What question did this study set out to answer?

This research aims to explore the applicability of deep learning and radiomics in prognostic stratification of patients with natural killer/T-cell lymphoma.

May 29, 2026Journal of Clinical Oncology

Deep learning–based PET/CT radiomics-clinical model for prognostic stratification and immunotherapy exploration in natural killer/T-cell lymphoma.

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Authors

TLTongyu LinUniversity of Electronic Science and Technology of China ZCZegeng ChenSun Yat-sen University HHHuangming HongUniversity of Electronic Science and Technology of China

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Randomized trial shows a deep learning model predicts outcomes in NKTCL, suggesting immunotherapy benefits for high-risk patients.

Key Points

This research aims to explore the applicability of deep learning and radiomics in prognostic stratification of patients with natural killer/T-cell lymphoma.
Retrospective multicenter study involving 425 NKTCL patients from four hospitals.
Patients were randomly assigned to training or validation cohorts for model development.
Radiomics features from pretreatment PET/CT images were used to construct prognostic models.
The XGBoost-based radiomics model achieved PFS AUC of 0.977 and OS AUC of 0.946 in the training cohort.
Radiomic-Clinical Prognostic Model stratified patients into high- and low-risk groups (all P < 0.001).
High-risk patients showed significant improvement in 3-year PFS (67.7% vs. 21.7%) and 3-year OS (81.7% vs. 39.6%) with PD-1 inhibitor therapy (both P < 0.001).

Cite This Study

Lin et al. (2026) studied this question.

synapsesocial.com/papers/6a192d4afab5b468c44161db https://doi.org/10.1200/jco.2026.44.16_suppl.7072

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Deep learning–based PET/CT radiomics-clinical model for prognostic stratification and immunotherapy exploration in natural killer/T-cell lymphoma.

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Key Points

Cite This Study

Deep learning–based PET/CT radiomics-clinical model for prognostic stratification and immunotherapy exploration in natural killer/T-cell lymphoma.

Discussion

Member takes

Implication

Key Points

Cite This Study

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