:The primary endpoint is the proportion of patients enrolling in trials, comparing intervention and usual care arms. Secondary objectives include evaluating usability, barriers to enrollment, and participant diversity. A total of 1200 patients (600 per arm) will be enrolled, with 81% power to detect a 75% relative increase in enrollment from 9.0% (control) to 15.8% (intervention) at a one-sided alpha of 0.05. Trial Progress:The first phase of the trial addressed institutional approvals, security compliance, and complex server and EHR integrations. The later phase addressed integration of the automated tool into diverse clinical workflows, engagement with site staff and participating patients. Both sites have enrolled approximately 200 patients to date, half on the intervention arm. The final phase will address primary and secondary outcomes as per trial design. Clinical trial information: NCT05885880 .

Journal of Clinical OncologyVol. 43(16_suppl)
American Cancer Society (US), University of South Florida (US), Tampa General Hospital (US), Pancreatic Cancer Action Network (US), Fred Hutch Cancer Center (US), Southwestern Medical Center (US), California Science Center (US), Southwestern Medical Center (US), Mitre (United States) (US), The University of Texas Southwestern Medical Center (US)
Openalex Percentile: Top 88%
Statistical Methods in Clinical Trials
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