- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04452058
CT-based Radiomic Algorithm for Assisting Surgery Decision and Predicting Immunotherapy Response of NSCLC (TOP-RLC)
Study Overview
Status
Intervention / Treatment
Detailed Description
Study Type
Enrollment (Anticipated)
Contacts and Locations
Study Contact
- Name: Haiyu Zhou, PhD
- Phone Number: +8613710342002
- Email: lungcancer@163.com
Study Contact Backup
- Name: Luyu Huang
- Email: 13lyhuang1@gmail.com
Study Locations
-
-
Guangdong
-
Guangzhou, Guangdong, China, 510000
- Recruiting
- Guangdong Provincial People's Hospital
-
Contact:
- Haiyu Zhou, PhD
- Phone Number: +8613710342002
- Email: lungcancer@163.com
-
Guangzhou, Guangdong, China, 510000
- Recruiting
- Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
-
Contact:
- Herui Yao, PhD
- Phone Number: +8613500018020
- Email: yaoherui@mail.sysu.edu.cn
-
Contact:
- Yufang Yu
- Phone Number: +8613660238987
- Email: yuyf9@mail.sysu.edu.cn
-
-
Zhejiang
-
Zhoushan, Zhejiang, China, 316000
- Recruiting
- Zhoushan Lung Cancer Institution
-
Contact:
- Hanbo Cao, PhD
- Phone Number: 13567690608
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Patients in Guangdong Provincial People's hospital from March 1, 2015 to May 31,2022.
Patients from Sun Yat-sen Memorial Hospital ,Guangdong Province, China ; Zhoushan Lung Cancer Institution,Zhejiang Province,China during 2019.01-2022.3
All Patients should be histologically confirmed NSCLC and those have preoperative chest CT scan.
Description
Inclusion Criteria:
- (a) that were pathologically confirmed as precancerous lesions or Stage I lung adenocarcinoma (≤3cm)
- (b) standard Chest CT scans with or without contrast enhancement performed <3 months before surgery;
- (c) availability of clinical characteristics.
Exclusion Criteria:
- (a) preoperative therapy (neoadjuvant chemotherapy or radiotherapy) performed,
- (b) suffering from other tumor disease before or at the same time.
- (c) Contain other pathological components such as squamous cell lung carcinoma (SCC) or small cell lung carcinoma (SCLC) or
- (d) poor image quality.
Inclusion Criteria of immunotherapy cohort:
- (a) that were diagnosed as advanced NSCLC
- (b) Both standard Chest CT scans with contrast enhancement performed <3 months before and after first dose of immunotherapy are available;
- (c) availability of clinical characteristics.
Exclusion Criteria of immunotherapy cohort:
- (a) Ever receiving pulmonary operation on the same side of the lesion.
- (b) suffering from other tumor disease before or at the same time.
- (c) Contain other pathological components( SCLC or lymphoma) or
- (d) poor image quality.
- (e) incomplete clinical data.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
Internal cohort
The internal cohort was retrospective enrolled in Guangdong Provincial People's hospital from March 1, 2015 to December 31,2019.
Patients with single pulmonary lesion underwent preoperative chest CT scan and histologically confirmed precancerous lesions or early stage lung adenocarcinoma after thoracic surgery was included.
|
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
|
External cohort 1
The same inclusion/exclusion criteria were applied for another independent centers, Sun Yat-sen Memorial Hospital ,Guangdong Province, China, forming an external validation cohort of 73 patients
|
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
|
External cohort 2
The same inclusion/exclusion criteria were applied for another independent centers, Zhoushan Lung Cancer Institution, Zhejiang Province, China, forming second external validation cohort of 30 patients
|
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
|
Immune Cohort
The internal cohort was retrospective enrolled in Guangdong Provincial People's hospital from March 1, 2015 to May 31,2020.
Patients with advanced lung cancer underwent preoperative chest CT scan and histologically confirmed NSCLC before receiving immunotherapy was included.
|
Different radiomic and machine learning strategies for radiomic features extraction, sorting features and model constriction
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Pathological subtype
Time Frame: 5 years
|
Pathological type of pulmonary nodules
|
5 years
|
Objective Response Rate (ORR)
Time Frame: 5 years
|
Rate of ORR in all subjects for the patients who receiving immunotherapy
|
5 years
|
Progression-free survival (PFS)
Time Frame: 5 years
|
From enrollment to progression or death (for any reason) in immunotherapy cohort
|
5 years
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Overall survival (OS)
Time Frame: 5 years
|
From enrollment to death (for any reason) in immunotherapy cohort
|
5 years
|
Clinical Benefit Rate (CBR)
Time Frame: 5 years
|
Rate of CBR greater than or equal to 24 weeks in all subjects
|
5 years
|
Collaborators and Investigators
Collaborators
Investigators
- Study Chair: Haiyu Zhou, PhD, Guangdong Provincial People's Hospital
- Principal Investigator: Luyu Huang, Guangdong Provincial People's Hospital
- Study Director: Herui Yao, PhD, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Study Director: Yunfang Yu, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
- Study Director: Hanbo Cao, PhD, Zhoushan Lung Cancer Institution
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Anticipated)
Study Completion (Anticipated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- SYSEC-KY-KS-2019-107
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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