ArticleBMC medical imaging2026
Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundIn the R-CHOP era, the IPI score has reduced efficacy in identifying high-risk diffuse large B-cell lymphoma (DLBCL) patients. Precise prognostic biomarkers and scoring systems are urgently needed to achieve refined stratification of this high-risk population. This study aimed to clarify the combined prognostic significance of
methodsThis study included 210 real-world patients with newly diagnosed DLBCL treated with R-CHOP. Radiomic parameters including maximum standardized uptake value (SUVmax), total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), and maximum lesion diameter (Dmax) were extracted from
resultsMultivariate analysis identified MTV, Dmax and DEL status as independent predictors of progression-free survival (PFS) and overall survival (OS), leading to the development of the MDE prognostic model. Five-fold cross-validation confirmed significant PFS/OS risk stratification across all training and validation cohorts (all P < 0.05). MDE was a significant independent PFS predictor (P < 0.0001), outperforming the IPI (P = 0.205). The MDE model showed superior predictive performance over IPI: for PFS, mean AIC (536.564 vs. 575.546) and C-index (0.778 vs. 0.677); for OS, mean AIC (424.227 vs. 445.86) and C-index (0.775 vs. 0.724). Its AUC (0.797) was significantly higher than IPI (0.700, all P < 0.05) per DeLong's test, bootstrap method and Venkatraman's permutation test. Compared with IPI high-risk patients (5-year PFS: 34.6%, OS: 32.6%), MDE identified a higher-risk subgroup (5-year PFS: 22.4%, OS: 29.7%) and improved discriminatory capacity across IPI subgroups (all P < 0.05).
conclusionsThe MDE scoring system integrates baseline
trial registrationThe research protocol of this study was approved by the Ethics Committee of Jiangsu Cancer Hospital (Approval KY-2025-095, approval date: 16 July 2025). CLINICAL TRIAL NUMBER: Not applicable.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.