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• W1816156720 abstract "Purpose This study utilizes a survival model and clinical data with various radiation doses from prospective trials to determine radiation dose–response parameters, such as radiosensitivity, and identify single-nucleotide-polymorphism (SNP) biomarkers that can potentially predict the dose response and guide personalized radiotherapy. Methods The study included 92 consecutive stage-III NSCLC patients with doses varying from 60 to 91 Gy. Logistic regression analysis of survival varying with SNP genotype and radiation dose was used to screen candidates for dose–response analysis. The dose–response parameter, represented by D50, was derived by fitting survival data into a model that takes into account both tumor control and treatment mortality. A candidate would be considered as a predictor if the 90% confident intervals (90% CIs) of D50 for the 2 groups stratified by the SNP genotype were separated. Results One SNP-signature (combining ERCC2:rs238406 and ERCC1:rs11615) was found to predict dose–response. D50 values are 63.7 (90% CI: 53.5–66.3) Gy and 76.1 (90% CI: 71.3, 84.6) Gy for the 2 groups stratified by the genotypes. Using this biomarker-based model, a personalized dose prescription may be generated to improve 2-year survival from ∼50% to 85% and ∼3% to 73% for hypothetical sensitive and resistant patients, respectively. Conclusions We have developed a survival model that may be used to identify genomic markers, such as ERCC1/2 SNPs, to predict radiation dose–response and potentially guide personalized radiotherapy." @default.
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• W1816156720 date "2015-10-01" @default.
• W1816156720 modified "2023-10-03" @default.
• W1816156720 title "Use a survival model to correlate single-nucleotide polymorphisms of DNA repair genes with radiation dose–response in patients with non-small cell lung cancer" @default.
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• W1816156720 doi "https://doi.org/10.1016/j.radonc.2015.07.024" @default.
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