Clinical trial · Observational
Assessment of Early-detection Based on Liquid Biopsy in Lung Cancer (ASCEND-LUNG)
Detection of Early-stage Lung Cancer Based on Liquid Biopsy of Peripheral Blood: a Prospective Study
NCT04817046CI-TRIAL-00050890unknownClinicalTrials.gov clinicaltrialsProvenance
- 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 purpose of this study is to develop a lung cancer diagnosis tool using a multi-omics approach based on liquid biopsy.
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 |
|---|---|---|---|
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (0)
Data not yet available
No intervention recorded.
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Accuracy of the multi-omics early-stage lung cancer diagnosis model
- timeFrame
- through study completion, an average of 1.5 year
- description
- Sensitivity and specificity of the multi-omics early-stage lung cancer diagnosis model
Secondary outcomes (2)
- measure
- Accuracy of diagnostic models established separately from multi-omics data
- timeFrame
- through study completion, an average of 1.5 year
- description
- Sensitivity and specificity models established separately from multi-omics data
- measure
- Relationship between multi-omics data
- timeFrame
- through study completion, an average of 1.5 year
- description
- Explore the relationship of features extracted from multi-omics data
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 40 Years
- Maximum age
- 74 Years
Show eligibility criteria text
Inclusion Criteria: * Signed informed consent * Male or female, age equal to or greater than 40 years old and less than 75 years old * Blood sample was collected before surgery for the detection of cfDNA methylation and other biomarkers * Lung cancer patients diagnosed for the first time within 42 days before blood sampling without any anti-tumor treatment; or patients who are highly suspected of lung cancer through imaging evaluation or other routine clinical diagnosis and confirmed by tissue biopsy or surgical specimens within 42 days after blood sampling * The subject has not received any local or systemic anti-tumor therapy before blood collection, including (not limited to) any surgery, local or systemic radiotherapy and chemotherapy, targeted therapy (including anti-angiogenesis), immunotherapy, cancer vaccines and hormone therapy, etc. Exclusion Criteria: * Unable to obtain sufficient and qualified blood samples * Female subjects who are pregnant or breastfeeding * Patients who have received organ transplantation or non-autologous bone marrow or stem cell transplantation * Patients who have received blood transfusion within 7 days before blood sampling * Patients who have received anti-infection treatment within 14 days before blood collection * Patients who have receiving anti-tumor drugs for other diseases within 30 days before blood collection, such as methotrexate, cyclophosphamide, mercaptopurine, chlorambucil, tamoxifen, etc. * Patients who suffered from other malignant tumors or multiple primary tumors at the same time * Pathological confirmed benign lesions by tissue biopsy or surgery * Insufficient sample for a confirmed pathological diagnosis * Lung cancer patients with ground glass nodules on CT imaging.
References
Publications (1)
- DERIVEDJin Y, Mu W, Shi Y, Qi Q, Wang W, He Y, Sun X, Yang B, Cui P, Li C, Liu F, Liu Y, Wang G, Zhao J, Zhang Y, Zhang S, Cao C, Sun C, Hong N, Cai S, Tian J, Yang F, Chen K. Development and validation of an integrated system for lung cancer screening and post-screening pulmonary nodules management: a proof-of-concept study (ASCEND-LUNG). EClinicalMedicine. 2024 Aug 3;75:102769. doi: 10.1016/j.eclinm.2024.102769. eCollection 2024 Sep. PMID 39165498