Baseline Immune Biomarkers as Predictors of MBSR(BC) Treatment Success in Off-Treatment Breast Cancer Patients
Biological Research For Nursing
Format: Journal Article
Publication Year: 2014
Pages: 429 - 437
Sources ID: 53456
Visibility: Public (group default)
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.