Ignite Creation Date:
2025-12-26 @ 1:19 PM
Ignite Modification Date:
2026-01-14 @ 3:50 AM
Study NCT ID:
NCT04722406
Status:
UNKNOWN
Last Update Posted:
2021-03-17
First Post:
2021-01-18
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Tumor Growth Rate (TGR) Predicts Clinical Outcomes for Advanced Non-small Cell Lung Cancer Undergoing Immunotherapy.
Sponsor:
Sun Yat-sen University
Organization:
Study Overview
Official Title:
Tumor Growth Rate (TGR) as an Early Predictor of Clinical Outcomes in Advanced Non-small Cell Lung Cancer Treated With PD-1 Axis Inhibitors.
Status:
UNKNOWN
Status Verified Date:
2021-03
Last Known Status:
RECRUITING
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
We hypothesized that TGR could serve as an early predictor of outcomes for aNSCLC patients undergoing immune checkpoint inhibitors (ICIs). A retrospective analysis was conducted to investigate the association of TGR with response and long-term survival of aNSCLC patients undergoing ICI therapy.
Detailed Description:
Tumor growth rate (TGR) signifies percentage change in tumor size per month (%/m). Electronic medical records were retrospectively reviewed for all histologically confirmed aNSCLC patients undergoing anti-PD-1/PD-L1 therapy at Sun Yat-Sen University Cancer Center (SYSUCC) between August 2016 and June 2018.
All response and outcome evaluation were determined as per RECIST 1.1 by two senior radiologists blinded to patients'information. Discrepancy was solved by consensus.
X-tile software was used to determine cut-off values that maximumly differentiate overall survival (OS). Log-rank tests and Cox regression models were performed for survival analysis. The predictive value of TGR for clinical outcomes in ICI-treated aNSCLC patients was validated in two external cohorts, recruited form Guangdong Province Traditional Chinese Medical Hospital and Shanghai Chest Hospital.
All response and outcome evaluation were determined as per RECIST 1.1 by two senior radiologists blinded to patients'information. Discrepancy was solved by consensus.
X-tile software was used to determine cut-off values that maximumly differentiate overall survival (OS). Log-rank tests and Cox regression models were performed for survival analysis. The predictive value of TGR for clinical outcomes in ICI-treated aNSCLC patients was validated in two external cohorts, recruited form Guangdong Province Traditional Chinese Medical Hospital and Shanghai Chest Hospital.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: