• Support Care Cancer · Nov 2013

    Symptom clusters of pain, depressed mood, and fatigue in lung cancer: assessing the role of cytokine genes.

    • Cielito C Reyes-Gibby, Michael D Swartz, Xiaoying Yu, Xifeng Wu, Sriram Yennurajalingam, Karen O Anderson, Margaret R Spitz, and Sanjay Shete.
    • Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, Unit 1468, 1155 Pressler Street, Houston, TX, 77030-4009, USA, creyes@mdanderson.org.
    • Support Care Cancer. 2013 Nov 1;21(11):3117-25.

    PurposeSymptom clusters, the multiple, co-occurring symptoms experienced by cancer patients, are debilitating and affects quality of life. We assessed if a panel of immune-response genes may underlie the co-occurrence of severe pain, depressed mood, and fatigue and help identify patients with severe versus non-severe symptom clusters.MethodsSymptoms were assessed at presentation, prior to cancer treatment in 599 newly diagnosed lung cancer patients. We applied cluster analyses to determine the patients with severe versus non-severe symptom clusters of pain, depressed mood, and fatigue.ResultsTwo homogenous clusters were identified. One hundred sixteen patients (19 %) comprised the severe symptom cluster, reporting high intensity of pain, depressed mood, and fatigue and 183 (30 %) patients reported low intensity of these symptoms. Using Bayesian model averaging methodology, we found that of the 55 single nucleotide polymorphisms assessed, an additive effect of mutant alleles in endothelial nitric oxide synthase (-1474 T/A) (posterior probability of inclusion (PPI) = 0.78, odds ratio (OR) = 0.54, 95 % credible interval (CI) = (0.31, 0.93)); IL1B T-31C (PPI = 0.72, OR = 0.55, 95 % CI = (0.31, 0.97)); TNFR2 Met(196)Arg (PPI = 0.70, OR = 1.85, 95 % CI = (1.03, 3.36)); PTGS2 exon 10+837T > C (PPI = 0.69, OR = 0.54, 95 % CI = (0.28, 0.99)); and IL10RB Lys(47)Glu (PPI = 0.68; OR = 1.74; 95 % CI = (1.04, 2.92)) were predictive for symptom clusters.ConclusionsGenetic polymorphisms may facilitate identification of high-risk patients and development of individualized symptom therapies.

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