Cancer
Conditions
Keywords
Cancer
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.
Interventions
OTHERAI-assisted MatchMiner Platform
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.
Sponsors
National Cancer Institute (NCI)
Dana-Farber Cancer Institute
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Percentage of Patients Enrolling in Any Dana-Farber Cancer Institute Therapeutic Clinical Trial of Anti-Cancer Systemic Therapy | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Percentage of Patients Consenting to Any Clinical Trial of an Anti-Cancer Systemic Therpay | 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. |
| Percentage of Patients Predicted to Change Treatment Who Enroll in Any Therapeutic Clinical Trial | 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. |
| Number of Patients Having Consultations with the Center for Cancer Therapeutic Innovation (CCTI) | 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. |
| Clinician Opt-Out Rate from Ongoing Email Notifications | 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. |
| Comparison of Anti-Cancer Systemic Therapy Clinical Trial Enrollment Proportions Between AI-Assisted Intervention Arms (Groups 2 and 3) | 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. |
| Percentage of New Systemic Therapy Initiations That Are Clinical Trials of Anti-Cancer Systemic Therapies | 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. |
Countries
United States
Outcome results
None listed