Clinical trial NCT06888089: Deep Clinical Trajectory Modeling to Optimize Accrual to Cancer Clinical Trials
Official title: Deep Clinical Trajectory Modeling to Optimize Accrual to Cancer Clinical Trials
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Cancer
Keywords: Cancer
Lead sponsor: Dana-Farber Cancer Institute
Sponsor class: OTHER
Collaborators: name: National Cancer Institute (NCI)
First posted: 2025-03-21
Enrollment: 20707
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: OTHER

Brief summary: 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.

Detailed description: The 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.

Eligibility criteria: 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.

Primary outcomes:
measure: Percentage of Patients Enrolling in Any Dana-Farber Cancer Institute Therapeutic Clinical Trial of Anti-Cancer Systemic Therapy
timeFrame: Up to 18 months
Secondary outcomes:
measure: Number of Patients Having Consultations with the Center for Cancer Therapeutic Innovation (CCTI)
timeFrame: Up to 18 months
measure: Percentage of Patients Consenting to Any Clinical Trial of an Anti-Cancer Systemic Therpay
timeFrame: Up to 18 months
measure: Percentage of Patients Predicted to Change Treatment Who Enroll in Any Therapeutic Clinical Trial
timeFrame: Up to 18 months
measure: Percentage of New Systemic Therapy Initiations That Are Clinical Trials of Anti-Cancer Systemic Therapies
timeFrame: Up to 18 months
measure: Clinician Opt-Out Rate from Ongoing Email Notifications
timeFrame: Up to 18 months
measure: Comparison of Anti-Cancer Systemic Therapy Clinical Trial Enrollment Proportions Between AI-Assisted Intervention Arms (Groups 2 and 3)
timeFrame: Up to 18 months
Other outcomes:
Locations:
city: Boston
country: United States
facility: Dana-Farber Cancer Institute
state: Massachusetts
Study officials:
affiliation: Dana-Farber Cancer Institute
name: Kenneth Kehl, MD, MPH
role: PRINCIPAL_INVESTIGATOR
References: