Biomarkers as Common Data Elements for Symptom and Self‐Management Science

Page, Gayle G.; Corwin, Elizabeth J.; Dorsey, Susan G.; Redeker, Nancy S.; McCloskey, Donna Jo; Austin, Joan K.; Guthrie, Barbara; Moore, Shirley; Barton, Debra L.; Kim, Miyong T.; Docherty, Sharron L.; Waldrop‐Valverde, Drenna; Bailey, Donald E.; Schiffman, Rachel F.; Starkweather, Angela; Ward, Teresa M.; Bakken, Suzanne; Hickey, Kathleen T.; Renn, Cynthia L.; Grady, Patricia A.

doi:10.1111/jnu.12378

Cited by 29 publications

(26 citation statements)

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“…Less than 80% of participants felt that family and caregivers understood what they were going through when feeling ill, which is in line with previous literature finding greater interference with social activities in MPC patients than in single cancer patients , as measured by the Impact of Cancer scale (Costa et al, 2016). As identified in Section 3.0, BMI (overweight vs normal weight and obesity), HPA axis marker, neuropeptide, and DNA polymorphisms) (Moore et al, 2016;Page et al, 2018).…”

Section: Discussionsupporting

confidence: 84%

18 - Characterizing Psychobehavioral Risks in Survivors of Multiple Primary Cancers

Belcher¹

2019

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Background: As the population ages and cancer survival improves, the incidence of multiple primary cancers (MPC) is increasing. Several studies have documented poorer health outcomes among adults with MPC compared to single-cancer survivors. However, there is a paucity of research focused on understanding factors linking MPC to poor health outcomes and identifying individual (e.g., personality, sociodemographic, clinical) factors that increase risk. Purpose: The purpose of this study was to test a psychobehavioral stress-response model to identify factors associated with MPC health outcomes. We aimed to: 1) test the hypothesized model, examining linear relations among six latent variables: perceived stress, psychological response, behavioral response, financial toxicity, social health, and physical health; 2) explore associations between individual characteristics and upstream latent variables; and 3) describe self-management behaviors of MPC survivors. Methods: This cross-sectional study included MPC survivors recruited through a regional tumor registry whose first cancers (stages I-III) were diagnosed within 1-10 years. Data were collected via 1) a battery of validated questionnaires to measure latent variables and covariates; 2) tumor registry records; and 3) medical records. Structural equation modeling was performed to fit and modify the measurement model, specify the full SEM, and identify significant covariates. Descriptive statistics were conducted to characterize self-management. v Results: 211 participants completed questionnaires. Data fit a four-factor modified measurement model linking self-management, distress, financial toxicity, and functional health. Overweight BMI, graduate education, less neuroticism, and increased social support predicted better self-management. Poorer self-management, greater neuroticism, and lower social support predicted increased distress. Greater distress predicted financial toxicity. Greater distress and financial toxicity predicted poorer functional health. Scores for positive selfmanagement were generally high; obesity rates were above published norms. Conclusions: MPC survivors with higher risk BMI, less education, greater neuroticism, and lower social support should be considered at risk for poorer self-management and negative health outcomes. Self-management behaviors and distress are potentially modifiable intervention targets to reduce financial toxicity and improve functional health. Future research should evaluate the model with a focus on developing the science of MPC self-management and financial toxicity and include longitudinal assessments to identify critical times of increased vulnerability during MPC survivorship. vi

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Section: Discussionsupporting

confidence: 84%

18 - Characterizing Psychobehavioral Risks in Survivors of Multiple Primary Cancers

Belcher¹

2019

Preprint

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“…Precision measures may help explain why individuals with the same clinical diagnosis have dissimilar symptoms with different severity, triggers or degree of life interference and diverse responses to pharmacologic and non-pharmacologic therapies. For example, specific biomarkers may reflect tissue damage produced by inflammation that results in pain, nausea, or fatigue (Page et al, 2018; Starkweather, Lyon, & Schubert, 2013). Omics approaches provide information on potential physiological mechanisms at play (i.e., proteomics and inflammation) and serve as outcome measures (i.e., diet changes and microbiome).…”

