Pulmonary NodulesNCT07882628
Diagnostic Performance of an AI-Based Multi-Omics Model for Early Lung Cancer
An observational study of Pulmonary Nodules and Early Detection of Cancer, run by Beijing Chao Yang Hospital at 8 sites in China.
Trial summary
This is a prospective, multicenter observational cohort study for patients with lung nodules suspicious for early-stage lung cancer. The study aims to build AI-assisted diagnostic models by integrating clinical data, CT imaging and multi-omics biomarkers, and validate a rapid evaluation system for bronchoscopic biopsy… Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Pulmonary Nodules, Early Detection of Cancer, Lung Neoplasms
- How many people
- 1,050 participants
- Where
- 8 sitesChina
- Study dates
- 21 Oct 2026to Dec 2028
- Phase
- Observational
- 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 18 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: This study uses consecutive enrollment. It recruits participants meeting eligibility criteria. The study has two sub-studies. Sub-study 1 includes patients with surgical resection. These patients have pulmonary nodules found on imaging and need clinical intervention. They are high-risk nodule patients from thoracic surgery or respiratory outpatient clinics. This is a multicenter study with seven tertiary teaching hospitals. The target sample size is 850. All sites use competitive enrollment. Sub-study 2 includes patients receiving bronchoscopic biopsy. These patients have pulmonary nodules detected on imaging and need bronchoscopic biopsy. This is a two-center study with two tertiary teaching hospitals. The target sample size is 200. All enrolled participants get follow-up after enrollment. Participants in Sub-study 1 are followed for 24 months. Participants in Sub-study 2 are followed for 6 months.
Who may be able to join
- Sub-study 1:
- Age: 18-75 years.
- Performance status: Eastern Cooperative Oncology Group (ECOG) performance status score of 0 or 1.
- Nodule characteristics: Single or multiple pulmonary nodules detected on thin-section CT (slice thickness ≤1.5 mm). The largest diameter of the primary lesion is ≥8 mm and ≤20 mm. For patients with multiple nodules, the maximum diameter of other lesions must be <8 mm.
- No clinical or imaging evidence of lymph node or distant metastasis.
- Planned surgical resection: Patients with complete clinical data and preoperative thin-section CT; peripheral blood samples can be collected.
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- Pathological/clinical diagnosis: Definitive pathological diagnosis after surgical resection is required as the gold standard.
- Informed consent: Patients voluntarily join this study, sign written informed consent, and agree to complete scheduled follow-up for at least 5 years.
- Sample availability: Patients can provide sufficient peripheral blood samples as required by the study protocol. For patients undergoing surgery or biopsy, tumor tissues and adjacent normal tissue samples meeting quality requirements can be obtained.
- Sub-study 2:
- Age: 18-75 years.
- Performance status: Able to tolerate bronchoscopic biopsy, with no contraindications to biopsy.
- Nodule characteristics: Single or multiple pulmonary nodules detected on thin-section CT (slice thickness ≤1.5 mm). The target lesion planned for biopsy has a maximum diameter ≥8 mm and ≤30 mm.
- Clinician assessment: Clinicians recommend bronchoscopic biopsy (including conventional bronchoscopy, endobronchial ultrasound [EBUS], navigational bronchoscopy, etc.) to determine the pathological nature of the pulmonary nodule.
- Specimen and imaging: Small tissue specimens obtained during biopsy undergo three-dimensional interferometric imaging, and complete imaging data are retained.
- Pathological/clinical diagnosis: Definitive pathological diagnosis of the small biopsy specimen is required as the gold standard.
- Informed consent: Patients voluntarily join this study, sign written informed consent, and agree to complete scheduled follow-up for at least 5 years.
Who cannot join
- Sub-study 1:
- Concurrent immune diseases: Active autoimmune diseases (such as rheumatoid arthritis, systemic lupus erythematosus, etc.), or patients receiving long-term systemic immunosuppressants or glucocorticoids within the past 6 months.
- Active infection: Active infections (such as active pulmonary tuberculosis, acute phase of SARS-CoV-2 infection, etc.) that may significantly affect immune status.
