Development of Nomogram for Predicting the Overall Survival of Diffuse Large B-Cell Lymphoma (DLBCL) Patients Based on Clinical Data and Systemic Inflammation Markers

Suddin, Sulasri; Hardianti, Mardiah Suci; Adi-Kusumo, Fajar; Gunardi, Gunardi

doi:10.31557/APJCP.2025.26.6.2145

Development of Nomogram for Predicting the Overall Survival of Diffuse Large B-Cell Lymphoma (DLBCL) Patients Based on Clinical Data and Systemic Inflammation Markers

Document Type : Research Articles

Authors

¹ Department of Mathematics, Faculty of Mathematics and Natural Sciences, Univeristas Gadjah Mada, Yogyakarta, Indonesia.

² Universitas Timor, Kefamenanu, Indonesia.

³ Division of Hematology and Medical-Oncology, Department of Internal Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/ Dr. Sardjito Hospital, Yogyakarta, Indonesia.

10.31557/APJCP.2025.26.6.2145

Abstract

Objective: Diffuse large B-cell lymphoma (DLBCL) is the most prevalent non-Hodgkin lymphoma and an aggressive blood malignancy. Despite the development of prognostic factors for DLBCL across clinical and molecular aspects, the accessibility and affordability can vary, specifically in developing countries. Therefore, this study aimed to examine the systemic immune inflammation index (SII), a predictive factor for DLBCL and generated from basic blood data. The study also established an effective predictive nomogram by integrating clinicopathological factors to predict overall survival (OS). Methods: A retrospective analysis was carried out on the laboratory and clinicopathological data of DLBCL patients from January 2012 to December 2020 from the Division of Hematology and Medical Oncology, Department of Internal Medicine, Dr. Sardjito Hospital, Yogyakarta, Indonesia. Cox survival analyses, both univariate and multivariate, were used to find prognostic markers associated with OS. The dynamic nomogram was created using all independent prognostic variables. Results: A total of 94 patients were included and based on the Akaike Information Criterion values from multivariate Cox analysis, absolute monocyte count (AMC), platelet count (PLT), platelet-to-lymphocytes ratio (PLR), and SII were independent prognostic factors of OS in DLBCL patients, and are included in the nomogram. The area under the curve in this group was 0.8, while the nomogram’s C-index for predicting OS was 0.74. Conclusion: This study found that monocyte count, platelet count, PLR, and SII can predict OS in our study population of Indonesian DLBCL. Nomogram created from this findings is a new and potentially effective model for predicting OS.

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