This study aims to characterize the epidemiology, clinicopathologic features, and survival outcomes of Chinese patients with PTCL; to develop and validate prognostic models to this population; to compare the real-world effectiveness and safety of alternative therapeutic strategies; to elucidate molecular mechanisms underlying treatment resistance and relapse; to identify actionable targets and predictive biomarkers.
Due to disease heterogeneity and variability in clinical practice, establishing a large-scale Chinese PTCL database to characterize real-world treatment patterns and clinical outcomes is a critical undertaking. A retrospective cohort will define the clinical epidemiology of the disease, while a prospective cohort will delineate current treatment pathways and outcomes in routine practice and explore the molecular features of PTCL in the Chinese population, thereby providing evidence to support precision therapy.
Study Type
OBSERVATIONAL
Enrollment
3,000
Observational
Fudan University Shanghai Cancer Center
Shanghai, Shanghai Municipality, China
RECRUITINGDistribution of PTCL Histological Subtypes according to WHO 2016 Classification
The number and percentage of participants diagnosed with each specific subtype of Peripheral T-Cell Lymphoma (e.g., PTCL-NOS, AITL, ALCL, ENKTL, etc.). Diagnosis is confirmed by pathological review based on the WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues (Revised 4th edition, 2017).
Time frame: Baseline (at the time of enrollment or diagnosis)
Overall Survival (OS)
OS is defined as the time from the date of pathological diagnosis to the date of death from any cause. For patients who are lost to follow-up, survival time will be censored at the date of last contact.
Time frame: 5 year after diagnosis
Progression-Free Survival (PFS)
PFS is defined as the time from the date of pathological diagnosis to the date of the first documented disease progression (PD) or death from any cause, whichever occurs first. Disease progression is assessed based on the investigator's evaluation of radiological and clinical data.
Time frame: 5 year after diagnosis
Frequency of Specific Genetic Mutations
Evaluation of the number and percentage of participants carrying specific genetic alterations. Key biomarkers to be assessed include: Gene Mutations: TET2, DNMT3A, IDH2, RHOA, TP53, EZH2, and genes related to the PI3K-AKT pathway, assessed by Next-Generation Sequencing (NGS) or ct-DNA analysis. Correlations between these biomarkers and clinical outcomes (response, survival) will be analyzed.
Time frame: Up to 5 years (at Baseline and at time of Disease Progression/Relapse)
Expression levels of biomarker proteins
Protein/Pathological Markers: Expression of PD-1/PD-L1, CD30, Ki-67 proliferation index, and EBV status, assessed by Immunohistochemistry (IHC) or In Situ Hybridization (ISH). Correlations between these biomarkers and clinical outcomes (response, survival) will be analyzed.
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Time frame: Up to 5 years (at Baseline and at time of Disease Progression/Relapse)
Incidence of Treatment-Emergent Adverse Events (TEAEs) assessed by CTCAE v5.0
Safety will be assessed by recording the number of participants with adverse events, graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE) version 5.0. This includes treatment-related deaths and incidence of second primary malignancies.
Time frame: Up to 5 years