Section: Precision Health Approaches For Advancing the Science Of Symmentioning

confidence: 99%

“…This requires careful conceptualization of the role of precision health and the integration of multiple data sources (e.g., phenotype including lifestyle and environmental factors, genotype and other biomarkers) supported by an information and data science infrastructure. (Page et al, 2018; Starkweather et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Precision health: Advancing symptom and self-management science

et al. 2019

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Precision health considers individual lifestyle, genetics, behaviors, and environment context and facilitates interventions aimed at helping individuals achieve well-being and optimal health. The purposes of this manuscript are to present the Nursing Science Precision Health (NSPH) Model and describe the integration of precision health concepts within the domains of symptom and self-management science as reflected in the National Institute of Nursing Research P30 Centers of Excellence and P20 Exploratory Centers. Center members developed the NSPH Model and the manuscript based on presentations and discussions at the annual NINR Center Directors Meeting and in follow-up telephone meetings. The NSPH Model comprises four precision components (measurement; characterization of phenotype including lifestyle and environment; characterization of genotype and other biomarkers; and intervention target discovery, design, and delivery) that are underpinned by an information and data science infrastructure. Nurse scientist leadership is necessary to realize the vision of precision health.

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“…In the present study, Poly I:C treatment differentially altered the expression of Fkbp5 and Nr3c1 in brains of mice stressed with Poly I:C either between genotypes of mice or in contrast to saline treatment. The alteration of IL-1β level, as well as that of BDNF [ 33 , 54 ], has been observed in major depressive patients, according to systematic Review and Meta-Analysis [ 28 ]. In the present study, Poly I:C treatment differentially altered the expression of interleukin Il1b gene in the striatum between the Cnr2 heterozygotes and the wild type mice.…”

Section: Discussionmentioning

confidence: 99%

Cannabinoid CB2 Receptor Gene and Environmental Interaction in the Development of Psychiatric Disorders

et al. 2018

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CB2 cannabinoid receptor (CB2R) gene is associated with depression. We investigated the gene-environment interaction between CB2R function and diverse stressors. First, anxiety-like behavior during chronic-mild-stress (CMS) was evaluated in C57BL/6JJmsSlc mice following treatment with CB2R agonist JWH015 or inverse-agonist AM630. Second, locomotor activity and anxiety-like behavior were measured following exposure to an immune poly I:C stressor. Gene expressions of HPA axis related molecules, Fkbp5, Nr3c1 and Crf and pro-inflammatory cytokine Il-1b, as well as Bdnf as a key neurotrophin that supports neuron health, function, and synaptic plasticity, were determined in hippocampus of Cnr2 knockout mice, as indicators of stressful environment. CMS-induced anxiety-like behavior was enhanced by AM630 and reduced by JWH015 and fluvoxamine. Poly I:C reduced locomotor activity and increased anxiety-like behavior, and these effects were pronounced in the heterozygote than in the wild type mice. Fkbp5 and Nr3c1 expression were lower in the Cnr2 heterozygotes than in the wild type mice with Poly I:C treatment. These findings indicate that interaction between CB2R gene and stressors increases the risk of depression-like behaviors that may be linked with neuro-immune crosstalk. Further studies in human subjects are necessary to determine the role of CB2R and environmental interaction in the development of depression.

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Biomarkers as Common Data Elements for Symptom and Self‐Management Science

Abstract: The use of biomarker CDEs in biobehavioral symptoms research will facilitate the reproducibility and generalizability of research findings and benefit symptom and self-management science.

Cited by 29 publications

References 73 publications

18 - Characterizing Psychobehavioral Risks in Survivors of Multiple Primary Cancers

18 - Characterizing Psychobehavioral Risks in Survivors of Multiple Primary Cancers

Precision health: Advancing symptom and self-management science

Cannabinoid CB2 Receptor Gene and Environmental Interaction in the Development of Psychiatric Disorders

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