Evidence map›Paper›PMID 28204639›Full record

Trial reportNeuro-oncology2017

Comparison of 2D (RANO) and volumetric methods for assessment of recurrent glioblastoma treated with bevacizumab-a report from the BELOB trial.

Renske Gahrmann, Martin van den Bent, Bronno van der Holt, René Michel Vernhout, Walter Taal, Maaike Vos, Jan Cees de Groot, Laurens Victor Beerepoot, Jan Buter, Zwenneke Hendrieke Flach and 3 more

Abstract readClinical Trial, Phase IIComparative StudyMulticenter Study
In one paragraph

Trial report in Neuro-oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
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

36 citing papers in PubMed.

  1. Trial
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  10. Updated Response Assessment in Neuro-Oncology (RANO) for Gliomas.Current neurology and neuroscience reports · 2024
    Review
  11. RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023
    Article
  12. Article
  13. Review
  14. Review
  15. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Renske GahrmannDepartment of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
Martin van den BentBrain Tumor Center at Erasmus MC Cancer Institute Erasmus University Medical Center, Rotterdam, The Netherlands.
Bronno van der HoltClinical Trial Center, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands.
René Michel VernhoutClinical Trial Center, Erasmus MC Cancer Institute, University Medical Center, Rotterdam, The Netherlands.
Walter TaalBrain Tumor Center at Erasmus MC Cancer Institute Erasmus University Medical Center, Rotterdam, The Netherlands.
Maaike VosDepartment of Neurology, Medical Center Haaglanden, The Hague, The Netherlands.
Jan Cees de GrootDepartment of Radiology, University Medical Center Groningen, Groningen, The Netherlands.
Laurens Victor BeerepootDepartment of Internal Medicine, Elisabeth Tweesteden Ziekenhuis, Tilburg, The Netherlands.
Jan ButerDepartment of Oncology, VU University Medical Center, Amsterdam, The Netherlands.
Zwenneke Hendrieke FlachDepartment of Radiology, Isala Clinics, Zwolle, The Netherlands.
Monique HanseDepartment of Neurology, Catharina Hospital, Eindhoven, The Netherlands.
Bas JasperseDepartment of Radiology, Antoni van Leeuwenhoek ziekenhuis, Amsterdam, The Netherlands.
Marion SmitsDepartment of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The current method for assessing progressive disease (PD) in glioblastoma is according to the Response Assessment in Neuro-Oncology (RANO) criteria. Bevacizumab-treated patients may show pseudo-response on postcontrast T1-weighted (T1w) MRI, and a more infiltrative non-enhancing growth pattern on T2w/fluid attenuated inversion recovery (FLAIR) images. We investigated whether the RANO criteria remain the method of choice for assessing bevacizumab-treated recurrent glioblastoma when compared with various volumetric methods. Methods: Patients with assessable MRI data from the BELOB trial (n = 148) were included. Patients were treated with bevacizumab, lomustine, or both. At first and second radiological follow-up (6 and 12 wk), PD was determined using the 2D RANO criteria and various volumetric methods based on enhancing tumor only and enhancing plus non-enhancing tumor. Differences in overall survival (OS) between PD and non-PD patients were assessed with the log-rank test and a Cox model. Hazard ratios (HRs) and their 95% CIs were determined. Results: For all patients together, all methods (except subtraction of non-enhancing from enhancing volume at first follow-up) showed significant differences in OS between PD and non-PD patients (P < .001). The largest risk increase for death in case of PD at both first and second follow-up was found with the RANO criteria: HR = 2.81 (95% CI, 1.92-4.10) and HR = 2.80 (95% CI, 1.75-4.49), respectively. In the bevacizumab-treated patients, all methods assessed showed significant differences in OS between PD and non-PD patients. There were no significant differences between methods. Conclusions: In the first 12 weeks, volumetric methods did not provide significant improvement over the RANO criteria as a posttreatment prognostic marker.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBevacizumabBrain NeoplasmsContrast MediaGlioblastomaHumansLomustineMagnetic Resonance ImagingNeoplasm Recurrence, LocalSurvival RateTreatment OutcomeBevacizumabContrast MediaLomustinebevacizumabRANOrecurrent glioblastomavolumetry

Identifiers

PMID28204639
PMCPMC5464446

What OpenQuestion holds

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Registered trials

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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.