Evidence map›Paper›PMID 32060714›Full record

ArticleEuropean radiology2020

MR image phenotypes may add prognostic value to clinical features in IDH wild-type lower-grade gliomas.

Chae Jung Park, Kyunghwa Han, Haesol Shin, Sung Soo Ahn, Yoon Seong Choi, Yae Won Park, Jong Hee Chang, Se Hoon Kim, Rajan Jain, Seung-Koo Lee

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In one paragraph

Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
0.8field-weighted citation impact, top 29% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Chae Jung ParkDepartment of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Kyunghwa HanDepartment of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Haesol ShinDepartment of Biostatistics and Computing, College of Medicine, Yonsei University, Seoul, South Korea.
Sung Soo AhnDepartment of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea. SUNGSOO@yuhs.ac.ORCID http://orcid.org/0000-0002-0503-5558
Yoon Seong ChoiDepartment of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Yae Won ParkDepartment of Radiology, College of Medicine, Ewha Womans University, Seoul, South Korea.
Jong Hee ChangDepartment of Neurosurgery, College of Medicine, Yonsei University, Seoul, South Korea.
Se Hoon KimDepartment of Pathology, College of Medicine, Yonsei University, Seoul, South Korea.
Rajan JainDepartment of Radiology, Langone Medical Center, School of Medicine, New York University, New York, NY, USA.
Seung-Koo LeeDepartment of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
Yonsei University · KREwha Womans University · KRNYU Langone Health · US

Funding

Ministry of Science, Information and Communication Technologies & Future Planning 2017R1D1A1B03030440
6 · The paper itself

Abstract

purposeTo identify significant prognostic magnetic resonance imaging (MRI) features and their prognostic value when added to clinical features in patients with isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas. MATERIALS AND

methodsPreoperative MR images of 158 patients (discovery set = 112, external validation set = 46) with IDHwt lower-grade gliomas (WHO grade II or III) were retrospectively analyzed using the Visually Accessible Rembrandt Images feature set. Radiologic risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator and elastic net. Multivariable Cox regression analysis, including age, Karnofsky Performance score, extent of resection, WHO grade, and RRS, was performed. The added prognostic value of RRS was calculated by comparing the integrated area under the receiver operating characteristic curve (iAUC) between models with and without RRS.

resultsThe presence of cysts, pial invasion, and cortical involvement were favorable prognostic factors, while ependymal extension, multifocal or multicentric distribution, nonlobar location, proportion of necrosis > 33%, satellites, and eloquent cortex involvement were significantly associated with worse prognosis. RRS independently predicted survival and significantly enhanced model performance for survival prediction when integrated to clinical features (iAUC increased to 0.773-0.777 from 0.737), which was successfully validated on the validation set (iAUC increased to 0.805-0.830 from 0.735).

conclusionMRI features associated with prognosis in patients with IDHwt lower-grade gliomas were identified. RRSs derived from MRI features independently predicted survival and significantly improved performance of survival prediction models when integrated into clinical features. KEY POINTS: • Comprehensive analysis of MRI features conveys prognostic information in patients with isocitrate dehydrogenase wild-type lower-grade gliomas. • Presence of cysts, pial invasion, and cortical involvement of the tumor were favorable prognostic factors. • Radiological phenotypes derived from MRI independently predict survival and have the potential to improve survival prediction when added to clinical features.

Indexed as

AlgorithmsBrain NeoplasmsFemaleGliomaHumansMagnetic Resonance ImagingMaleMiddle AgedPhenotypePrognosisRetrospective StudiesROC CurveGliomaIsocitrate dehydrogenaseMagnetic resonance imagingPrognosisSurvival

Identifiers

PMID32060714
OpenAlexW3006328397

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.