Baseline immune biomarkers as predictors of MBSR(BC) treatment success in off-treatment breast cancer patients.
Baseline immune biomarkers as predictors of MBSR(BC) treatment success in off-treatment breast cancer patients.
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DOI：
10.1177/1099800413519494
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发表时间：
2014-10
影响因子：
2.5
通讯作者：
Klein TW
中科院分区：
文献类型：
--
作者：
Reich RR;Lengacher CA;Kip KE;Shivers SC;Schell MJ;Shelton MM;Widen RH;Newton C;Barta MK;Paterson CL;Farias JR;Cox CE;Klein TW
专注于以患者为中心的医学的研究人员越来越多地试图确定预测治疗成功的基线因素。由于淋巴细胞亚群的数量和功能在应激过程中发生变化，我们假设这些亚群将作为应激标记，从而预测哪些乳腺癌患者将从基于正念的压力减轻(MBSR)促进的压力缓解中受益最大。这项研究的目的是评估基线生物标记物水平是否可以预测乳腺癌幸存者接受MBSR干预后症状改善。这项随机对照试验涉及41名患者，他们被分配到MBSR(BC)干预组或不治疗对照组。在基线时评估生物标志物，并在6周后评估症状变化。生物标志物包括外周血中常见的淋巴细胞亚群，以及T细胞在有丝分裂原刺激下被激活并分泌细胞因子的能力。使用Spearman相关性来确定基线生物标记物和6周症状改善之间的单变量关系。接下来，使用反向消除回归模型从单变量分析中确定最强的预测因素。多个基线生物标志物与6周症状改善呈显著正相关。回归模型确定B淋巴细胞和干扰素-γ是胃肠道改善的最强预测因子(p<；.01)，+CD-4+CD_8是认知/心理(CP)改善的最强预测因子(p=.02)，淋巴细胞和白介素4是疲劳改善的最强预测因子(p<；.01)。这些结果为使用基线生物标志物作为预测指标来确定可能从这种干预中受益的患者提供了初步证据。
Researchers focused on patient-centered medicine are increasingly trying to identify baseline factors that predict treatment success. Because the quantity and function of lymphocyte subsets change during stress, we hypothesized that these subsets would serve as stress markers and therefore predict which breast cancer patients would benefit most from mindfulness-based stress reduction (MBSR)-facilitated stress relief. The purpose of this study was to assess whether baseline biomarker levels predicted symptom improvement following an MBSR intervention for breast cancer survivors (MBSR[BC]). This randomized controlled trial involved 41 patients assigned to either an MBSR(BC) intervention group or a no-treatment control group. Biomarkers were assessed at baseline, and symptom change was assessed 6 weeks later. Biomarkers included common lymphocyte subsets in the peripheral blood as well as the ability of T cells to become activated and secrete cytokines in response to stimulation with mitogens. Spearman correlations were used to identify univariate relationships between baseline biomarkers and 6-week improvement of symptoms. Next, backward elimination regression models were used to identify the strongest predictors from the univariate analyses. Multiple baseline biomarkers were significantly positively related to 6-week symptom improvement. The regression models identified B-lymphocytes and interferon-γ as the strongest predictors of gastrointestinal improvement (p < .01), +CD4+CD8 as the strongest predictor of cognitive/psychological (CP) improvement (p = .02), and lymphocytes and interleukin (IL)-4 as the strongest predictors of fatigue improvement (p < .01). These results provide preliminary evidence of the potential to use baseline biomarkers as predictors to identify the patients likely to benefit from this intervention.