JoVE - Journal of Visualized Experiments
JoVE Visualize
Contact Us

Establishment and Evaluation of Prognostic Prediction Model for Diffuse Large B-Cell Lymphoma Patients Based on International Prognostic Index and FAT4, TP53 Mutation

  • 0Department of Hematology, The People's Hospital of Xinjiang Uygur Autonomous Region, Nanjing, China, 489411975@qq.com.
Acta Haematologica +

|

October 2, 2025

|

October 2, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study developed a new prognostic model (FAT4-TP53-IPI) for diffuse large B-cell lymphoma (DLBCL) by integrating genetic mutations with the IPI score. The model improves prognosis prediction for DLBCL patients receiving immunotherapy.

Area Of Science

  • Oncology
  • Genetics
  • Hematology

Background

  • Diffuse large B-cell lymphoma (DLBCL) exhibits significant clinical and genetic heterogeneity.
  • This heterogeneity leads to variable patient prognoses, necessitating improved predictive tools.

Purpose Of The Study

  • To develop and validate a novel prognostic model for DLBCL.
  • To enhance the prognostic accuracy of the International Prognostic Index (IPI) by incorporating genetic mutation data.

Main Methods

  • High-throughput sequencing of 155 DLBCL patients to identify key gene mutations.
  • Cox regression analysis to identify prognostic factors for progression-free survival (PFS) and overall survival (OS).
  • Validation of the new FAT4-TP53-IPI model using C-index, ROC curves, calibration curves, and decision curve analysis (DCA).

Main Results

  • The FAT4-TP53-IPI model, incorporating IPI, FAT4, and TP53 mutations, demonstrated superior discriminative ability compared to the IPI alone.
  • The model showed good accuracy and clinical utility, effectively stratifying patients into high- and low-risk groups with significantly different survival outcomes (p < 0.01).

Conclusions

  • Integrating genetic mutation status (FAT4, TP53) significantly enhances the prognostic value of the IPI system in DLBCL.
  • The FAT4-TP53-IPI model offers a valuable tool for predicting prognosis in DLBCL patients undergoing rituximab-based immunotherapy.

Keywords: