ArticleJournal of neuro-oncology2016
Prognostic factors in recurrent glioblastoma patients treated with bevacizumab.
Article in Journal of neuro-oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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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.
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Who cites it
11 citing papers in PubMed, 26 citations in OpenAlex.
- Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab.Neuro-oncology · 2017Trial
- A prognostic model for overall survival in recurrent glioma patients treated with bevacizumab-containing therapy.Discover oncology · 2024Article
- Article
- Long-term survival in patients with recurrent glioblastoma treated with bevacizumab: a multicentric retrospective study.Journal of neuro-oncology · 2019Article
- Regorafenib in advanced high-grade glioma: a retrospective bicentric analysis.Neuro-oncology · 2019Article
- EGFR amplification and classical subtype are associated with a poor response to bevacizumab in recurrent glioblastoma.Journal of neuro-oncology · 2019Article
- The Clinical Significance of OFrontiers in neurology · 2018Article
- Bevacizumab for Patients with Recurrent Multifocal Glioblastomas.International journal of molecular sciences · 2017Article
- Bevacizumab as a last-line treatment for glioblastoma following failure of radiotherapy, temozolomide and lomustine.Oncology letters · 2017Article
- The earlier the better? Bevacizumab in the treatment of recurrent MGMT-non-methylated glioblastoma.Journal of cancer research and clinical oncology · 2016Article
- Can Platelet-to-Lymphocyte Ratio (PLR) and Neutrophil-to-Lymphocyte Ratio (NLR) Help Predict Outcomes of Patients With Recurrent Glioblastoma?In vivo (Athens, Greece)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The value of bevacizumab (BEV) in recurrent glioblastoma is unclear. Imaging parameters and progression-free survival (PFS) are problematic endpoints. Few data exist on clinical factors influencing overall survival (OS) in unselected patients with recurrent glioblastoma exposed to BEV. We retrospectively analyzed 174 patients with recurrent glioblastoma treated with BEV at two German brain tumor centers. We evaluated general patient characteristics, MGMT status, pretreatment, concomitant oncologic treatment and overall survival. Karnofsky performance score, number of prior chemotherapies, number of prior recurrences and combined treatment with irinotecan (IRI) were significantly associated with OS in univariate analysis. We did not find differences in OS related to sex, age, histology, MGMT status, prior surgical treatment or number of prior radiotherapies. Combined treatment with IRI and higher KPS both remained significantly associated with prolonged survival in multivariate analysis, but patients receiving IRI co-treatment had less advanced disease. Grouping into clinically relevant categories revealed an OS of 16.9 months from start of BEV in patients with first recurrence and KPS ≥ 80 % (n = 25). In contrast, in patients with second recurrence and KPS < 80 %, OS was 3.6 months (n = 27). Our observational data support an early use of BEV in patients with good performance status. The benefit of co-treatment with IRI in our cohort seems to be the result of biased patient recruitment.
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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.