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Cited by 771

The DOI matches its Crossref record; 117 of the 117 references it cites were found in a registry or an index.

Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype

Open access
Barnett, Gillian C., West, Catherine M. L., Dunning, Alison M., Elliott, Rebecca M., Coles, Charlotte E., Pharoah, Paul D. P., Burnet, Neil G.·2009·Nature Reviews Cancer

Abstract

A key challenge in radiotherapy is to maximize radiation doses to cancer cells while minimizing damage to surrounding healthy tissue. As severe toxicity in a minority of patients limits the doses that can be safely given to the majority, there is interest in developing a test to measure an individual's radiosensitivity before treatment. Variation in sensitivity to radiation is an inherited genetic trait and recent progress in genotyping raises the possibility of genome-wide studies to characterize genetic profiles that predict patient response to radiotherapy.

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Crossref · 10.1038/nrc2587

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Metadata

Authors
Barnett, G. C., West, C. M. L., Dunning, A. M., Elliott, R. M., Coles, C. E., Pharoah, P. D. P., & Burnet, N. G.
Venue
Nature Reviews Cancer
Published
2009-01-16
Volume
9
Issue
2
Pages
134-142
ISSN
  • 1474-175X (ISSN-L)
  • 1474-1768
OpenAlex
W2016899305
Cited by
771
References
117
FWCI
3.88
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype. https://app.cochat.ai/papers/10.1038/nrc2587
The paper
Barnett, G. C., West, C. M. L., Dunning, A. M., Elliott, R. M., Coles, C. E., Pharoah, P. D. P., & Burnet, N. G. (2009). Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype. Nature Reviews Cancer. https://doi.org/10.1038/nrc2587

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.