- Prior anti-tumor treatment: Any form of anti-tumor therapy received within the past 6 months, including chemotherapy, radiotherapy, targeted therapy, or immune checkpoint inhibitor therapy.
- Suspected multiple primary lung cancers where secondary lesions require simultaneous or staged intervention (surgery, ablation, radiotherapy, etc.).
- Other malignant tumors: History of other malignant tumors within the past 3 years.
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- Severe dysfunction of major organs: Severe hepatic or renal insufficiency (judged by investigators).
- Special population: Pregnant or breastfeeding women.
- Poor study compliance: Any psychological, family, or social factors that prevent patients from understanding and following the study protocol and follow-up plan.
- Sub-study 2:
- Concurrent immune diseases: Active autoimmune diseases (such as rheumatoid arthritis, systemic lupus erythematosus, etc.), or patients receiving long-term systemic immunosuppressants or glucocorticoids within the past 6 months.
- Active infection: Active infections (such as active pulmonary tuberculosis, acute phase of SARS-CoV-2 infection, etc.) that may significantly affect immune status.
- Prior anti-tumor treatment: Any form of anti-tumor therapy received within the past 6 months, including chemotherapy, radiotherapy, targeted therapy, or immune checkpoint inhibitor therapy.
- Special population: Pregnant or breastfeeding women.
- Poor compliance with study or procedure: Any physical, psychological, family, or social factors that prevent patients from understanding and following the study protocol or tolerating bronchoscopy.
- Bleeding tendency or severe coagulation disorders.
Trial locations and contacts
8 sites in 1 country. Contact the study team or a site near you to ask about taking part.
8 sites in 1 country
China8 sites
Beijing Chao Yang Hospital
Beijing, Beijing Municipality, 100020
Ying Ji, MD, +86 010-85231044, 15675112499@163.com
Nan Song, PhD
Beijing Anzhen Hospital, Capital Medical University
Beijing, Beijing Municipality, 100029
Bin You, MD
Beijing Friendship Hospital, Capital Medical University
Beijing, Beijing Municipality, 100050
Yong Cui, MD
Peking University Cancer Hospital
Beijing, Beijing Municipality, 100142
Guangyu Bai
Peking University Third Hospital
Beijing, Beijing Municipality, 100191
Guangliang Qiang, MD
Miyun District Hospital of Beijing
Beijing, Beijing Municipality, 101500
Yongzheng Yao, MD
Fangshan Hospital, Beijing University of Chinese Medicine
Beijing, Beijing Municipality, 102400
Wei Li, MD
The Third Xiangya Hospital of Central South University
Changsha, Hunan, 410013
Wei Feng, MD
About this study
Official title: Establishment and Application of an AI-Based Multi-Omics Model for Early and Precise Diagnosis of Lung Cancer
This is a prospective, multicenter observational cohort study for patients with lung nodules suspicious for early-stage lung cancer. The study aims to build AI-assisted diagnostic models by integrating clinical data, CT imaging and multi-omics biomarkers, and validate a rapid evaluation system for bronchoscopic biopsy specimens. No investigational drugs or devices will be applied; all participants receive routine clinical care. We will collect clinical records, CT images, blood and tissue samples, and conduct long-term follow-up of disease outcomes. A total of 1050 subjects will be enrolled from 8 participating hospitals in China.
