Clinical trial · Observational
CT-based Radiomic Algorithm for Assisting Surgery Decision and Predicting Immunotherapy Response of NSCLC
NCT04452058CI-TRIAL-00045719TOP-RLCunknownClinicalTrials.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 was to investigate whether the combined radiomic model based on radiomic features extracted from focus and perifocal area (5mm) can effectively improve prediction performance of distinguishing precancerous lesions from early-stage lung adenocarcinoma, which could assist clinical decision making for surgery indication. Besides, response and long term clinical benefit of immunotherapy of advanced NSCLC lung cancer patients could also be predicted by this strategy.
Conditions
Conditions (3)
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 |
| Predictive Cancer Model | — | UNRESOLVED | — |
| Preinvasive Adenocarcinoma | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Radiomic Algorithm | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (4)
- label
- Internal cohort
- description
- 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.
- interventionNames
- Other: Radiomic Algorithm
- label
- External cohort 1
- description
- 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
- interventionNames
- Other: Radiomic Algorithm
- label
- External cohort 2
- description
- 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
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
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.
References
Publications (0)
Data not yet available
No reference posted for this study.