AI-informed Screening Navigation for Colorectal Cancer

Age: 18 - 65

Sex: Any

Trial Phase: Academic

Sponsor: Abramson Cancer Center at Penn Medicine

Disqualifiers: Prior CRC, Late-stage cancer, Colectomy, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial explores how artificial intelligence (AI) can improve colorectal cancer (CRC) screening for individuals aged 45-49. The goal is to identify those at higher risk and assist them in completing necessary screenings, such as a fecal test or colonoscopy. Participants will be divided into two groups: one receiving additional support from a trained navigator and the other receiving standard care. Individuals who have not recently undergone CRC screenings and have a primary care provider at Penn Medicine may be suitable candidates. The trial aims to make CRC screening easier and more accessible for those at risk. As an unphased trial, this study offers a unique opportunity to contribute to innovative research that could enhance early detection and prevention strategies for colorectal cancer.

Do I need to stop my current medications for this trial?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What prior data suggests that this AI-informed screening navigation is safe for colorectal cancer screening?

Research has shown that AI is increasingly used to manage colorectal cancer (CRC), enhancing detection and treatment. AI tools can identify individuals at higher risk for CRC and guide them to appropriate screenings.

In terms of safety, this AI-based method improves patient guidance through the screening process. Unlike drugs or surgery, it lacks those treatments' side effects. The primary aim is to ensure high-risk individuals receive screenings, with AI facilitating the process.

Patient navigation, integral to this approach, has been employed in other CRC screening programs. It assists individuals in understanding and completing their screenings by addressing barriers such as scheduling, transportation, and test preparation.

Although specific safety data for this AI-guided navigation is not yet available, AI use in similar contexts has been well-tolerated. Since this trial does not involve a new medical treatment, the risks are minimal compared to typical clinical trials. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores a new way of using AI to improve colorectal cancer screening. Unlike standard options that rely on traditional patient outreach and education, this approach involves a trained navigator who uses AI insights to tailor communication and support. This method aims to overcome common barriers to screening, like misinformation, fear, and logistical challenges, making it more likely that people at increased risk will complete their screenings. By addressing these issues with personalized assistance, this trial could lead to higher screening rates and earlier detection of colorectal cancer.

What evidence suggests that AI-informed colorectal cancer screening navigation is effective for colorectal cancer?

Research has shown that artificial intelligence (AI) can enhance colorectal cancer (CRC) screening by more effectively identifying polyps, which are growths that might develop into cancer. AI aids doctors in detecting these polyps more accurately during procedures like colonoscopies, potentially leading to better health outcomes for patients. In this trial, participants in the intervention arm will receive AI-informed screening navigation with the assistance of a trained CRC navigator. This support program aims to help participants overcome obstacles such as fear, lack of information, or transportation issues. Meanwhile, participants in the control arm will receive standard care without navigator assistance. Overall, combining AI with patient support could make CRC screening more effective and accessible. ^{4 6 7 8 9}

Are You a Good Fit for This Trial?

This trial is for Penn Medicine patients aged 45-49 who haven't been screened for colorectal cancer (CRC). It's designed to help those at higher risk, as determined by machine learning algorithms. To join, individuals must be screening-naive and willing to undergo CRC screening through patient navigation assistance.

Inclusion Criteria

Not up to date with CRC screening within the recommended period of time (colonoscopy within 10 years, FIT within 1 year, Cologuard within 3 years, sigmoidoscopy within 3-5 years)

Have primary care providers in Penn Internal Medicine and Family Medicine Practices

Have at least 1 outpatient CBC in the past 12 months.

Exclusion Criteria

I have had colorectal cancer in the past.

My cancer is in stage 4.

I have had surgery to remove part or all of my colon.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Intervention

Participants receive risk-informed patient navigation to assist in completing either a fecal immunochemical test (FIT) or a colonoscopy

12 months

Ongoing contact with navigator as needed

Control

Participants receive standard of care without navigator assistance

12 months

Follow-up

Participants are monitored for completion of CRC screening and abnormal screening findings

12 months

What Are the Treatments Tested in This Trial?

Interventions

• AI-informed Colorectal Cancer Screening Navigation

Trial Overview The study tests whether a special AI-informed patient navigation can increase CRC screening uptake compared to standard care. High-risk patients will either receive personalized guidance to complete a fecal test or colonoscopy or follow the usual process with potential nurse navigator support.

How Is the Trial Designed?

Group I: Intervention Arm - Navigator Assistance Experimental Treatment 1 Intervention

A trained CRC navigator who will conduct outreach and navigation by interviewing these patients according to a script that consists of a statement of research, confirms eligibility, communicates their relative increased risk of CRC, assesses and addresses barriers to completion of CRC screening, and offers an adapted validated questionnaire regarding these barriers for patients to complete asynchronously. The navigator will be able to address barriers such as lack of awareness/knowledge about screening, misinformation, negative attitudes and fear, scheduling, inability to afford the prep, and lack of transportation and escort. The calls performed by the patient navigator will not be recorded.

Group II: Control Arm - NO Navigator Assistance Active Control 1 Intervention

Patients in the control arm will be enrolled under a waiver. They will only receive standard of care.

Who Is Running the Clinical Trial?

Abramson Cancer Center at Penn Medicine

Lead Sponsor

Trials

425

Recruited

464,000+

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT07230795

AI-informed Colorectal Cancer (CRC) Screening ... We will evaluate the effectiveness of the program on uptake of navigation and completion of CRC screening, rates of abnormal screening results, ...

2. medicine.iu.edu medicine.iu.edu/news/2025/09/colorectal-cancer-screening-personalized-health-data

Informing patients of personal colorectal cancer risks does not ... A study of Indianapolis patients found providing personalized health information did not increase colorectal cancer testing rates.

3. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC10647850/

The Role of Artificial Intelligence in Colorectal Cancer ... AI in colonoscopy holds the potential to advance the detection and characterisation of polyps, addressing current limitations and improving patient outcomes.

4. acsjournals.onlinelibrary.wiley.com acsjournals.onlinelibrary.wiley.com/doi/10.1002/cncr.70121?af=R

Findings from the Accelerating Colorectal Cancer Screening ... This article highlights key challenges and adaptations in implementing patient navigation programs for colorectal cancer screening across ...

5. sciencedirect.com sciencedirect.com/science/article/pii/S2589004225012416

Comprehensive application of artificial intelligence in ... AI is increasingly integrated into the clinical management of colorectal cancer (CRC), playing a role in areas ranging from disease screening and therapy ...

6. clinicaltrials.gov clinicaltrials.gov/study/NCT07230795?aggFilters=status%3A%2Cphase%3A

AI-informed Colorectal Cancer (CRC) Screening ... It identifies the role of the intervention that participants receive. Types of arms include experimental arm, active comparator arm, placebo ...

7. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12272945/

Comprehensive application of artificial intelligence in ... Artificial intelligence (AI) is increasingly integrated into the clinical management of colorectal cancer (CRC), playing a role in areas ranging from disease ...

8. sciencedirect.com sciencedirect.com/science/article/abs/pii/S0749379725006555

Modeling Tradeoffs in Reminder Intensity and Navigation ... Mailed stool testing is effective for increasing colorectal cancer (CRC) screening, which reduces CRC incidence and mortality. To scale up ...

9. formative.jmir.org formative.jmir.org/2024/1/e53224

The Development of a Digital Patient Navigation Tool to ... This study conducts user testing of a digital patient navigation tool, called eNav, designed to support FQHC patients in preparing for, requesting, and ...