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Clinical Characteristics, Outcomes, and Risk Factors for Patients with Diffuse Large B-Cell Lymphoma and Development of Nomogram to Identify High-Risk Patients

OBJECTIVES: To analyse the clinical features, outcomes, and risk factors of patients with diffuse large B-cell lymphoma (DLBCL) in China, with the aim to establish a new prognostic model based on risk factors. METHODS: Clinical features and outcomes of 564 patients newly diagnosed with DLBCL from Ja...

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Detalles Bibliográficos
Autores principales: Zhao, Jinrong, Zhang, Yan, Wang, Wei, Zhang, Wei, Zhou, Dao-bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9691331/
https://www.ncbi.nlm.nih.gov/pubmed/36439900
http://dx.doi.org/10.1155/2022/8395246
Descripción
Sumario:OBJECTIVES: To analyse the clinical features, outcomes, and risk factors of patients with diffuse large B-cell lymphoma (DLBCL) in China, with the aim to establish a new prognostic model based on risk factors. METHODS: Clinical features and outcomes of 564 patients newly diagnosed with DLBCL from Jan 2009 to May 2017 were analyzed retrospectively. Variables were screened by LASSO regression and nomogram was constructed. RESULTS: The 5-year overall survival (OS) of the cohort was 75%. The 5-year OS of patients differentiated by International Prognostic Index (IPI) score was 90% (score 0–2), 73% (score 3), and 51% (score 4-5), respectively. Age > 60, Eastern Cooperative Oncology Group (ECOG) > 1, Ann Arbor stage III-IV, bone marrow involvement, low level of albumin (ALB), and lymphatic/monocyte ratio (LMR) were independent predictors of OS. The predictive model was developed based on factors including age, bone marrow involvement, LMR, ALB, and ECOG scores. The predictive ability of the model (AUC, 0.77) was better than that of IPI (AUC, 0.74) and NCCN-IPI (AUC, 0.69). The 5-year OS of patients in the low-, intermediate-, and high-risk groups identified by the new predictive model was 89%, 70%, and 33%, respectively. CONCLUSIONS: The new prediction model had better predictive performance and could better identify high-risk patients.