ArticleJournal of inflammation research2025
A Nomogram for Predicting Overall Survival in Primary Central Nervous System Lymphoma: A Retrospective Study.
Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A Prognostic Model Incorporating Age and Systemic Inflammation Response Index for Primary CNS Lymphoma.Current oncology (Toronto, Ont.) · 2026Article
- Unraveling the immune microenvironment in primary CNS lymphoma.Biomarker research · 2026Review
- A nomogram for predicting the diagnosis of central malignant tumors based on preoperative clinical characteristics and laboratory indicators: a diagnostic study.International journal of surgery (London, England) · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Current prognostic scoring systems for newly diagnosed primary central nervous system lymphoma (PCNSL), such as IELSG prognostic score and MSKCC prognostic score, are widely used but have limitations in clinical practice. This study aimed to develop a novel prognostic model based on real clinical data and compare it with existing systems. Patients and Methods: A total of 288 patients newly diagnosed with PCNSL were recruited. Patients were randomly allocated to the development and validation cohorts. The least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analysis were used to identify the risk factors for overall survival (OS) and construct a nomogram. Additionally, Kaplan-Meier survival curves were plotted to show the stratification ability of the risk groups. Results: Eastern Cooperative Oncology Group performance status (ECOG-PS), albumin, and two inflammatory biomarkers D-Dimer, and neutrophil-to-lymphocyte ratio (NLR)-were independent predictors of inferior OS. The prognostic model demonstrated concordance Index (C-index) of 0.731 and 0.679 in the development and validation cohorts, respectively. In terms of the time dependent area under the curve (AUC) values for OS, the development cohort exhibited values of 0.765, 0.762, and 0.812 for 1-year, 3-year, and 5-year OS, respectively. The corresponding AUC values in the validation cohort were 0.711, 0.731, and 0.840, respectively. The calibration curves showed excellent concordance. The novel prognostic model also provided superior risk stratification for patients with PCNSL compared with existing scoring systems. Conclusion: This study presents a novel prognostic model for predicting the OS of patients with newly diagnosed PCNSL. The model accurately and effectively stratifies the prognosis of patients with PCNSL and offers valuable clinical guidance for decision making.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.