ArticleNeurosurgical review2017
Predicting surgical outcome in patients with glioblastoma multiforme using pre-operative magnetic resonance imaging: development and preliminary validation of a grading system.
Article in Neurosurgical review, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 29 citations in OpenAlex.
- Impact of holiday periods on glioblastoma surgery: a Dutch nationwide population-based cohort study.Scientific reports · 2026Article
- Development of the glioma imaging complexity score (GICS): a volumetric MRI-based stratification framework.Frontiers in surgery · 2026Article
- Enhancing decision-making in glioblastoma surgery through an explainable human-AI collaboration: an international multicenter model development and external validation study.NPJ precision oncology · 2025Article
- Towards a New Dawn for Neuro-Oncology: Nanomedicine at the Service of Drug Delivery for Primary and Secondary Brain Tumours.Brain sciences · 2025Review
- Choice of intraoperative ultrasound adjuncts for brain tumor surgery.BMC medical informatics and decision making · 2022Article
- Preoperative nonmedical predictors of functional impairment after brain tumor surgery.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022Article
- Review
- Second surgery for progressive glioblastoma: a multi-centre questionnaire and cohort-based review of clinical decision-making and patient outcomes in current practice.Journal of neuro-oncology · 2021Article
- Outcome prediction in brain tumor surgery: a literature review on the influence of nonmedical factors.Neurosurgical review · 2021Review
- Neurosurgery and artificial intelligence.AIMS neuroscience · 2021Review
- Association of Isocitrate Dehydrogenase (IDH) Status With Edema to Tumor Ratio and Its Correlation With Immune Infiltration in Glioblastoma.Frontiers in immunology · 2021Article
- The IDEAL framework in neurosurgery: a bibliometric analysis.Acta neurochirurgica · 2020Review
- Evaluating angioarchitectural characteristics of glial and metastatic brain tumors with conventional magnetic resonance imaging.Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia · 2020Article
- Improved Prediction of Surgical Resectability in Patients with Glioblastoma using an Artificial Neural Network.Scientific reports · 2020Article
- Real-time presurgical resting-state fMRI in patients with brain tumors: Quality control and comparison with task-fMRI and intraoperative mapping.Human brain mapping · 2020Article
- Is a pretreatment radiological staging system feasible for suggesting the optimal extent of resection and predicting prognosis in glioblastoma? An observational study.Journal of neuro-oncology · 2018Observational
- Predicting complexity of tumor removal and postoperative outcome in patients with high-grade gliomas.Neurosurgical review · 2018Article
- Improved prediction of postoperative pediatric cerebellar mutism syndrome using an artificial neural network.Neuro-oncology advancesArticle
Corrections and comments
- Commented on by
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The lack of a simple, objective and reproducible system to describe glioblastoma multiforme (GBM) represents a major limitation in comparative effectiveness research. The objectives of this study were therefore to develop such a grading system and to validate it on patients who underwent surgical resection. A systematic review of the literature was performed to identify features on pre-operative magnetic resonance imaging (MRI) that predict the surgical outcome of patients with GBM. In all, the five most important features of GBM on pre-operative MRI were as follows: periventricular or deep location, corpus callosum or bilateral location, eloquent location, size and associated oedema. These were then used to develop a grading system. To validate this grading system, a retrospective cohort study of all adult patients with supratentorial GBM who underwent surgical resection between the 1 January 2014 and the 31 June 2015 was performed. There was a substantial agreement between the two neurosurgeons grading GBM (Cohen's κ was 0.625; standard error 0.066). High-complexity lesions were significantly less likely to result in complete resection of contrast-enhancing tumour than low-complexity lesions (50.0 versus 3.4%; p = 0.0007). The proposed grading system may allow for the standardised communication of anatomical features of GBM identified on pre-operative MRI.
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.