Evidence map›Paper›PMID 25313236›Full record

ArticleNeuro-oncology2014

Impact of imaging measurements on response assessment in glioblastoma clinical trials.

David A Reardon, Karla V Ballman, Jan C Buckner, Susan M Chang, Benjamin M Ellingson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuro-oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Interval brain imaging for adults with cerebral glioma.The Cochrane database of systematic reviews · 2019
    Pooled it
  2. Image-based Re-evaluation of the JCOG0911 Study Focusing on Tumor Volume and Survival, Disease Progression Diagnosis, and Radiomic Prognostication for Newly Diagnosed Glioblastoma.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Treatment-related changes in glioblastoma: a review on the controversies in response assessment criteria and the concepts of true progression, pseudoprogression, pseudoresponse and radionecrosis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2018
    Review
  14. Pseudoprogression of brain tumors.Journal of magnetic resonance imaging : JMRI · 2018
    Article
  15. Article
  16. Article
  17. Response Assessment in Neuro-Oncology Clinical Trials.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2017
    Review
  18. Modified Criteria for Radiographic Response Assessment in Glioblastoma Clinical Trials.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2017
    Review
  19. Article
  20. 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

5 authors.

David A ReardonCenter for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts (D.A.R.); Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (K.V.B.); Department of Oncology, Mayo Clinic, Rochester, Minnesota (J.C.B.); Department of Neurological Surgery, University of California - San Francisco, San Francisco, California (S.M.C.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); Department of Biomedical Physics, David Geffen School of Medicine at UCLA, Los Angeles, CA (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.).
Karla V BallmanCenter for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts (D.A.R.); Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (K.V.B.); Department of Oncology, Mayo Clinic, Rochester, Minnesota (J.C.B.); Department of Neurological Surgery, University of California - San Francisco, San Francisco, California (S.M.C.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); Department of Biomedical Physics, David Geffen School of Medicine at UCLA, Los Angeles, CA (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.).
Jan C BucknerCenter for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts (D.A.R.); Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (K.V.B.); Department of Oncology, Mayo Clinic, Rochester, Minnesota (J.C.B.); Department of Neurological Surgery, University of California - San Francisco, San Francisco, California (S.M.C.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); Department of Biomedical Physics, David Geffen School of Medicine at UCLA, Los Angeles, CA (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.).
Susan M ChangCenter for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts (D.A.R.); Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (K.V.B.); Department of Oncology, Mayo Clinic, Rochester, Minnesota (J.C.B.); Department of Neurological Surgery, University of California - San Francisco, San Francisco, California (S.M.C.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); Department of Biomedical Physics, David Geffen School of Medicine at UCLA, Los Angeles, CA (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.).
Benjamin M EllingsonCenter for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts (D.A.R.); Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (K.V.B.); Department of Oncology, Mayo Clinic, Rochester, Minnesota (J.C.B.); Department of Neurological Surgery, University of California - San Francisco, San Francisco, California (S.M.C.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); Department of Biomedical Physics, David Geffen School of Medicine at UCLA, Los Angeles, CA (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at UCLA, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at UCLA, Los Angeles, California (B.M.E.).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We provide historical and scientific guidance on imaging response assessment for incorporation into clinical trials to stimulate effective and expedited drug development for recurrent glioblastoma by addressing 3 fundamental questions: (i) What is the current validation status of imaging response assessment, and when are we confident assessing response using today's technology? (ii) What imaging technology and/or response assessment paradigms can be validated and implemented soon, and how will these technologies provide benefit? (iii) Which imaging technologies need extensive testing, and how can they be prospectively validated? Assessment of T1 +/- contrast, T2/FLAIR, diffusion, and perfusion-imaging sequences are routine and provide important insight into underlying tumor activity. Nonetheless, utility of these data within and across patients, as well as across institutions, are limited by challenges in quantifying measurements accurately and lack of consistent and standardized image acquisition parameters. Currently, there exists a critical need to generate guidelines optimizing and standardizing MRI sequences for neuro-oncology patients. Additionally, more accurate differentiation of confounding factors (pseudoprogression or pseudoresponse) may be valuable. Although promising, diffusion MRI, perfusion MRI, MR spectroscopy, and amino acid PET require extensive standardization and validation. Finally, additional techniques to enhance response assessment, such as digital T1 subtraction maps, warrant further investigation.

Indexed as

Response Evaluation Criteria in Solid TumorsBrain NeoplasmsClinical Trials as TopicGlioblastomaHumansMagnetic Resonance ImagingMagnetic Resonance SpectroscopyPositron-Emission Tomographyclinical trialsglioblastomaimagingMRIresponse assessment

Identifiers

PMID25313236
PMCPMC4195531

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.