Clinical trial · Interventional
AI-Based Personalized Digital Management for High-Risk Pulmonary Nodule Follow-up
AI-Based Personalized Digital Management to Improve Follow-up Care Adherence Among Patients With High-Risk Pulmonary Nodules: A Pragmatic Randomized Clinical Trial
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The goal of this pragmatic clinical trial is to learn whether AI-based personalized digital management can help patients with high-risk pulmonary nodules complete appropriate follow-up care. The study will include adults aged 40 years or older whose pulmonary nodules were identified on chest CT scans already performed at the hospital for clinical care, health examinations, or other reasons. The hospital's AI-based lung nodule evaluation system will be used to identify nodules classified as high risk. Patients who have already completed follow-up or entered an active pulmonary nodule management pathway will not be included. The main question this study aims to answer is: \- Does personalized digital management increase the proportion of patients who complete appropriate pulmonary nodule follow-up within 16 weeks after randomization compared with usual care? Researchers will compare personalized digital management with usual care. Participants will be randomly assigned in a 1:1 ratio to one of the following groups: * The personalized digital management group will receive individualized information about the pulmonary nodule and recommendations for appropriate follow-up through the hospital's official WeChat account. * The usual care group will not receive the study-specific personalized digital message. Participants in both groups may continue to receive routine clinical care. Participants will: * Provide electronic informed consent * Answer a brief questionnaire about pulmonary nodule care received outside the hospital and selected health information, including smoking history * Continue their usual medical care * Allow researchers to review relevant hospital records to determine whether pulmonary nodule follow-up was completed The study will not arrange an additional initial chest CT solely for research purposes. Appropriate follow-up may include specialist evaluation, follow-up chest CT, PET/CT, tissue sampling, surgery, or a documented clinical decision that no further evaluation is needed. Researchers will also examine subsequent diagnostic procedures, lung cancer diagnoses, treatments, complications, and longer-term clinical outcomes.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Pulmonary Nodules | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Personalized Digital Outreach | Behavioral | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- Personalized Digital Management
- description
- Following common AI-based identification, eligibility confirmation, and randomization, participants assigned to this arm will receive personalized information about their high-risk pulmonary nodule and recommendations for appropriate specialist follow-up through the hospital's official WeChat account. Participants will otherwise continue routine clinical care.
- interventionNames
- Behavioral: Personalized Digital Outreach
- type
- NO_INTERVENTION
- label
- Usual Care
- description
- Participants assigned to this arm will not receive the study-specific personalized digital information or follow-up recommendations after randomization. They will continue routine clinical care. Standard clinical communication and any necessary safety notifications will remain available.
Primary outcomes (1)
- measure
- Pulmonary Nodule Follow-up Completion Within 16 Weeks After Randomization
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 40 Years
Show eligibility criteria text
Inclusion Criteria: 1. Age 40 years or older. 2. Completion of a chest CT at the study hospital for clinical care, health examination, or another reason. 3. At least one pulmonary nodule classified as high risk by the Linc model, with a predicted malignancy probability of 75% or greater. The index CT, index nodule, model version, and risk score must be traceable. 4. Follow-up management for the index nodule has not been completed before randomization, and the participant has not entered a clearly documented active pulmonary nodule management pathway. 5. Ability to provide valid electronic informed consent and receive study messages through the hospital's official WeChat account. Exclusion Criteria: 1. Prior or current lung cancer, or ongoing diagnostic evaluation, treatment, postoperative care, or surveillance for the index nodule. 2. Active malignancy for which the pulmonary nodule should be evaluated or managed as possible metastatic disease or within another established cancer care pathway. 3. Completion before randomization of a qualifying chest CT, pulmonary nodule specialist or multidisciplinary team evaluation, PET/CT, tissue sampling, surgery or lesion-directed treatment, or verified clinical closure related to the index nodule. 4. An existing valid order, appointment, referral, or documented active management plan for the index nodule, including active management by thoracic surgery, a pulmonary nodule clinic or multidisciplinary team, oncology, or radiation oncology. 5. Maximum diameter of the index lesion greater than 30 mm. These patients will receive standardized safety notification and accelerated specialist referral and will not be randomized. 6. Lung-RADS category 4B or 4X, or an equivalent highly suspicious finding, when Lung-RADS is applicable or can be reliably reconstructed, if clinical safety review determines that immediate notification or accelerated clinical care is required. 7. Another major clinical safety, ethical, technical, or data-protection concern that cannot be reasonably mitigated.
References
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