Construction and validation of prognostic scoring models to risk stratify patients with acquired immune deficiency syndrome‐related diffuse large B cell lymphoma

Author:

Zhao Han1,Liu Rongqiu2ORCID,Tao Yu3,Bertero Luca4,Feng Lizhi1,Liu Bo1,Chen Zhimin1,Guan Jialong1,Liao Baolin1,Li Linghua1,He Haolan1,You Hua35

Affiliation:

1. Infectious Diseases Center, Guangzhou Eighth People's Hospital Guangzhou Medical University Guangzhou China

2. Department of Oncology Affiliated Cancer Hospital & Institute of Guangzhou Medical University Guangzhou China

3. Department of Pediatric Hematology and Oncology, Laboratory for Excellence in Systems Biomedicine of Pediatric Oncology, Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders, National Clinical Research Center for Child Health and Disorders Children's Hospital of Chongqing Medical University Chongqing China

4. Department of Medical Sciences, Pathology Unit University of Turin Torino Italy

5. Lead Contact

Abstract

AbstractAcquired immune deficiency syndrome (AIDS)‐related diffuse large B cell lymphoma (AR‐DLBCL) is a rare disease with a high risk of mortality. There is no specific prognostic model for patients with AR‐DLBCL. A total of 100 patients diagnosed with AR‐DLBCL were enrolled in our study. Clinical features and prognostic factors for overall survival (OS) and progression‐free survival (PFS) were evaluated by univariate and multivariate analyses. Central nervous system (CNS) involvement, opportunistic infection (OI) at lymphoma diagnosis, and elevated lactate dehydrogenase (LDH) were selected to construct the OS model; CNS involvement, OI at lymphoma diagnosis, elevated LDH, and over four chemotherapy cycles were selected to construct the PFS model. The area under the curve and C‐index of GZMU OS and PFS models were 0.786/0.712; 0.829/0.733, respectively. The models we constructed showed better risk stratification than International Prognostic Index (IPI), age‐adjusted IPI, and National Comprehensive Cancer Network‐IPI. Furthermore, in combined cohort, the Hosmer−Lemeshow test showed that the models were good fits (OS: p = 0.8244; PFS: p = 0.9968) and the decision curve analysis demonstrated a significantly better net benefit. The prognostic efficacy of the proposed models was validated independently and outperformed the currently available prognostic tools. These novel prognostic models will help to tackle a clinically relevant unmet need.

Publisher

Wiley

Subject

Infectious Diseases,Virology

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