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Colorectal NeoplasmsNCT07261059

AI-assisted Integrated Care to Promote Colonoscopy Uptake

A study testing AI-assisted integrated care in people with Colorectal Neoplasms and Colonoscopy, run by Fudan University.

Not yet recruiting

Opening soon. The study is approved but enrolment has not started yet. Sites may already take enquiries.

Sites and contacts
Official record
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Trial summary

Colorectal cancer (CRC) ranks the second most common cancer and the fourth leading cause of cancer-related deaths in China. Early screening of CRC has been proven to reduce the incidence and mortality, with colonoscopy as the gold standard for CRC screening. Read more about this study

Who is it for?
Ages 40 to 64 yearsHealthy volunteers can take part
Conditions the study is for
Colorectal Neoplasms, Colonoscopy
What is being tested?
AI-assisted integrated care
Could I receive a placebo?
No, everyone receives an active treatment
How many people
400 participants
Where
No sites listed yet
Study dates
8 Dec 2025to Dec 2026
Phase
Interventional
Are there results?
Not yet: the study is under way

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 40 to 64 years
  • All sexes
  • Healthy volunteers accepted
  • Adult

Who may be able to join

  • Individuals who test positive on either the Colorectal Cancer Risk Assessment Scale or the fecal immunochemical test (FIT);
  • Aged 40 ~ 64 years;
  • Proficient in smartphone use and able to engage with the intervention;
  • Provided informed consent .

Who cannot join

  • History of colorectal cancer;
  • Contraindications to colonoscopy,(e.g. severe cardiac, cerebral, lung diseases, or renal dysfunction).

Trial locations and contacts

No sites are listed yet. Contact the study team or a site near you to ask about taking part.

Zhiyuan Hou, PhD contact

86+21 54231112

zyhou@fudan.edu.cn

About this study

Official title: Artificial Intelligence-assisted Integrated Care to Promote Colonoscopy Uptake in China: a Cluster Randomized Controlled Trial

Colorectal cancer (CRC) ranks the second most common cancer and the fourth leading cause of cancer-related deaths in China. Early screening of CRC has been proven to reduce the incidence and mortality, with colonoscopy as the gold standard for CRC screening. This trial aims to evaluate the effectiveness of artificial intelligence-assistant integrated care for improving uptake rate of colonoscopy among high-risk individuals aged 40 to 64 in China. It's a two-arm, parallel cluster randomized controlled trial. The main question it aims to answer is whether the AI-assisted integrated care influence participants' screening-related knowledge, health beliefs, behavioral intention, and uptake of colonoscopy.

Participants will:

  1. Be recruited and allocated into one of two groups according to the assigned clusters. Participants in one group will be invited to receive usual specialty care. In addition to usual specialty care, participants in the other group will receive AI-assisted integrated care provided by specialist and general practitioners collaboratively.
  2. Complete a questionnaire survey on their knowledge, health beliefs, behavioral intention on CRC screening.
  3. Have their colonoscopy status checked at the middle and end of trial.
Read the detailed description

We will conduct a two-arm, cluster randomized controlled trial to evaluate the effectiveness of an AI-assisted integrated care (AICC) model in improving colonoscopy uptake rate among high-risk individuals aged 40-64. This will be followed by a pragmatic implementation science study to assess user engagement of AICC and identify the facilitators and barriers to its real-world implementation.

Sample size calculation, based on detecting an increase in colonoscopy uptake from 15% to 30% with 80% power (α=0.05, two-sided), an ICC of 0.05, and 10 participants per cluster, indicates a need for 18 clusters per arm. Allowing for 10% attrition, the final sample size is determined to be 20 clusters per arm. Thus, a total sample size is 400 participants from 40 clusters.

Participant recruitment will be conducted across 40 villages/communities in three representative counties/cities in China. An independent biostatistician will randomly allocate these villages/communities within each county/city to the study arms in a 1:1 ratio. The study procedure involves first identifying high-risk individuals for CRC through an initial risk assessment questionnaire and a fecal immunochemical test (FIT). Those who meet the criteria will then receive the intervention corresponding to their village's assigned study group.

