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This is a multicenter prospective study to develop and validate a multimodal, deep learning-based model for predicting treatment response in patients with extranodal natural killer/T-cell lymphoma (NKTCL) receiving first-line asparaginase-based therapy.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| First-line Asparaginase-based Treatment Cohort | Participants in this cohort are patients with extranodal natural killer/T-cell lymphoma (NKTCL) who are planned to receive standard first-line asparaginase-based chemotherapy according to institutional practice. Pretreatment clinical data, contrast-enhanced magnetic resonance imaging (MRI) of the nasopharynx and neck, and digital pathology images from hematoxylin and eosin (H&E)-stained tumor sections will be collected. Patients will be followed for progression-free survival and overall survival according to routine follow-up schedule. |
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| Measure | Description | Time Frame |
|---|---|---|
| Predictive accuracy of first-line treatment response (CR vs non-CR) according to Lugano 2014 criteria | The primary outcome is the predictive performance of the multimodal deep learning model for first-line treatment response in patients with extranodal natural killer/T-cell lymphoma (NKTCL). Treatment response is assessed according to the Lugano 2014 criteria. Model performance will be evaluated by receiver operating characteristic (ROC) analysis and quantified using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value, and negative predictive value by comparing model predictions with observed clinical response. | From baseline to disease response and follow-up assessments, up to 3 years. |
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Inclusion Criteria:
Exclusion Criteria:
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The study population includes adult patients with pathologically confirmed extranodal natural killer/T-cell lymphoma (NKTCL) receiving first-line asparaginase-based chemotherapy or chemoradiotherapy, with available pretreatment MRI or H&E-stained whole-slide pathology images. Patients will be prospectively followed for treatment response and survival outcomes.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Qingqing Cai, MD. PhD. | Contact | 0208734282 | caiqq@sysucc.org.cn |
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