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Genetic biomarkers associated with changes in quality of life and pain following palliative radiotherapy in patients with bone metastases

  
@article{APM16779,
	author = {Anthony Furfari and Bo Angela Wan and Keyue Ding and Andrew Wong and Liting Zhu and Andrea Bezjak and Rebecca Wong and Carolyn F. Wilson and Carlo DeAngelis and Azar Azad and Edward Chow and George S. Charames},
	title = {Genetic biomarkers associated with changes in quality of life  and pain following palliative radiotherapy in patients with bone  metastases},
	journal = {Annals of Palliative Medicine},
	volume = {0},
	number = {0},
	year = {2017},
	keywords = {},
	abstract = {Background: Patients with bone metastases undergoing palliative radiation therapy (RT) may experience changes in both the functional and symptomatic aspects of quality of life (QOL). The European Organization of Cancer Research and Treatment (EORTC) QOL Questionnaire Core-15 Palliative (QLQ-C15-PAL) is a validated questionnaire employed to assess QOL specifically in palliative patients. Our study aimed to identify single-nucleotide variant (SNV) genetic biomarkers associated with changes in QOL and pain.
Methods: Fifty-two patients who received a single 8-Gy RT for painful bone metastases completed the EORTC QOL-C15-PAL questionnaire prior to randomization and at 42-day post RT. Saliva samples obtained at day of RT were sequenced, and SNVs from genes involved in inflammation, radiation response, immune response, DNA damage, or QOL were assessed for association with changes in global QOL or the pain scale items using the Cochran-Armitage trend test. The penalized LASSO method with minimum Bayesian information criterion was used to select a multi-SNV model out of significant SNVs (PT had the largest positive and negative effect sizes, respectively (HS1BP3: 8.21, ABCA1: −3.44). The model for the response of QOL pain item included 8 SNVs, of which PLAUR rs4760 A>G and ELAC2rs11545302 had the largest positive and negative effect sizes, respectively (PLAUR: 5.23; ELAC: −3.84). The patients’ risk groups were highly predictive of QOL response (P},
	url = {http://apm.amegroups.com/article/view/16779}
}