A Study Developing a Non-invasive Urine-based Proteomic Model for Early Lung Cancer Detection.

NCT06733311 | Recruiting DMC

• 1 other identifier: CYFH202324
• Study Type: observational
• Target: 480
• Locations: 1 country
• Sites: 1

Brief Summary

Brief Summary: The goal of this observational study is to develop a non-invasive urine proteomic diagnostic model to improve early-stage lung cancer detection. The study aims to answer the following main questions: Can urine proteomics reliably differentiate early-stage lung cancer from benign conditions? How does the diagnostic model compare to current clinical and imaging methods in accuracy? Participants will: Provide preoperative urine samples. Undergo proteomic analysis of urine samples. Have clinical, imaging, and proteomic data integrated into an AI-assisted diagnostic model. The study will evaluate the sensitivity and specificity of this innovative diagnostic approach.

Conditions

Early-Stage Lung Cancer; NSCLC; Pulmonary Nodule

Keywords

Early-Stage Lung Cancer; Pulmonary Nodule; Urine Proteomics; Non-Invasive Diagnosis; Artificial Intelligence

Outcome Measures

Primary Outcomes (1)

• Prediction Accuracy of Diagnostic Models

  The primary outcome measure is the accuracy of preoperative predictions (sensitivity and specificity) for early-stage non-small cell lung cancer (NSCLC) diagnosis. Predictions are based on: 1. Urine proteomics in the experimental group. 2. Chest CT imaging in the control group. Accuracy will be assessed by comparing preoperative predictions with postoperative pathological findings, including tumor histopathological subtypes, lymph node metastasis, and other pathological factors.

  Within 2 weeks post-surgery.

Secondary Outcomes (3)

• Cut-off Value for Urine Proteomics Diagnostic Test

  Within 1 month after data analysis.

• Comparative Performance of Diagnostic Models

  Within 2 months post-surgery.

• Long-term Diagnostic Effectiveness

  Up to 2 years post-surgery.

Study Arms (2)

Urine Proteomics Diagnostic Group

Participants in this group will undergo urine proteomic analysis before surgery to predict early-stage non-small cell lung cancer (NSCLC). The predictions include tumor histopathological subtypes, lymph node metastasis, and other pathological factors. The accuracy of the diagnostic model will be compared to pathological results after surgery. This group consists of approximately 240 participants, with an anticipated 10% loss accounted for.

CT Diagnostic Group

Participants in this group will undergo standard preoperative chest CT imaging to predict early-stage non-small cell lung cancer (NSCLC). Predictions include tumor histopathological subtypes, lymph node metastasis, and other pathological factors. The accuracy of the imaging predictions will be compared to pathological results after surgery. This group also consists of approximately 240 participants, with an anticipated 10% loss accounted for.

Eligibility Criteria

• Age: 18 Years - 75 Years
• Gender Eligibility Details: Eligibility is not restricted by gender. Both male and female participants aged 18 to 75 years, who meet the inclusion and exclusion criteria, are eligible to participate in this study. Gender-specific factors, such as hormonal influences or comorbid conditions, will be documented and analyzed if applicable but are not criteria for inclusion or exclusion.
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population includes patients suspected of having early-stage (I-IIIA, non-N2) non-small cell lung cancer (NSCLC), recruited from the thoracic surgery and respiratory departments of Beijing Chao-Yang Hospital and collaborating clinical centers. Participants are individuals scheduled for surgical intervention based on preoperative clinical and imaging assessments.

You may qualify if:

• Male or female participants aged 18 to 75 years.
• Diagnosed or highly suspected early-stage (I-IIIA, non-N2) non-small cell lung 3.cancer (NSCLC) based on imaging or clinical assessment.
• No prior anti-cancer treatment, including surgery, chemotherapy, radiotherapy, targeted therapy, or immunotherapy.
• Able to provide informed consent and willing to comply with the study protocol, including urine sample collection before surgery.
• Diagnosis confirmed within 42 days post-imaging or preoperative assessment through biopsy or surgical specimen.

You may not qualify if:

• History of any cancer treatment prior to study enrollment.
• Presence of metastatic disease (N2 or more advanced staging).
• Severe comorbid conditions or organ dysfunctions (e.g., renal failure) that could affect urine sample quality or interpretation.
• Pregnancy or lactation.
• Participation in another clinical study that could interfere with the outcomes of this study.
• Inability to comply with the study protocol, including language barriers or cognitive impairments.

Sponsors & Collaborators

• Beijing Chao Yang Hospital: lead

Study Sites (1)

Beijing Chao-Yang Hospital, Capital Medical University

Chaoyang District, Beijing Municipality, 100000, China

RECRUITING

Related Publications (1)

• Gasparri R, Sedda G, Caminiti V, Maisonneuve P, Prisciandaro E, Spaggiari L. Urinary Biomarkers for Early Diagnosis of Lung Cancer. J Clin Med. 2021 Apr 16;10(8):1723. doi: 10.3390/jcm10081723.

  PMID: 33923502 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

Urine samples: Urine samples will be collected and retained for proteomic analysis to identify biomarkers for early-stage lung cancer diagnosis.

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases

Central Study Contacts

Bin Hu, MD

CONTACT

+86 139-0130-1750

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 2 Years
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 10, 2024
• First Posted: December 13, 2024
• Study Start: March 1, 2024
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2024
• Last Updated: December 13, 2024

Record last verified: 2024-02

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)