Participants in the intervention group will receive AICC. This includes a colonoscopy recommendation from a county specialist for both participants and their families, followed by an introduction to and guided registration for a CRC education chatbot with an initial 5-minute tutorial. Subsequently, general practitioners will conduct three monthly face-by-face follow-ups, each comprising a brief reminder of colonoscopy and a guided usage of CRC education chatbot. The control group will receive only a colonoscopy recommendation from a county specialist, with access to the chatbot granted only after the end of the 6-month study period. Post-intervention, all participants will complete a questionnaire assessing CRC screening knowledge, health beliefs, and behavioral intention. Colonoscopy uptake will be collected via the hospital information system at the 3- and 6-month follow-up.

The primary analysis will follow the intention-to-treat (ITT) principle. The primary outcome is the uptake and timing of colonoscopy at 3 and 6 months after intervention. Secondary outcomes encompassed several domains: CRC screening knowledge, beliefs, and intention; chatbot usability and user engagement; and intervention costs. Between-group comparisons for continuous and categorical variables will utilize t-tests and chi-square tests. To account for potential confounders, the generalized estimating equation (GEE) will be employed to derive robust effect estimates. The timing of colonoscopy uptake will be analyzed using Kaplan-Meier survival curves and log-rank tests, and the intervention effects on the time-to-event will be quantified with a Cox proportional hazards model. Subgroup analyses will be conducted to elucidate the effect heterogeneity across populations stratified by baseline characteristics.

Being tested
AI-assisted integrated care
Keywords
colorectal cancer, colonoscopy, artificial intelligence, integrated care, trial
Medical subject headings
Colorectal Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • AI-assisted integrated careBehavioural

    A colorectal cancer screening chatbot delivered via WeChat or a web browser, designed to provide information and health education about the colonoscopy, including essential knowledge, screening rationale, methods, procedural details, and local screening policies,. The chatbot is powered by large language models and is trained on an expert-validated knowledge base derived from authoritative sources such as the China colorectal cancer screening guidelines to ensure accuracy. The knowledge base is validated by colorectal cancer specialists. The chatbot engages users in interactive, conversational dialogue to answer questions and address concerns regarding colorectal cancer and colonoscopy.

    In addition to a colonoscopy recommendation from a county specialist at on-site, general practitioners will also join to provide recommendation and brief reminder of colonoscopy within the follow-up period.

Study groups in NCT07261059
Study groupRoleWhat they receive
AICC intervention groupExperimentalParticipants in the intervention group will receive AICC. This includes a colonoscopy recommendation from a county specialist for both participants and their families, followed by an introduction to and guided registration for a CRC education chatbot with an initial 5-minute tutorial. Subsequently, general practitioners will conduct three monthly face-by-face follow-ups, each comprising a brief reminder of colonoscopy and a guided usage of CRC education chatbot.
Receives: Behavioral: AI-assisted integrated care
Control groupNo interventionParticipants in this group will receive usual specialty care, only a colonoscopy recommendation from a county specialists. For ethical considerations, participants in this arm will be offered access to the chatbot after the end of the study.

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Uptake of colonoscopy

    Whether participants receive colonoscopy for colorectal cancer screening.Data will be collected from information system of hospitals.

    Measured: Three and six months after recruitment

  2. Time to completion of colonoscopy

    The interval from intervention initiation to the colonoscopy procedure. Data will be collected from information systems of hospitals.

    Measured: Six months after recruitment

Secondary outcomes (6)

  1. CRC screening literacy

    CRC screening literacy will be assessed using a "Colorectal Cancer Screening Literacy Questionnaire" developed by the research team to ensure alignment with the study aims and intervention. The questionnaire comprises of 7 items , covering the basic knowledge of CRC, screening methods, benefits, and common misconceptions. Each item is answered with "yes", "no", and "not sure", with one point for a correct answer and no points for "not sure" and incorrect answers. The total score ranges from 0 to 7, and the higher the score, the higher the literacy level of the participants about CRC screening.

    Measured: One month after recruitment

  2. CRC screening belief

    Participants' perceptions of CRC risk and their beliefs regarding benefits and barriers of colonoscopy will be assessed using a 5-point Likert scale (from "completely disagree" to "completely agree"). A higher score indicates a stronger belief.

    Measured: One month after recruitment

  3. Colonoscopy behavioral intention

    Participants' intention to receive colonoscopy will be measured using a 5-point Likert scale (from "completely disagree" to "completely agree"). Those who agree or completely agree are defined as having colonoscopy intention.

