Dana-Farber Cancer Institute
Boston, Massachusetts, 02215, United States
NCT Number: NCT06888089
This study aims to evaluate the effectiveness of proactive notifications to treating oncologist to optimize participant accrual to clinical trials by utilizing the MatchMiner AI platform. This study compares the standard MatchMinder AI access method to two enhanced recruitment methods.
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Notify MeThe goal of this medical record data analysis and health system implementation study is to evaluate the effectiveness of proactive notifications to treating oncologist to optimize participant accrual to clinical trials by utilizing the MatchMiner platform. This study compares the standard MatchMinder access method to two enhanced recruitment methods.
In the first phase, investigators will provide qualitative feedback to improve AI algorithm impact on clinical trial accrual and the delivery of information from the MatchMiner platform that is utilized by treating oncologists and investigators.
In the second phase, medical records identified by the MatchMiner platform as available or a "match" for clinical trial enrollment will be randomized into three cohorts with the randomization occurring at the participant level. In Group 1, treating oncologists can use MatchMiner in its traditional form to identify potential clinical trial candidates based on structured genomic data and cancer type. In Group 2, treating oncologists will automatically receive emails with lists of potential genomically matched clinical trials identified by MarchMiner for patients in whom our AI algorithm detects an elevated probability of changing treatment based on imaging reports; oncologists can also still use traditional MatchMiner workflows. In Group 3, treating oncologists will receive email lists of genomically matched clinical trials identified by Matchminer for patients with AI-detected elevated probability of treatment change, after additional manual review to confirm that patients had progressive diseased based on their imaging reports and did not meet one of the common exclusion criteria for most cancer trials (including uncontrolled brain metastases, multiple primary cancers, poor performance status, lack of measurable disease, already having changed treatment, and hospice enrollment).
Of note, this study was not itself considered a clinical trial during the initial NCI grant application process or on subsequent discussion with NIH staff, since the outcomes were research processes (whether patients enrolled in other therapeutic clinical trials), not health-related patient outcomes as per the NIH definition of a clinical trial. However, for publication, a medical journal determined that the study met ICMJE criteria for a clinical trial and requested that it be registered.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
-≥ 18 years of age
-adults with any type of cancer whose tumors underwent OncoPanel genomic sequencing from 2013-2022
Exclusion criteria
-≤ 18 years of age.
A medical record data analysis tool that uses conjunction machine learning and natural language processing models to predict changes in treatment and prognosis and ascertain progression of disease and metastatic sites using retrospective imaging reports. MatchMiner is an established clinical operations tool at Dana-Farber Cancer Institute that links OncoPanel next-generation sequencing data to basic clinical information and clinical trial eligibility criteria to suggest biomarker-selected therapeutic trials for participants.
Time frame: Up to 18 months
This measure assesses the proportion of patients in each study arm who enroll in any Dana-Farber Cancer Institute (DFCI) therapeutic clinical trial involving anti-cancer systemic therapy during the intervention period. Trial enrollment data will be pulled from the institutional OnCore database.
Time frame: Up to 18 months
Counts the number of patients in each study arm who have at least one consultation with the CCTI at Dana-Farber Cancer Institute during the intervention period. Encounters with the CCTI will be pulled from the institutional Enterprise Data Warehouse.
Time frame: Up to 18 months
Counts the proportion of patients in each study arm who provide consent to participate in any therapeutic clinical trial during the intervention period. Trial consent data will be pulled from the institutional OnCore database.
Time frame: Up to 18 months
Assesses the proportion of patients identified by our AI model as likely to change treatment within the next 30 days who subsequently enroll in any DFCI therapeutic clinical trial involving anti-cancer systemic therapy. Trial enrollment data will be pulled from the institutional OnCore database.
Time frame: Up to 18 months
Determines the proportion of new systemic therapy regimens initiated during the intervention period that are part of a therapeutic clinical trial. New systemic therapy initiations will be pulled from the institutional Enterprise Data Warehouse, and clinical trial enrollment data will be pulled from the institutional OnCore database.
Time frame: Up to 18 months
Measures the percentage of clinicians in each intervention arm (Groups 2 and 3) who opt out of receiving ongoing email notifications from the study. This will be measured using physician survey responses.
Time frame: Up to 18 months
Compares the percentage of patients enrolling in any DFCI therapeutic clinical trial of anti-cancer systemic therapy between Group 2 and Group 3 to evaluate the effectiveness of automated notifications versus notifications after manual review. Trial enrollment data will be pulled from the institutional OnCore database.
Dana-Farber Cancer Institute
Other
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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