Read the detailed description
This is a multicenter, prospective, observational diagnostic cohort study conducted in China that comprises two substudies. Substudy 1 enrolls patients with lung nodules scheduled for surgical resection to enable multi-omics biomarker exploration and the development of an integrated clinical-imaging-immune artificial intelligence diagnostic model. Substudy 2 enrolls patients undergoing bronchoscopic biopsy for lung nodules to clinically validate a rapid microscopic tissue evaluation system. All participants will receive standard-of-care management without any study-specific therapeutic interventions. Baseline data, including demographics, smoking history, comorbidities, clinical symptoms, and thin-section CT imaging features, will be collected. Peripheral blood samples will be obtained for multi-omics analysis. For participants in Substudy 1, resected tissue specimens will be collected for histopathological assessment and multi-omics profiling, with postoperative paraffin pathology serving as the gold standard. For participants in Substudy 2, biopsy specimens will be assessed by the rapid microscopic evaluation system before routine pathological processing. Participants will undergo protocol-scheduled long-term follow-up. Follow-up assessments include clinical visits, chest CT scans, and documentation of recurrence, metastasis, and survival events. The primary objective is to evaluate the performance of multi-omics-enhanced artificial intelligence models in discriminating benign from malignant lung nodules in Substudy 1, as well as to assess the diagnostic concordance between the rapid microscopic biopsy evaluation system and paraffin pathology in Substudy 2. Secondary objectives include analyses of disease-free survival and overall survival, and identification of potential immune-related biomarkers for early-stage lung cancer. Uniform standard operating procedures (SOPs) for data collection will be implemented across all participating sites. Centralized quality control of image processing, biological sample handling, and clinical data entry will be conducted to reduce multicenter heterogeneity. Participants in Substudy 1 will be followed for at least 24 months, while those in Substudy 2 will be followed for at least 6 months. The target loss-to-follow-up rate is set at less than 10%.
- Conditions
- Pulmonary Nodules, Early Detection of Cancer, Lung Neoplasms
- Keywords
- CT imaging, Tumor autoantibodies, Three-dimensional interference microscopy imaging, Deep learning, Early-stage lung cancer diagnosis
- Medical subject headings
- Multiple Pulmonary Nodules, Lung Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Surgical cohort | Patients with pulmonary nodules who are scheduled to receive thoracic surgical resection. Biospecimens including serum, plasma, tumor tissue and NAT will be collected. | |
| Bronchoscopy Sub-cohort | Patients with pulmonary nodules who will undergo bronchoscopic biopsy.No biological specimens will be collected. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sub-study 1:Area under the receiver operating characteristic curve (AUC) of the multi-modal diagnostic model
To assess the diagnostic performance of the multi-modal model combining CT imaging, tumor autoantibodies and multi-omics data for differentiating early-stage lung cancer from benign pulmonary nodules. Pathological results serve as the gold standard. The primary endpoint is the AUC of the model.
Measured: Up to 12 months after participant enrollment, after final pathological diagnosis of pulmonary nodules is obtained
Sub-study2:Area under the receiver operating characteristic curve (AUC) of three-dimensional interference microscopy
To evaluate the diagnostic performance of three-dimensional interference microscopy in differentiating malignant and benign pulmonary nodules based on bronchoscopic biopsy samples. Final pathological diagnosis is used as the gold standard. The primary outcome is the AUC of the microscopic imaging method.
Measured: Up to 12 months after participant enrollment, after final pathological diagnosis is obtained
Secondary outcomes (3)
Sub-study1&2:Overall Survival (OS)
Overall survival is defined as the time from the date of surgery to death from any cause. All-cause mortality will be documented during the follow-up period.
Measured: 24 months after participant enrollment
Sub-study1&2:Tumor recurrence or progression
Tumor recurrence or disease progression is determined according to the RECIST 1.1 criteria or comprehensive multidisciplinary judgment based on serial imaging and clinical data. Events include local recurrence, new lesion emergence, or significant enlargement of existing lesions.
Measured: 24 months after participant enrollment
Sub-study1&2:Tumor metastasis
Tumor metastasis is defined as tumor spread to regional lymph nodes or distant organs during follow-up, confirmed by imaging evidence and comprehensive clinical evaluation. All metastatic events will be recorded.
Measured: 24 months after participant enrollment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Oct 2026
- Study start21 Oct 2026 (estimated)
- Primary completionJun 2028 (estimated)
- Study completionDec 2028 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pulmonary NodulesStudies 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
- 1,050 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Beijing Chao Yang Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Guangxu Liu, Study director, Beijing Chao Yang Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07882628
- Sponsor's protocol ID
- 2026-9-11-K3
- Other IDs
- CFH 2026-1Q-1042
- Status last verified
- Oct 2026
- First submitted
- 11 Oct 2026
- Last updated
- 20 Oct 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared with external researchers due to participant privacy protection and local data management regulations. The aggregate study results will be available via publication in peer-reviewed journals.