    Measured: One month after recruitment

  4. User engagement level with chatbot

    Chatbot engagement level is measured by a binary variable whether users highly engage with chatbot in terms of usage frequency, usage duration, the number of asked questions, and the presence of free-text questions. High-engagement is defined as those using chatbot frequently and longer, and asking more questions and free-text questions; others are low-engagement.

    Measured: Six months after recruitment

  5. Usability of AI-assisted integrated care intervention

    The usability of the AICC intervention will be evaluated using a series of questions on its acceptability, feasibility, and sustainability. It covers two sections with 9 entries: Evaluation of Clinician-Delivered Health Education (4 entries) and Evaluation of the Chatbot (5 entries). The Likert 5-point scale is used, with scores ranging from 1 to 5 on a scale of "completely disagree" to "completely agree". The total usability score ranges from 9 to 45 points, with higher scores indicating greater perceived usability of the AICC intervention.

    Measured: Six months after recruitment

  6. Incremental cost-effectiveness ratio (ICER)

    The incremental cost-effectiveness ratio (ICER) of the AICC intervention versus usual specialty care will be assessed from the perspective of the health care system. The ICER is defined as the cost per additional quality-adjusted life year (QALY) gained. Cost data will include screening program costs (from project records), direct medical costs, direct non-medical costs, and indirect costs (sourced from the study in Shandong Province). QALYs will be calculated by applying health utility weights, derived from existing literature, according to patients based on their diagnostic states. The specific ICER value will be reported as the primary economic outcome. Unit of Measure: United States dollar (Dollar).

    Measured: Six months after recruitment

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted3 Dec 2025
  2. Study start8 Dec 2025 (estimated)
  3. Primary completionSep 2026 (estimated)
  4. Study completionDec 2026 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Interventional
Phase
Phase N/A
Primary purpose
Health services research
Allocation
Randomised
Intervention model
Parallel groups
Masking
Single blind
Who is masked
Outcomes assessor
Enrolment
400 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07261059
Sponsor's protocol ID
Fudan-CRC chatbot
Status last verified
Dec 2025
First submitted
21 Nov 2025
Last updated
3 Dec 2025
Results posted
No
Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No: Individual participant data will not be shared due to participant privacy concerns and institutional data protection policies.

Publications

  • Han B, Zheng R, Zeng H, Wang S, Sun K, Chen R, Li L, Wei W, He J. Cancer incidence and mortality in China, 2022. J Natl Cancer Cent. 2024 Feb 2;4(1):47-53. doi: 10.1016/j.jncc.2024.01.006. eCollection 2024 Mar.

    PubMed 39036382

  • Zhang Q, Wong AKC, Bayuo J. The Role of Chatbots in Enhancing Health Care for Older Adults: A Scoping Review. J Am Med Dir Assoc. 2024 Sep;25(9):105108. doi: 10.1016/j.jamda.2024.105108. Epub 2024 Jun 22.

    PubMed 38917965

  • Zeng A, Steinke J, Bocse HF, De Pastena M. Dr. LLM Will See You Now: The Ability of ChatGPT to Provide Geographically Tailored Colorectal Cancer Screening and Surveillance Recommendations. J Clin Med. 2025 Jul 18;14(14):5101. doi: 10.3390/jcm14145101.

    PubMed 40725794

  • Kerbage A, Kassab J, El Dahdah J, Burke CA, Achkar JP, Rouphael C. Accuracy of ChatGPT in Common Gastrointestinal Diseases: Impact for Patients and Providers. Clin Gastroenterol Hepatol. 2024 Jun;22(6):1323-1325.e3. doi: 10.1016/j.cgh.2023.11.008. Epub 2023 Nov 19.

    PubMed 37984563

  • Maida M, Mori Y, Fuccio L, Sferrazza S, Vitello A, Facciorusso A, Hassan C. Exploring ChatGPT effectiveness in addressing direct patient queries on colorectal cancer screening. Endosc Int Open. 2025 May 12;13:a25689416. doi: 10.1055/a-2568-9416. eCollection 2025.

    PubMed 40376022

  • Heald B, Keel E, Marquard J, Burke CA, Kalady MF, Church JM, Liska D, Mankaney G, Hurley K, Eng C. Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy. J Med Genet. 2021 Dec;58(12):807-814. doi: 10.1136/jmedgenet-2020-107294. Epub 2020 Nov 9.

