Ignite Creation Date:
2025-12-24 @ 2:14 PM
Ignite Modification Date:
2026-01-28 @ 1:23 PM
Study NCT ID:
NCT07144995
Status:
NOT_YET_RECRUITING
Last Update Posted:
2025-08-28
First Post:
2025-08-05
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
MAIC of Fruquintinib Plus Paclitaxel Versus Ramucirumab Plus Paclitaxel in Advanced G/GEJ Adenocarcinoma
Sponsor:
Sun Yat-sen University
Organization:
Study Overview
Official Title:
Adjusted Indirect Treatment Comparison of Fruquintinib-based Therapy Versus Standard Care in Advanced Gastric/Gastroesophageal Junction Adenocarcinoma: A MAIC Analysis.
Status:
NOT_YET_RECRUITING
Status Verified Date:
2025-08
Last Known Status:
None
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:
This anchored matching-adjusted indirect comparison (MAIC) evaluates the relative efficacy of fruquintinib-paclitaxel (using IPD from the FRUTIGA trial, n=703) versus ramucirumab-paclitaxel (using published AgD from RAINBOW-Asia, n=440) in advanced gastric/GEJ adenocarcinoma. Baseline characteristics are adjusted via entropy balancing weights. Primary endpoint is progression-free survival (PFS) analyzed by Bucher method; secondary endpoints include overall survival (OS) and objective response rate (ORR). Sensitivity analyses comprise restricted mean survival time (RMST) analysis and simulated treatment comparison (STC).
Detailed Description:
This retrospective MAIC analysis employs individual patient data (IPD) from the FRUTIGA trial (fruquintinib arm) and published aggregate data (AgD) from RAINBOW-Asia (ramucirumab arm), with placebo as the common anchor. Pseudo individual participant data (Pseudo-IPD) for the RAINBOW-Asia trial were reconstructed from published Kaplan-Meier curves using the Guyot algorithm (2012).
•Weighting Methodology: Seven prognostic factors balanced: age \<65, male sex, ECOG 0, GEJ primary, peritoneal metastases, metastatic sites, prior doublet chemotherapy Optimization via BFGS algorithm (convergence tolerance 1e-6) Effective sample size (ESS) retention: \> 50%
•Statistical Analysis: Primary: Adjusted PFS hazard ratio (HR) using Bucher method with 95% bootstrap CI (100 iterations) Secondary: Weighted Cox models for OS; logistic regression for ORR/DCR Sensitivity: Simulated Treatment Comparison (STC) and covariate threshold analyses
•Sensitivity Analyses: RMST analyses were conducted as supportive evidence alongside primary Cox models for time-to-event endpoints violating proportional hazards assumptions.
Restricted mean survival time (RMST) Simulated Treatment Comparison (STC) Bootstrap confidence intervals (100 iterations)
•Weighting Methodology: Seven prognostic factors balanced: age \<65, male sex, ECOG 0, GEJ primary, peritoneal metastases, metastatic sites, prior doublet chemotherapy Optimization via BFGS algorithm (convergence tolerance 1e-6) Effective sample size (ESS) retention: \> 50%
•Statistical Analysis: Primary: Adjusted PFS hazard ratio (HR) using Bucher method with 95% bootstrap CI (100 iterations) Secondary: Weighted Cox models for OS; logistic regression for ORR/DCR Sensitivity: Simulated Treatment Comparison (STC) and covariate threshold analyses
•Sensitivity Analyses: RMST analyses were conducted as supportive evidence alongside primary Cox models for time-to-event endpoints violating proportional hazards assumptions.
Restricted mean survival time (RMST) Simulated Treatment Comparison (STC) Bootstrap confidence intervals (100 iterations)
Study Oversight
Has Oversight DMC:
None
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?: