Colorectal CancerPCSNaPNCT05383976
Improving Colorectal Cancer Screening in Racially Diverse Zip Codes Using Navigation and Machine Learning (PCSNaP)
An observational study of Colorectal Cancer, run by Abramson Cancer Center at Penn Medicine at 1 site in United States.
Trial summary
The overarching goal of the "PCSNaP" Research Study is to support the Abramson Cancer Center (ACC) of the University of Pennsylvania in carrying out its mission to increase colorectal cancer (CRC) screening completion among high-risk individuals living in a persistent poverty county by designing, conducting… Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Colorectal Cancer
- What is being tested?
- Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation Program
- How many people
- 385 participants
- Where
- 1 siteUnited States
- Study dates
- 29 Mar 2022to 1 Nov 2024
- Phase
- Observational
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: The cohort will consist of patients residing in 18 zip codes in Western and Southwestern Philadelphia who have primary care providers in 4 Penn Medicine Internal Medicine practices and 3 Penn Medicine Family Medicine Practices. Patients will have had a colonoscopy order placed in the past 6 months and have not scheduled, cancelled, or no-showed to their colonoscopy.
Who may be able to join
- Patients residing in 18 zip codes in Western and Southwestern Philadelphia who have primary care providers in 4 Penn Medicine Internal Medicine practices and 3 Penn Medicine Family Medicine Practices
- Patients who have had a colonoscopy order placed in the past 6 months and have not scheduled, cancelled, or no-showed to their colonoscopy
Who cannot join
- Not applicable
Trial locations and contacts
1 site in 1 country.
United States1 site
University of Pennsylvania
Philadelphia, Pennsylvania, 19104
About this study
Official title: A Feasibility Study to Improve Colorectal Cancer Screening Among Racially Diverse Zip Codes in a Persistent Poverty County Using Navigation and Machine Learning Predictive Algorithms
The overarching goal of the "PCSNaP" Research Study is to support the Abramson Cancer Center (ACC) of the University of Pennsylvania in carrying out its mission to increase colorectal cancer (CRC) screening completion among high-risk individuals living in a persistent poverty county by designing, conducting, disseminating and evaluating an electronic health record-based automated identification program to target effective, culturally-sensitive CRC screening navigation to individuals who have not completed an ordered colonoscopy or fecal immunochemical test (FIT).
Read the detailed description
Specifically, the goals of this study are to: 1) Adapt a previously validated electronic health record (EHR)-based machine learning algorithm to predict colorectal cancer (CRC) detection by retraining the model using data from patients seen in primary care clinics serving zip codes with a high proportion of racial and ethnic minorities living in Philadelphia County, a persistent poverty county; and 2) Implement and evaluate the feasibility and effectiveness of an algorithm-based CRC navigation program to increase colorectal cancer screening among patients in Philadelphia county who are at high risk of CRC and have uncompleted colonoscopies.
Together, these novel projects aim to be the first to combine use of machine learning algorithms and patient navigation to increase guideline-based cancer screening in order to reduce the burden of CRC among high-risk individuals living in a persistent poverty county through targeted, culturally-sensitive navigation that addresses social factors that prevent CRC screening.
- Conditions
- Colorectal Cancer
- Being tested
- Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation Program
- Medical subject headings
- Colorectal Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation ProgramOther
This intervention will utilize the existing Penn Medicine CRC patient navigation program. There will be a monthly list of patients with unfilled coloscopies provided, that are risk-stratified according to the machine learning algorithm and select high-risk criteria. The navigation team will prioritize timely outreach and navigation to high-risk patients according to a script that communicates risk.
| Study group | Role | What they receive |
|---|---|---|
| Patients Residing in 18 zip codes in Western and Southwestern Philadelphia | The cohort will consist of patients residing in 18 zip codes in Western and Southwestern Philadelphia who have primary care providers in 4 Penn Medicine Internal Medicine practices and 3 Penn Medicine Family Medicine Practices. Receives: Other: Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation Program |
What is being measured
The primary outcome is the main question the study is designed to answer.
