Massachusetts General Hospital
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.
This study is a prospective, longitudinal observational study of patients with newly diagnosed or relapsed/refractory T-cell and NK-cell neoplasms, conducted across multiple participating institutions globally. Patients will be enrolled during their initial visit as new patients and will be followed for up to four years through the course of their clinical management. Data for routine demographics, baseline clinical features, including pathology, molecular information related to the tumor, radiology, treatment characteristics and quality of life (QoL) associated with their lymphoma care will b…
Inclusion Criteria: * Untreated, relapsed, or refractory histologically confirmed mature T-cell or NK-cell neoplasm. * All subtypes of PTCL are eligible except for T-cell large granular lymphocytic leukemia, cutaneous T-cell lymphoma such as but not limited to mycosis fungoides and transformation, Sézary syndrome, and primary cutaneous CD30+ disorders. Exclusion Criteria: * Precursor T/NK neoplasms, T-cell large granular lymphocytic leukemia, cutaneous T-cell lymphoma such as but not limited to mycosis fungoides and transformation, Sézary syndrome, and primary cutaneous CD30+ disorders. * A…