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Characteristics and predictive model for diffuse large B-cell lymphoma with early chemoimmunotherapy failure.

Ying-Yu Dong1, Qing Shi1, Wen Wu1

  • 1Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics; National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Frontiers in Immunology
|July 1, 2025
PubMed
Summary

Identifying early chemoimmunotherapy failure (ECF) in diffuse large B-cell lymphoma is crucial. This study developed a predictive model for ECF, identifying key clinical and molecular factors to improve patient outcomes.

Keywords:
CAR- T cellsDLBCL - diffuse large B cell lymphomaRCHOP-like regimenchemo-resistantearly chemoimmunotherapy failurenomogram

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Area of Science:

  • Hematology
  • Oncology
  • Genetics

Background:

  • Refractory or relapsed diffuse large B-cell lymphoma (DLBCL) has poor outcomes.
  • Early chemoimmunotherapy failure (ECF) within 12 months of diagnosis has a dismal 2-year overall survival (OS) of 24.7%.

Purpose of the Study:

  • To identify predictors of ECF in DLBCL patients.
  • To develop a predictive model for early recognition of ECF.
  • To improve therapeutic strategies and outcomes for chemo-resistant DLBCL patients.

Main Methods:

  • Retrospective analysis of 2038 newly diagnosed DLBCL patients treated with R-CHOP/RminiCHOP or R-CHOP-based immunochemotherapy.
  • Multivariate analysis to identify independent predictors of ECF.
  • Development and validation of a nomogram-based ECF prediction model.

Main Results:

  • ECF patients were associated with elderly age, advanced Ann Arbor stage, elevated LDH, poor performance status, extranodal involvement, double expressor lymphoma (DEL), and non-GCB subtype.
  • TP53, FOXO1, and FBXW7 mutations were frequent in ECF.
  • Elderly age, advanced stage, elevated LDH, DEL, and TP53 or FOXO1 mutations were independent predictors of ECF.

Conclusions:

  • A nomogram predicting ECF was established with good predictive power in both Chinese and Western cohorts.
  • The ECF prediction model enables early identification of high-risk patients.
  • Optimizing therapeutic strategies for early identified ECF patients can improve outcomes.