Cancer medicine · 2023
A promising prognostic model for predicting survival of patients with HIV-related diffuse large B-cell lymphoma in the cART era.
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Chen Juanjuan, Wu Yihua, Kang Zixin, Qin Shanfang, Ruan Guangjing, Zhao Han, Tao Xin, Xie Zhiman, Peng Jie
Аннотация
BACKGROUND: Optimization of risk stratification is important for facilitating prognoses and therapeutic decisions regarding diffuse large B-cell lymphoma (DLBCL). However, a simple and applicable prognostic tool is lacking for individuals with human immunodeficiency virus (HIV)-related DLBCL in the era of combined antiretroviral therapy (cART).
METHODS: This retrospective multicenter observational study included 147 HIV-related DLBCL patients with histologically confirmed DLBCL from 2013 to 2020. The total group was divided into training (n = 78) and validation (n = 69) cohorts to derive the best prognostic score. Clinicopathological and characteristic biomarkers correlated with clinical outcomes were analyzed.
RESULTS: Age, Ann Arbor stage, lactate dehydrogenase (LDH) ratio, bulky disease, and red blood cell distribution width (RDW) ratio retained robust independent correlations with overall survival (OS) in multivariate analysis. A new and practical prognostic model was generated and externally validated, classifying patients into three categories with significantly different survival rates. Moreover, the new index outperformed the International Prognostic Index (IPI) score (area under the curve values of 0.94 vs. 0.81 in the training cohort and 0.85 vs. 0.74 in the validation cohort, C-indices of 0.80 vs. 0.70 in the training cohort and 0.74 vs. 0.70 in the validation cohort, and integrated discrimination improvement values of 0.203 in the training cohort and 0.175 in the validation cohort) and was better at defining intermediate- and high-risk groups. The calibration curves performed satisfactorily for predicting 3-year OS in the training and validation cohorts.
CONCLUSIONS: We developed and validated a simple and feasible prognostic model for patients with HIV-related DLBCL that had more discriminative and predictive accuracy than the IPI score for risk stratification and individualized treatment in the cART era.
METHODS: This retrospective multicenter observational study included 147 HIV-related DLBCL patients with histologically confirmed DLBCL from 2013 to 2020. The total group was divided into training (n = 78) and validation (n = 69) cohorts to derive the best prognostic score. Clinicopathological and characteristic biomarkers correlated with clinical outcomes were analyzed.
RESULTS: Age, Ann Arbor stage, lactate dehydrogenase (LDH) ratio, bulky disease, and red blood cell distribution width (RDW) ratio retained robust independent correlations with overall survival (OS) in multivariate analysis. A new and practical prognostic model was generated and externally validated, classifying patients into three categories with significantly different survival rates. Moreover, the new index outperformed the International Prognostic Index (IPI) score (area under the curve values of 0.94 vs. 0.81 in the training cohort and 0.85 vs. 0.74 in the validation cohort, C-indices of 0.80 vs. 0.70 in the training cohort and 0.74 vs. 0.70 in the validation cohort, and integrated discrimination improvement values of 0.203 in the training cohort and 0.175 in the validation cohort) and was better at defining intermediate- and high-risk groups. The calibration curves performed satisfactorily for predicting 3-year OS in the training and validation cohorts.
CONCLUSIONS: We developed and validated a simple and feasible prognostic model for patients with HIV-related DLBCL that had more discriminative and predictive accuracy than the IPI score for risk stratification and individualized treatment in the cART era.