The Journal of international medical research · 2021
A novel prognostic model for angioimmunoblastic T-cell lymphoma: A retrospective study of 55 cases.
СтатьяНазвание и аннотация: Перевод в очереди
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Sun Jie, He Sha, Cen Hong, Zhou Da, Li Zhe, Wang Ming-Yue, Ke Qing, Guo Bao-Ping, Liao Cheng-Cheng, Rong Chao, Zhong Da-Ni, Tan Xiao-Hong
Аннотация
OBJECTIVE: To explore prognostic factors and develop an accurate prognostic prediction model for angioimmunoblastic T-cell lymphoma (AITL).
METHODS: Clinical data from Chinese patients with newly diagnosed AITL were retrospectively analysed. Overall survival (OS) and progression-free survival (PFS) were estimated using Kaplan-Meier method survival curves; prognostic factors were determined using a Cox proportional hazards model. The sensitivity and specificity of the predicted survival rates were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves.
RESULTS: The estimated 5-year OS and PFS of 55 eligible patients with AITL were 22% and 3%, respectively. Multivariate analysis showed that the presence of pneumonia, and serous cavity effusions at initial diagnosis were significant prognostic factors for OS. Based on AUC ROC values, our novel prognostic model was superior to IPI and PIT based models and suggested better diagnostic accuracy.
CONCLUSIONS: Our prognostic model based on pneumonia, and serous cavity effusions at initial diagnosis enabled a balanced classification of AITL patients into different risk groups.
METHODS: Clinical data from Chinese patients with newly diagnosed AITL were retrospectively analysed. Overall survival (OS) and progression-free survival (PFS) were estimated using Kaplan-Meier method survival curves; prognostic factors were determined using a Cox proportional hazards model. The sensitivity and specificity of the predicted survival rates were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves.
RESULTS: The estimated 5-year OS and PFS of 55 eligible patients with AITL were 22% and 3%, respectively. Multivariate analysis showed that the presence of pneumonia, and serous cavity effusions at initial diagnosis were significant prognostic factors for OS. Based on AUC ROC values, our novel prognostic model was superior to IPI and PIT based models and suggested better diagnostic accuracy.
CONCLUSIONS: Our prognostic model based on pneumonia, and serous cavity effusions at initial diagnosis enabled a balanced classification of AITL patients into different risk groups.