Study at a glance
From the registry record, last updated by the sponsor on 20 Oct 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Establishment and Application of an AI-Based Multi-Omics Model for Early and Precise Diagnosis of Lung Cancer
- ClinicalTrials.gov ID
- NCT07882628
- Acronym / sponsor ID
- 2026-9-11-K3
- Conditions
- Pulmonary Nodules, Early Detection of Cancer, Lung Neoplasms
- Keywords
- CT imaging, Tumor autoantibodies, Three-dimensional interference microscopy imaging, Deep learning, Early-stage lung cancer diagnosis
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 1,050 participants (estimated)
- Lead sponsor
- Beijing Chao Yang HospitalUniversity, hospital or other
- Study start
- 21 Oct 2026 (estimated)
- Primary completion
- Jun 2028 (estimated)
- Study completion
- Dec 2028 (estimated)
- First posted
- 20 Oct 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is a prospective, multicenter observational cohort study for patients with lung nodules suspicious for early-stage lung cancer. The study aims to build AI-assisted diagnostic models by integrating clinical data, CT imaging and multi-omics biomarkers, and validate a rapid evaluation system for bronchoscopic biopsy specimens. No investigational drugs or devices will be applied; all participants receive routine clinical care. We will collect clinical records, CT images, blood and tissue samples, and conduct long-term follow-up of disease outcomes. A total of 1050 subjects will be enrolled from 8 participating hospitals in China.
Detailed description
This is a multicenter, prospective, observational diagnostic cohort study conducted in China that comprises two substudies. Substudy 1 enrolls patients with lung nodules scheduled for surgical resection to enable multi-omics biomarker exploration and the development of an integrated clinical-imaging-immune artificial intelligence diagnostic model. Substudy 2 enrolls patients undergoing bronchoscopic biopsy for lung nodules to clinically validate a rapid microscopic tissue evaluation system. All participants will receive standard-of-care management without any study-specific therapeutic interventions. Baseline data, including demographics, smoking history, comorbidities, clinical symptoms, and thin-section CT imaging features, will be collected. Peripheral blood samples will be obtained for multi-omics analysis. For participants in Substudy 1, resected tissue specimens will be collected for histopathological assessment and multi-omics profiling, with postoperative paraffin pathology serving as the gold standard. For participants in Substudy 2, biopsy specimens will be assessed by the rapid microscopic evaluation system before routine pathological processing. Participants will undergo protocol-scheduled long-term follow-up. Follow-up assessments include clinical visits, chest CT scans, and documentation of recurrence, metastasis, and survival events. The primary objective is to evaluate the performance of multi-omics-enhanced artificial intelligence models in discriminating benign from malignant lung nodules in Substudy 1, as well as to assess the diagnostic concordance between the rapid microscopic biopsy evaluation system and paraffin pathology in Substudy 2. Secondary objectives include analyses of disease-free survival and overall survival, and identification of potential immune-related biomarkers for early-stage lung cancer. Uniform standard operating procedures (SOPs) for data collection will be implemented across all participating sites. Centralized quality control of image processing, biological sample handling, and clinical data entry will be conducted to reduce multicenter heterogeneity. Participants in Substudy 1 will be followed for at least 24 months, while those in Substudy 2 will be followed for at least 6 months. The target loss-to-follow-up rate is set at less than 10%.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Surgical cohort | – | –Patients with pulmonary nodules who are scheduled to receive thoracic surgical resection. Biospecimens including serum, plasma, tumor tissue and NAT will be collected. |
| Bronchoscopy Sub-cohort | – | –Patients with pulmonary nodules who will undergo bronchoscopic biopsy.No biological specimens will be collected. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- This study uses consecutive enrollment. It recruits participants meeting eligibility criteria. The study has two sub-studies. Sub-study 1 includes patients with surgical resection. These patients have pulmonary nodules found on imaging and need clinical intervention. They are high-risk nodule patients from thoracic surgery or respiratory outpatient clinics. This is a multicenter study with seven tertiary teaching hospitals. The target sample size is 850. All sites use competitive enrollment. Sub-study 2 includes patients receiving bronchoscopic biopsy. These patients have pulmonary nodules detected on imaging and need bronchoscopic biopsy. This is a two-center study with two tertiary teaching hospitals. The target sample size is 200. All enrolled participants get follow-up after enrollment. Participants in Sub-study 1 are followed for 24 months. Participants in Sub-study 2 are followed for 6 months.
