ArticleThe Journal of international medical research2021
A novel prognostic model for angioimmunoblastic T-cell lymphoma: A retrospective study of 55 cases.
Article in The Journal of international medical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 4 citations in OpenAlex.
- Predicting one-year overall survival in patients with AITL using machine learning algorithms: a multicenter study.Scientific reports · 2025Article
- Predicting the efficiency of chidamide in patients with angioimmunoblastic T-cell lymphoma using machine learning algorithm.Frontiers in pharmacology · 2024Article
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12 authors at 1 institution in 1 country.
Funding
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Abstract
objectiveTo explore prognostic factors and develop an accurate prognostic prediction model for angioimmunoblastic T-cell lymphoma (AITL).
methodsClinical 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.
resultsThe 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.
conclusionsOur prognostic model based on pneumonia, and serous cavity effusions at initial diagnosis enabled a balanced classification of AITL patients into different risk groups.
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