ArticleCancer medicine2024
Exploring the Potential of Enhanced Prognostic Performance of NCCN-IPI in Diffuse Large B-Cell Lymphoma by Integrating Tumor Microenvironment Markers: Stromal FOXC1 and Tumor pERK1/2 Expression.
Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence for Risk Stratification in Diffuse Large B-Cell Lymphoma: A Systematic Review of Classification Models and Predictive Performances.Medical sciences (Basel, Switzerland) · 2025Pooled it
- Machine learning-driven investigation on liquid-liquid phase separation-related prognostic signature in diffuse large B-cell lymphoma.British journal of haematology · 2026Article
- Machine learning enhances risk stratification and treatment failure prediction in diffuse large B-cell lymphoma.HemaSphere · 2026Article
- Mortality Prediction in Diffuse Large B-Cell Lymphoma Using Supervised Machine Learning Models-A Retrospective Study.Journal of clinical medicine · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundFOXC1 and ERK1-2 are proteins implicated in aggressive biological behavior of various malignancies including lymphomas. MATERIAL AND
methodsWe investigate the additive prognostic value of stromal FOXC1 expression and tumor phosphorylated ERK1-2 (pERK1-2) expression to the established National Comprehensive Cancer Network International Prognostic Index (NCCN-IPI), in 92 diffuse large B-cell lymphoma (DLBCL) cases. Multidimensional analysis using statistics and machine learning (ML) models assessed prognostic value of established clinicopathologic variables with stromal FOXC1 and tumor pERK1-2 expressions.
resultsBoth high FOXC1 stroma group and high pERK1-2 tumor group were significantly associated with shorter progression-free survival (PFS) and overall survival (OS) compared with low group (p = 0.015, 0.034 and p = 0.025, 0.025 each respectively). In multivariable analysis, high FOXC1 stromal expression was an independent prognostic factor of OS (p = 0.037). The addition of stromal FOXC1 and tumor pERK1-2 to the NCCN-IPI score significantly improved prediction of time to death compared with NCCN-IPI score alone (Harrell's C-index = 0.801 vs. 0.764; p = 0.030). ML models reconfirmed the addition of stromal FOXC1 expression and tumor pERK1-2 to NCCN-IPI score had the highest C-index (0.952) among combinations. Stromal FOXC1 and tumor pERK1-2 were determinants of DLBCL prognosis, whose addition significantly improved prognostic performance of the NCCN-IPI.
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