Enrollment in Navigator Program (Feasibility)
Number of patients that participate in the navigation program
Measured: During the three month enrollment period
Completion of Colorectal Cancer Screening
Number of patients that have completed their colonoscopy or Fecal Immunochemical Test (FIT)
Measured: Within the three month enrollment period and three month follow-up period
Number of Participants With Adenoma Detection
Rate of adenomas after completion of colonoscopy
Measured: Within the three month enrollment period and three month follow-up period
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 May 2022
- Study start29 Mar 2022
- Primary completion1 Nov 2024
- Study completion1 Nov 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Other trials for Colorectal CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 385 participants (actual)
Sponsor and investigators
- Lead sponsor
- Abramson Cancer Center at Penn Medicine
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Carmen E. Guerra, MD, MSCE, FACP, Abramson Cancer Center at Penn Medicine
- Investigators
- Carmen Guerra, MD, Principal investigator, University of Pennsylvania
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05383976
- Sponsor's protocol ID
- UPCC 09222
- Other IDs
- 850205
- Acronym
- PCSNaP
- Status last verified
- Nov 2024
- First submitted
- 17 May 2022
- Last updated
- 11 Feb 2026
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 11 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Feasibility Study to Improve Colorectal Cancer Screening Among Racially Diverse Zip Codes in a Persistent Poverty County Using Navigation and Machine Learning Predictive Algorithms
- ClinicalTrials.gov ID
- NCT05383976
- Acronym / sponsor ID
- PCSNaP / UPCC 09222
- Conditions
- Colorectal Cancer
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 385 participants (actual)
- Lead sponsor
- Abramson Cancer Center at Penn MedicineUniversity, hospital or other
- Study start
- 29 Mar 2022 (actual)
- Primary completion
- 1 Nov 2024 (actual)
- Study completion
- 1 Nov 2024 (actual)
- First posted
- 20 May 2022 (actual)
- Results
- Posted 11 Feb 2026
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The overarching goal of the "PCSNaP" Research Study is to support the Abramson Cancer Center (ACC) of the University of Pennsylvania in carrying out its mission to increase colorectal cancer (CRC) screening completion among high-risk individuals living in a persistent poverty county by designing, conducting, disseminating and evaluating an electronic health record-based automated identification program to target effective, culturally-sensitive CRC screening navigation to individuals who have not completed an ordered colonoscopy or fecal immunochemical test (FIT).
Detailed description
Specifically, the goals of this study are to: 1) Adapt a previously validated electronic health record (EHR)-based machine learning algorithm to predict colorectal cancer (CRC) detection by retraining the model using data from patients seen in primary care clinics serving zip codes with a high proportion of racial and ethnic minorities living in Philadelphia County, a persistent poverty county; and 2) Implement and evaluate the feasibility and effectiveness of an algorithm-based CRC navigation program to increase colorectal cancer screening among patients in Philadelphia county who are at high risk of CRC and have uncompleted colonoscopies.
Together, these novel projects aim to be the first to combine use of machine learning algorithms and patient navigation to increase guideline-based cancer screening in order to reduce the burden of CRC among high-risk individuals living in a persistent poverty county through targeted, culturally-sensitive navigation that addresses social factors that prevent CRC screening.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patients Residing in 18 zip codes in Western and Southwestern Philadelphia | – | Other: Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation ProgramThe cohort will consist of patients residing in 18 zip codes in Western and Southwestern Philadelphia who have primary care providers in 4 Penn Medicine Internal Medicine practices and 3 Penn Medicine Family Medicine Practices. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- The cohort will consist of patients residing in 18 zip codes in Western and Southwestern Philadelphia who have primary care providers in 4 Penn Medicine Internal Medicine practices and 3 Penn Medicine Family Medicine Practices. Patients will have had a colonoscopy order placed in the past 6 months and have not scheduled, cancelled, or no-showed to their colonoscopy.
Key inclusion criteria (2 listed)
- Patients residing in 18 zip codes in Western and Southwestern Philadelphia who have primary care providers in 4 Penn Medicine Internal Medicine practices and 3 Penn Medicine Family Medicine Practices
- Patients who have had a colonoscopy order placed in the past 6 months and have not scheduled, cancelled, or no-showed to their colonoscopy
Key exclusion criteria (1 listed)
- Not applicable
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Machine Learning Algorithm with Existing Penn Medicine CRC Patient Navigation ProgramThis intervention will utilize the existing Penn Medicine CRC patient navigation program. There will be a monthly list of patients with unfilled coloscopies provided, that are risk-stratified according to the machine learning algorithm and select high-risk criteria. The navigation team will prioritize timely outreach and navigation to high-risk patients according to a script that communicates risk. | Other | Patients Residing in 18 zip codes in Western and Southwestern Philadelphia |
Primary outcome
Enrollment in Navigator Program (Feasibility)
Time frame: During the three month enrollment period
Number of patients that participate in the navigation program
Completion of Colorectal Cancer Screening
Time frame: Within the three month enrollment period and three month follow-up period
Number of patients that have completed their colonoscopy or Fecal Immunochemical Test (FIT)
Number of Participants With Adenoma Detection
Time frame: Within the three month enrollment period and three month follow-up period
Rate of adenomas after completion of colonoscopy
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Feb 2026.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Carmen Guerra, MD principal investigator
University of Pennsylvania
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Colorectal Cancer, run by Abramson Cancer Center at Penn Medicine at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 11 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 11 Feb 2026). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Enrollment in Navigator Program (Feasibility) (time frame: During the three month enrollment period). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 Feb 2026.