Key inclusion criteria (17 listed)
- Age: 18-75 years.
- Performance status: Eastern Cooperative Oncology Group (ECOG) performance status score of 0 or 1.
- Nodule characteristics: Single or multiple pulmonary nodules detected on thin-section CT (slice thickness ≤1.5 mm). The largest diameter of the primary lesion is ≥8 mm and ≤20 mm. For patients with multiple nodules, the maximum diameter of other lesions must be <8 mm.
- No clinical or imaging evidence of lymph node or distant metastasis.
- Planned surgical resection: Patients with complete clinical data and preoperative thin-section CT; peripheral blood samples can be collected.
Key exclusion criteria (16 listed)
- Concurrent immune diseases: Active autoimmune diseases (such as rheumatoid arthritis, systemic lupus erythematosus, etc.), or patients receiving long-term systemic immunosuppressants or glucocorticoids within the past 6 months.
- Active infection: Active infections (such as active pulmonary tuberculosis, acute phase of SARS-CoV-2 infection, etc.) that may significantly affect immune status.
- Prior anti-tumor treatment: Any form of anti-tumor therapy received within the past 6 months, including chemotherapy, radiotherapy, targeted therapy, or immune checkpoint inhibitor therapy.
- Suspected multiple primary lung cancers where secondary lesions require simultaneous or staged intervention (surgery, ablation, radiotherapy, etc.).
- Other malignant tumors: History of other malignant tumors within the past 3 years.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Sub-study 1:Area under the receiver operating characteristic curve (AUC) of the multi-modal diagnostic model
Time frame: Up to 12 months after participant enrollment, after final pathological diagnosis of pulmonary nodules is obtained
To assess the diagnostic performance of the multi-modal model combining CT imaging, tumor autoantibodies and multi-omics data for differentiating early-stage lung cancer from benign pulmonary nodules. Pathological results serve as the gold standard. The primary endpoint is the AUC of the model.
Sub-study2:Area under the receiver operating characteristic curve (AUC) of three-dimensional interference microscopy
Time frame: Up to 12 months after participant enrollment, after final pathological diagnosis is obtained
To evaluate the diagnostic performance of three-dimensional interference microscopy in differentiating malignant and benign pulmonary nodules based on bronchoscopic biopsy samples. Final pathological diagnosis is used as the gold standard. The primary outcome is the AUC of the microscopic imaging method.
3 secondary outcomes
Sub-study1&2:Overall Survival (OS)
Time frame: 24 months after participant enrollment
Sub-study1&2:Tumor recurrence or progression
Time frame: 24 months after participant enrollment
Sub-study1&2:Tumor metastasis
Time frame: 24 months after participant enrollment
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 20 Oct 2026.
- Individual participant dataSharing planned: No. Individual participant data will not be shared with external researchers due to participant privacy protection and local data management regulations. The aggregate study results will be available via publication in peer-reviewed journals.
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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.
Guangxu Liu study director
Beijing Chao Yang Hospital
8 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pulmonary Nodules and Early Detection of Cancer, run by Beijing Chao Yang Hospital at 8 sites in China.
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 17 inclusion and 16 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 20 Oct 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 8 sites in China. 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?
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 Ying Ji, MD (+86 010-85231044, 15675112499@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sub-study 1:Area under the receiver operating characteristic curve (AUC) of the multi-modal diagnostic model (time frame: Up to 12 months after participant enrollment, after final pathological diagnosis of pulmonary nodules is obtained). 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?
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 20 Oct 2026; AzTrials last refreshed its copy on 26 Oct 2026.