ArticleEuropean radiology2021
Development of MR-based preoperative nomograms predicting DNA copy number subtype in lower grade gliomas with prognostic implication.
Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed.
- T2-FLAIR Mismatch Sign Predicts DNA Methylation Subclass and CDKN2A/B Status in IDH-Mutant Astrocytomas.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Article
- Novel insight into histological and molecular astrocytoma, IDH-mutant, Grade 4 by the updated WHO classification of central nervous system tumors.Cancer medicine · 2023Article
- Development of a nomogram based on radiomics and semantic features for predicting chromosome 7 gain/chromosome 10 loss in IDH wild-type histologically low-grade gliomas.Frontiers in oncology · 2023Article
- Development and validation of an MRI-based nomogram for the preoperative prediction of tumor mutational burden in lower-grade gliomas.Quantitative imaging in medicine and surgery · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWe aimed to determine the value of MR-based preoperative nomograms in predicting DNA copy number (CN) subtype in lower grade glioma (LGG) patients.
methodsThe overall survival (OS) data were analyzed. MRI data of 170 subjects were retrospectively analyzed. The correlation was explored by univariate and multivariate regression analysis.
resultsCN2 subtype was associated with shortest median OS (CN2 subtype vs. others: 46.8 vs. 221.7 months, p < 0.05). The time-dependent receiver operating characteristic for the CN2 subtype was 0.80 (95% CI: 0.74-0.85) for survival at 1 year, 0.80 (95% CI: 0.75-0.85) for survival at 2 years, and 0.77 (95% CI: 0.73-0.83) for survival at 3 years. On multivariate analysis, hemorrhage (OR: 0.118; p < 0.001; 95% CI: 0.037-0.376), poorly defined margin (OR: 4.592; p < 0.001; 95% CI: 1.965-10.730), extranodular growth (OR: 0.247; p = 0.006; 95% CI: 0.091-0.671), and volume ≥ 60 cm
conclusionsThe shortest OS was observed in patients with CN2 subtype. This preliminary radiogenomics analysis revealed that the MR-based preoperative nomograms provide individualized prediction of DNA copy number subtype in LGG patients. KEY POINTS: • This preliminary radiogenomics analysis of LGG revealed that the MR-based preoperative nomograms provide individualized prediction of DNA copy number subtype in LGG patients. • The AUC for the ROC curve was 0.781 for CN1 subtype, 0.854 for CN2 subtype, and 0.808 for CN3 subtype. Decision curve analysis supported that all nomograms were clinically useful. • The sensitivity was 0.779 (CN1), 0.731 (CN2), and 0.851 (CN3), respectively. The specificity was 0.664 (CN1), 0.872 (CN2), and 0.625 (CN3), respectively. And the accuracy was 0.717 (CN1), 0.849 (CN2), and 0.692 (CN3), respectively.
Indexed as
Identifiers
33025175What 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.