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.
Study Type
OBSERVATIONAL
Enrollment
100
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.
Time frame: From baseline to disease response and follow-up assessments, up to 3 years.
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