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December 8, 2025Blood

Development of a machine learning model to predict overall survival in patients with peripheral T-cell lymphoma in a minority enriched population

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Authors

NLNicholas LiECEmma CordoverSHSung Chul Hwang

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Overview

Model demonstrates robust predictive capacity for overall survival in peripheral T-cell lymphoma, indicating potential for clinical application.

Key Points

  • This research aims to develop a machine learning model for predicting overall survival in patients with peripheral T-cell lymphoma.
  • Developed a ML model using demographic, clinical, and laboratory data from 97 PTCL patients
  • Data collected from Montefiore Medical Center via manual chart review
  • Applied random forest survival model and assessed performance with C-index and Brier scores
  • ML model showed a C-index of 0.86 for the full dataset before decreasing to 0.68 on validation
  • Identified key predictive features including baseline LDH and ECOG score
  • 57.7% of patients died during the study period, highlighting the poor prognosis associated with PTCL

Cite This Study

Li et al. (2025) studied this question.

synapsesocial.com/papers/69362f514fa91c937236d97ehttps://doi.org/10.1182/blood-2025-2568
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  4. 4Peripheral T-cell lymphomas: Real-world insights into clinical features and prognosis2025 · 1 citations
  5. 5Prognostic survival models for diffuse large B-cell lymphoma using statistical and machine learning approaches2026