ArticleInternational journal of particle therapy2018
Radiogenomic Predictors of Adverse Effects following Charged Particle Therapy.
Article in International journal of particle therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Potential Single Nucleotide Polymorphisms markers for radiation dermatitis in head and neck cancer patients: a meta-analysis.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2024Pooled it
- Carbon Ion Radiobiology.Cancers · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
Abstract
Radiogenomics is the study of genomic factors that are associated with response to radiation therapy. In recent years, progress has been made toward identifying genetic risk factors linked with late radiation-induced adverse effects. These advances have been underpinned by the establishment of an international Radiogenomics Consortium with collaborative studies that expand cohort sizes to increase statistical power and efforts to improve methodologic approaches for radiogenomic research. Published studies have predominantly reported the results of research involving patients treated with photons using external beam radiation therapy. These studies demonstrate our ability to pool international cohorts to identify common single nucleotide polymorphisms associated with risk for developing normal tissue toxicities. Progress has also been achieved toward the discovery of genetic variants associated with radiation therapy-related subsequent malignancies. With the increasing use of charged particle therapy (CPT), there is a need to establish cohorts for patients treated with these advanced technology forms of radiation therapy and to create biorepositories with linked clinical data. While some genetic variants are likely to impact toxicity and second malignancy risks for both photons and charged particles, it is plausible that others may be specific to the radiation modality due to differences in their biological effects, including the complexity of DNA damage produced. In recognition that the formation of patient cohorts treated with CPT for radiogenomic studies is a high priority, efforts are underway to establish collaborations involving institutions treating cancer patients with protons and/or carbon ions as well as consortia, including the Proton Collaborative Group, the Particle Therapy Cooperative Group, and the Pediatric Proton Consortium Registry. These important radiogenomic CPT initiatives need to be expanded internationally to build on experience gained from the Radiogenomics Consortium and epidemiologists investigating normal tissue toxicities and second cancer risk.
Indexed as
Identifiers
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.