ArticleEuropean journal of nuclear medicine and molecular imaging2017
Response assessment of bevacizumab therapy in GBM with integrated 11C-MET-PET/MRI: a feasibility study.
Article in European journal of nuclear medicine and molecular imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 18 citations in OpenAlex.
- Amino acid PET vs. RANO MRI for prediction of overall survival in patients with recurrent high grade glioma under bevacizumab therapy.European journal of nuclear medicine and molecular imaging · 2024Article
- Emerging Therapies for Glioblastoma.Cancers · 2024Review
- PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group.The Lancet. Oncology · 2024Review
- Advanced Imaging Techniques for Differentiating Pseudoprogression and Tumor Recurrence After Immunotherapy for Glioblastoma.Frontiers in immunology · 2021Review
- The Emerging Role of Amino Acid PET in Neuro-Oncology.Bioengineering (Basel, Switzerland) · 2018Review
- A systematic review of the utility of amino acid PET in assessing treatment response to bevacizumab in recurrent high-grade glioma.Neuro-oncology advancesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe objective of this study was to evaluate the potential of integrated 11C-MET PET/MR for response assessment of relapsed glioblastoma (GBM) receiving bevacizumab treatment.
methodsEleven consecutive patients with relapsed GBM were enrolled for an integrated 11C-MET PET/MRI at baseline and at follow-up. Treatment response for MRI was evaluated according to Response Assessment in Neuro-oncology (RANO) criteria and integrated 11C-MET PET was assessed by the T/N ratio.
resultsMRI showed no patient with complete response (CR), six of 11 patients with PR, four of 11 patients with SD, and one of 11 patients with progressive disease (PD). PET revealed metabolic response in five of the six patients with partial response (PR) and in two of the four patients with stable disease (SD), whereas metabolic non-response was detected in one of the six patients with PR, in two of the four patients with SD, and in the one patient with PD. Morphological imaging was predictive for PFS and OS when response was defined as CR, PR, SD, and non-response as PD. Metabolic imaging was predictive when using T/N ratio reduction of >25 as discriminator. Based on the morphologic and metabolic findings of this study a proposal for applying integrated PET/MRI for treatment response in relapsed GBM was developed, which was significantly predictive for PFS and OS (P = 0.010 respectively 0,029, log).
conclusionsThis study demonstrates the potential of integrated 11C-MET-PET/MRI for response assessment of GBM and the utility of combined assessment of morphologic and metabolic information with the proposal for assessing relapsed GBM.
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.