ReviewCancer drug resistance (Alhambra, Calif.)2019
Use of MRI, metabolomic, and genomic biomarkers to identify mechanisms of chemoresistance in glioma.
Review in Cancer drug resistance (Alhambra, Calif.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Untangling the web of glioblastoma treatment resistance using a multi-omic and multidisciplinary approach.The American journal of the medical sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gliomas are the most common form of central nervous system tumor. The most prevalent form, glioblastoma multiforme, is also the most deadly with mean survival times that are less than 15 months. Therapies are severely limited by the ability of these tumors to develop resistance to both radiation and chemotherapy. Thus, new tools are needed to identify and monitor chemoresistance before and after the initiation of therapy and to maximize the initial treatment plan by identifying patterns of chemoresistance prior to the start of therapy. Here we show how magnetic resonance imaging, particularly sodium imaging, metabolomics, and genomics have all emerged as potential approaches toward the identification of biomarkers of chemoresistance. This work also illustrates how use of these tools together represents a particularly promising approach to understanding mechanisms of chemoresistance and the development individualized treatment strategies for patients.
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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.