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A Global Study of the PETAL Consortium
Sponsor: Massachusetts General Hospital
Summary
The goal of this observational study is to correlate molecular alterations with outcomes including overall survival (OS), progression-free survival (PFS), response rates for patients with a new diagnosis, primary refractory or relapse, of mature T-cell and NK-cell neoplasms (TNKL). We hypothesize that machine learning can be leveraged to uncover distinct genetic vulnerabilities that underlie treatment response and resistance for patients with TNKL, thus moving towards personalized treatment solutions.
Official title: Integration of Machine Learning and Genomics to Predict Outcomes for Newly Diagnosed, Relapsed and Refractory Mature T-cell and NK/T-cell Lymphomas: a Global Study of the PETAL Consortium
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
1200
Start Date
2024-01-05
Completion Date
2028-01
Last Updated
2026-04-09
Healthy Volunteers
Yes
Conditions
Locations (14)
City of Hope
Duarte, California, United States
University of Colorado
Denver, Colorado, United States
Moffitt Cancer Center
Tampa, Florida, United States
Massachusetts General Hospital
Boston, Massachusetts, United States
Dana-Farber Cancer Institute
Boston, Massachusetts, United States
Mayo Clinic
Rochester, Minnesota, United States
Hackensack University Medical Center
Hackensack, New Jersey, United States
OhioHealth
Columbus, Ohio, United States
University of Pennsylvania
Philadelphia, Pennsylvania, United States
University of Virginia
Charlottesville, Virginia, United States
Royal Adelaide Hospital
Adelaide, South Australia, Australia
Peter MacCallum Cancer Centre
Melbourne, Victoria, Australia
Kyoto University
Kyoto, Japan
University of Cape Town
Cape Town, South Africa, South Africa