Evidence map›Paper›PMID 37554221›Full record

ArticleNeuro-oncology advances

Change in volumetric tumor growth rate after cytotoxic therapy is predictive of overall survival in recurrent glioblastoma.

Sonoko Oshima, Akifumi Hagiwara, Catalina Raymond, Chencai Wang, Nicholas S Cho, Jianwen Lu, Blaine S C Eldred, Phioanh L Nghiemphu, Albert Lai, Donatello Telesca and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

13 authors.

Sonoko OshimaUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-1453-3807
Akifumi HagiwaraUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0001-5277-3249
Catalina RaymondUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-2757-439X
Chencai WangUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, California, USA.
Nicholas S ChoUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-8686-0575
Jianwen LuUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-0516-3135
Blaine S C EldredUCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, California, USA.
Phioanh L NghiemphuUCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0003-4064-6079
Albert LaiUCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-7265-2986
Donatello TelescaDepartment of Biostatistics, University of California, Los Angeles, California, USA.
Noriko SalamonDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-3520-9467
Timothy F CloughesyUCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-8656-7483
Benjamin M EllingsonUCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-2764-6640

Funding

UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI David A. Nathanson · 2017 to 2026
$25.2M
Role of decorin and diffusion MRI in anti-VEGF efficacy for recurrent glioblastomaR01CA270027 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TIMOTHY CLOUGHESY, Benjamin M. Ellingson · 2022 to 2026
$3.0M
Quantitative molecular MR-PET imaging of glycolysis in glioblastomaR01CA279984 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Benjamin M. Ellingson, David A. Nathanson · 2023 to 2026
$2.4M
NCI NIH HHS P50 CA211015NCI NIH HHS R01 CA270027NCI NIH HHS R01 CA279984
6 · The paper itself

Abstract

Background: Alterations in tumor growth rate (TGR) in recurrent glioblastoma (rGBM) after treatment may be useful for identifying therapeutic activity. The aim of this study was to assess the impact of volumetric TGR alterations on overall survival (OS) in rGBM treated with chemotherapy with or without radiation therapy (RT). Methods: Sixty-one rGBM patients treated with chemotherapy with or without concomitant radiation therapy (RT) at 1st or 2nd recurrence were retrospectively examined. Pre- and post-treatment contrast enhancing volumes were computed. Patients were considered "responders" if they reached progression-free survival at 6 months (PFS6) and showed a decrease in TGR after treatment and "non-responders" if they didn't reach PFS6 or if TGR increased. Results: Stratification by PFS6 and based on TGR resulted in significant differences in OS both for all patients and for patients without RT ( Conclusion: A decrease in TGR in patients with PFS6, along with smaller baseline tumor volume, were associated with a significantly longer OS in rGBM treated with chemotherapy with or without radiation. Importantly, all patients that exhibited PFS6 also showed a measurable decrease in TGR.

Indexed as

MRIrecurrent glioblastomasurvivaltumor growth rate

Identifiers

PMID37554221
PMCPMC10406419

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.