Actively Recruiting
Study on Treatment Approaches for Children With Rhabdomyosarcoma Using Risk-Based Stratification and Chemotherapy Regimens
Led by Yizhuo Zhang · Updated on 2025-02-20
300
Participants Needed
1
Research Sites
13 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are evaluating the SYSUCC-RMS regimen for children with rhabdomyosarcoma, a type of pediatric cancer. This study aims to understand how effective and safe this treatment is, while also exploring how combining radiotherapy with chemotherapy affects survival rates across different risk groups low, medium, high, and very high risk. The study is a Phase 3 clinical trial led by Yizhuo Zhang. Participants receive one of several combination chemotherapy regimens based on their risk level low risk patients receive VAC, intermediate risk patients receive VACVII, high risk patients receive CAVIE, and very high risk patients receive CAVVIP. The study follows a single-arm design and evaluates the treatments over various risk groups, focusing on the impact of concurrent therapies on survival. During the study, researchers will monitor participants for up to 10 years, assessing outcomes such as objective response rate, disease control rate, progression-free survival, and overall survival. Safety of the SYSUCC-RMS regimen will also be tracked throughout this period. Participants health status will be regularly evaluated to understand the long-term effects and treatment outcomes.
CONDITIONS
Brief Title
A Prospective Clinical Cohort Study on Stratified Treatment of Rhabdomyosarcoma Based on Risk Factors.
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Age between 0 and 18 years, any gender
- Diagnosed with tumor by histopathology or bone marrow cytology
- Receiving first treatment for the tumor
- ECOG score of 2 or less
- Expected survival time longer than 8 months
- Parent or guardian has signed informed consent
You will not qualify if you...
- Presence of immunodeficiency disease
- Having a second tumor
Research Team
S
Suying Lu
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