ArticleCancer management and research2023
A Novel and Validated Inflammation-Based Prognosis Score (IBPS) Predicts Outcomes in Patients with Diffuse Large B-Cell Lymphoma.
Article in Cancer management and research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- CAR T therapy in adult DLBCL patients in Slovenia: Evaluation of predictive scores for outcomes and adverse events.Human vaccines & immunotherapeutics · 2026Article
- Development and Validation of Prognostic Models for Treatment Response of Patients with B-Cell Lymphoma: Standard Statistical and Machine-Learning Approaches.Journal of clinical medicine · 2025Article
- The importance of systemic inflammatory response measurements as pretransplant risk factors for outcome after allogeneic haematopoietic cell transplantation.British journal of haematology · 2025Article
- Clinical scoring systems, molecular subtypes and baseline [Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- Comparison of Cox regression and generalized Cox regression models to machine learning in predicting survival of children with diffuse large B-cell lymphoma.Translational cancer research · 2024Article
- A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Diffuse Large B Cell Lymphoma.Journal of inflammation research · 2024Article
- Biomarkers for prediction of CAR T therapy outcomes: current and future perspectives.Frontiers in immunology · 2024Review
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: We aimed to create a novel prognostic score, the inflammation-based prognosis score (IBPS). In addition, we attempted to establish and validate a nomogram to predict the overall survival (OS) of patients with DLBCL. Patients and Methods: We retrospectively investigated the data of 213 patients with DLBCL diagnosed and treated in the Affiliated Hospital of Jiangnan University and used these data to develop nomograms. At the same time, 89 patients diagnosed and treated in Wuxi People's Hospital Affiliated with Nanjing Medical University from January 2015 to June 2021 were collected as an external validation cohort. We developed IBPS through the least absolute shrinkage and selection operator (LASSO) Cox regression. The univariate and multivariate Cox regression method was used to develop the nomogram. We used the concordance index (C-index), calibration chart, time-dependent receiver operating characteristic (ROC) analysis, decision curve analysis (DCA), and the Kaplan-Meier curve were used to assess the nomogram. Results: The systemic immune inflammation index (SII), prognostic nutrition index (PNI), and modified Glasgow prognostic score (mGPS) were used to construct IBPS. The Eastern Cooperative Oncology Group performance status (ECOG PS), IBPS, response to treatment, and whether accept surgery were used to construct the nomogram to predict the OS of DLBCL patients. The C-index in the training and validation cohorts were 0.844 and 0.828, respectively. According to the time-dependent ROC curve and DCA, the nomogram has good predictive accuracy and clinical net benefit. The Kaplan-Meier curve showed that according to the nomogram score, patients in the training and validation cohorts could be classified into three risk groups. Conclusion: In patients with DLBCL, baseline IBPS was a reliable predictor of OS. The survival probability of DLBCL patients can be precisely predicted using the prognosis nomogram based on IBPS.
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