    PubMed 33168571

  • Chen D, Avison K, Alnassar S, Huang RS, Raman S. Medical accuracy of artificial intelligence chatbots in oncology: a scoping review. Oncologist. 2025 Apr 4;30(4):oyaf038. doi: 10.1093/oncolo/oyaf038.

    PubMed 40285677

  • Leung DY, Chow KM, Lo SW, So WK, Chan CW. Contributing Factors to Colorectal Cancer Screening among Chinese People: A Review of Quantitative Studies. Int J Environ Res Public Health. 2016 May 17;13(5):506. doi: 10.3390/ijerph13050506.

    PubMed 27196920

  • Wolf AMD, Fontham ETH, Church TR, Flowers CR, Guerra CE, LaMonte SJ, Etzioni R, McKenna MT, Oeffinger KC, Shih YT, Walter LC, Andrews KS, Brawley OW, Brooks D, Fedewa SA, Manassaram-Baptiste D, Siegel RL, Wender RC, Smith RA. Colorectal cancer screening for average-risk adults: 2018 guideline update from the American Cancer Society. CA Cancer J Clin. 2018 Jul;68(4):250-281. doi: 10.3322/caac.21457. Epub 2018 May 30.

    PubMed 29846947

  • Peterson EB, Ostroff JS, DuHamel KN, D'Agostino TA, Hernandez M, Canzona MR, Bylund CL. Impact of provider-patient communication on cancer screening adherence: A systematic review. Prev Med. 2016 Dec;93:96-105. doi: 10.1016/j.ypmed.2016.09.034. Epub 2016 Sep 28.

    PubMed 27687535

  • Butterly LF. Proven Strategies for Increasing Adherence to Colorectal Cancer Screening. Gastrointest Endosc Clin N Am. 2020 Jul;30(3):377-392. doi: 10.1016/j.giec.2020.02.003. Epub 2020 Apr 9.

    PubMed 32439077

  • Dougherty MK, Brenner AT, Crockett SD, Gupta S, Wheeler SB, Coker-Schwimmer M, Cubillos L, Malo T, Reuland DS. Evaluation of Interventions Intended to Increase Colorectal Cancer Screening Rates in the United States: A Systematic Review and Meta-analysis. JAMA Intern Med. 2018 Dec 1;178(12):1645-1658. doi: 10.1001/jamainternmed.2018.4637.

    PubMed 30326005

  • Deng SX, Cai QC, An W, Gao J, Hong SY, Zhu W, Li ZS. [Factors influencing patient compliance in colorectal cancer screening: qualitative research synthesis]. Zhonghua Yi Xue Za Zhi. 2010 Oct 19;90(38):2679-83. Chinese.

    PubMed 21162896

  • Yu Z, Li B, Zhao S, Du J, Zhang Y, Liu X, Guo Q, Zhou H, He M. Uptake and detection rate of colorectal cancer screening with colonoscopy in China: A population-based, prospective cohort study. Int J Nurs Stud. 2024 May;153:104728. doi: 10.1016/j.ijnurstu.2024.104728. Epub 2024 Feb 20.

    PubMed 38461798

  • Chen H, Li N, Ren J, Feng X, Lyu Z, Wei L, Li X, Guo L, Zheng Z, Zou S, Zhang Y, Li J, Zhang K, Chen W, Dai M, He J; group of Cancer Screening Program in Urban China (CanSPUC). Participation and yield of a population-based colorectal cancer screening programme in China. Gut. 2019 Aug;68(8):1450-1457. doi: 10.1136/gutjnl-2018-317124. Epub 2018 Oct 30.

    PubMed 30377193

Questions about this trial

What is this clinical trial studying?

A study testing AI-assisted integrated care in people with Colorectal Neoplasms and Colonoscopy, run by Fudan University.

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 4 inclusion and 2 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: opening soon, as of the sponsor's last update on 3 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.

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?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Contact Zhiyuan Hou, PhD (86+21 54231112, zyhou@fudan.edu.cn), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Uptake of colonoscopy (time frame: Three and six months after recruitment). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07261059, which also lists 21 linked publications.

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 3 Dec 2025.

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