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<p>Mantle cell lymphoma (MCL) exhibits significant biological and clinical heterogeneity, necessitating a refined prognostic model. According to the drawbacks of existing models which do not truly define the complexity of the disease, we used the clinical and molecular data from nine medical centers of China to validate the predictive utility of progression of disease within 24 months (POD24), and also established a novel prognostic risk model to predict the survival outcome of MCL patients. POD24 occurred in 37.7% of evaluable patients, with the median over survival being 21 months (vs. 122 months for those without POD24, <i>P</i> &lt; 0.0001). The POD24-based risk model had the highest sensitivity to predict survival with the most satisfying AUC value for risk score (AUC = 0.869). In conclusion, we confirm the obviously predictive performance of POD24 and established a novel risk model combined POD24 and clinical factors. Our new prognostic model might be helpful in effectively classify MCL patients with high-risk groups in terms of survival rate, which may help in selecting high-risk MCL patients for more intensive treatment at time of relapse.</p>

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POD24-Based prognostic signature enables personalized risk stratification in mantle cell lymphoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月13日

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  • Yizi He,
  • Caiqin Wang,
  • Tao Pan,
  • Qingqing Cai,
  • Dehui Zhou,
  • Huilai Zhang,
  • Rong Liang,
  • Dongfeng Zeng,
  • Haige Ye,
  • Yun Liang,
  • Xiuhua Sun,
  • Ling Xiao,
  • Hui Zhou

摘要

Mantle cell lymphoma (MCL) exhibits significant biological and clinical heterogeneity, necessitating a refined prognostic model. According to the drawbacks of existing models which do not truly define the complexity of the disease, we used the clinical and molecular data from nine medical centers of China to validate the predictive utility of progression of disease within 24 months (POD24), and also established a novel prognostic risk model to predict the survival outcome of MCL patients. POD24 occurred in 37.7% of evaluable patients, with the median over survival being 21 months (vs. 122 months for those without POD24, P < 0.0001). The POD24-based risk model had the highest sensitivity to predict survival with the most satisfying AUC value for risk score (AUC = 0.869). In conclusion, we confirm the obviously predictive performance of POD24 and established a novel risk model combined POD24 and clinical factors. Our new prognostic model might be helpful in effectively classify MCL patients with high-risk groups in terms of survival rate, which may help in selecting high-risk MCL patients for more intensive treatment at time of relapse.