Complementary and alternative medicine use in oncology: A questionnaire survey of patients and health care professionals

<p>Abstract</p> <p>Background</p> <p>We aimed to investigate the prevalence and predictors of Complementary and Alternative Medicine (CAM) use among cancer patients and non-cancer volunteers, and to assess the knowledge of and attitudes toward CAM use in oncology among health care professionals.</p> <p>Methods</p> <p>This is a cross-sectional questionnaire survey conducted in a single institution in Ireland. Survey was performed in outpatient and inpatient settings involving cancer patients and non-cancer volunteers. Clinicians and allied health care professionals were asked to complete a different questionnaire.</p> <p>Results</p> <p>In 676 participants including 219 cancer patients; 301 non-cancer volunteers and 156 health care professionals, the overall prevalence of CAM use was 32.5% (29.1%, 30.9% and 39.7% respectively in the three study cohorts). Female gender (p < 0.001), younger age (p = 0.004), higher educational background (p < 0.001), higher annual household income (p = 0.001), private health insurance (p = 0.001) and non-Christian (p < 0.001) were factors associated with more likely CAM use. Multivariate analysis identified female gender (p < 0.001), non-Christian (p = 0.001) and private health insurance (p = 0.015) as independent predictors of CAM use. Most health care professionals thought they did not have adequate knowledge (58.8%) nor were up to date with the best evidence (79.2%) on CAM use in oncology. Health care professionals who used CAM were more likely to recommend it to patients (p < 0.001).</p> <p>Conclusions</p> <p>This study demonstrates a similarly high prevalence of CAM use among oncology health care professionals, cancer and non cancer patients. Patients are more likely to disclose CAM usage if they are specifically asked. Health care professionals are interested to learn more about various CAM therapies and have poor evidence-based knowledge on specific oncology treatments. There is a need for further training to meet to the escalation of CAM use among patients and to raise awareness of potential benefits and risks associated with these therapies.</p

Identification and validation of oncologic miRNA biomarkers for Luminal A-like breast cancer

Introduction: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu-) breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. Methods: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n=54) and controls (n=56). RNA was extracted, reverse transcribed and subjected to microarray analysis (n=10 Luminal A-like; n=10 Control). Differentially expressed miRNAs were identified by artificial neural network (ANN) data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n=44 Luminal A; n=46 Control) and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. Results: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis ( miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652 ). The biomarker potential of 4 miRNAs ( miR-29a, miR-181a , miR-223 and miR-652 ) was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p=0.001, 0.004, 0.009 and 0.004 respectively). Binary logistic regression confirmed that combination of 3 of these miRNAs ( miR-29a, miR-181a and miR-652 ) could reliably differentiate between cancers and controls with an AUC of 0.80. Conclusion: This study provides insight into the underlying molecular portrait of Luminal A-like breast cancer subtype. From an initial 76 miRNAs, 4 were validated with altered expression in the blood of women with Luminal A-like breast cancer. The expression profiles of these 3 miRNAs, in combination with mammography, has potential to facilitate accurate subtype- specific breast tumor detection

A multi-decade record of high quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) “living data” publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID

Younger age as a prognostic indicator in breast cancer: A cohort study

<p>Abstract</p> <p>Background</p> <p>The debate continues as to whether younger women who present with breast cancer have a more aggressive form of disease and a worse prognosis. The objectives of this study were to determine the incidence of breast cancer in women under 40 years old and to analyse the clinicopathological characteristics and outcome compared to an older patient cohort.</p> <p>Methods</p> <p>Data was acquired from a review of charts and the prospectively reviewed GUH Department of Surgery database. Included in the study were 276 women diagnosed with breast cancer under the age of forty and 2869 women over forty. For survival analysis each women less than 40 was matched with two women over forty for both disease stage and grade.</p> <p>Results</p> <p>The proportion of women diagnosed with breast cancer under the age of forty in our cohort was 8.8%. In comparison to their older counterparts, those under forty had a higher tumour grade (p = 0.044) and stage (p = 0.046), a lower incidence of lobular tumours (p < 0.001), higher estrogen receptor negativity (p < 0.001) and higher <it>HER2 </it>over-expression (p = 0.002); there was no statistical difference as regards tumour size (p = 0.477). There was no significant difference in overall survival (OS) for both groups; and factors like tumour size (p = 0.026), invasion (p = 0.026) and histological type (p = 0.027), PR (p = 0.031) and <it>HER2 </it>(p = 0.002) status and treatment received were independent predictors of OS</p> <p>Conclusion</p> <p>Breast cancer in younger women has distinct histopathological characteristics; however, this does not result in a reduced survival in this population.</p

Predicting general and cancer-related distress in women with newly diagnosed breast cancer

Background: Psychological distress can impact medical outcomes such as recovery from surgery and experience of side effects during treatment. Identifying the factors that explain variability in distress would guide future interventions aimed at decreasing distress. Two factors that have been implicated in distress are illness perceptions and coping, and are part of the Self-Regulatory Model of Illness Behaviour (SRM). The model suggests that coping mediates the relationship between illness perceptions and distress. Despite this; very little research has assessed this relationship with cancer-related distress, and none have examined women with screen-detected breast cancer. This study is the first to examine the relative contribution of illness perceptions and coping on general and cancer-related distress in women with screen-detected breast cancer. Methods: Women recently diagnosed with breast cancer (N = 94) who had yet to receive treatment completed measures of illness perceptions (Revised Illness Perception Questionnaire), cancer-specific coping (Mental Adjustment to Cancer Scale), general anxiety and depression (Hospital Anxiety and Depression scale), and cancer-related distress. Results: Hierarchical regression analyses revealed that medical variables, illness perceptions and coping predicted 50% of the variance in depression, 42% in general anxiety, and 40% in cancer-related distress. Believing in more emotional causes to breast cancer (beta = .22, p = .021), more illness identity (beta = .25, p = .004), greater anxious preoccupation (beta = .23, p = .030), and less fighting spirit (beta = -.31, p = .001) predicted greater depression. Greater illness coherence predicted less cancer-related distress (beta = -.20, p = .043). Greater anxious preoccupation also led to greater general anxiety (beta = .44, p &amp;lt; .001) and cancer-related distress (beta = .37, p = .001). Mediation analyses revealed that holding greater beliefs in a chronic timeline, more severe consequences, greater illness identity and less illness coherence increases cancer-specific distress (ps &amp;lt; .001) only if women were also more anxiously preoccupied with their diagnosis. Conclusions: Screening women for anxious preoccupation may help identify women with screen-detected breast cancer at risk of experiencing high levels of cancer-related distress; whilst illness perceptions and coping could be targeted for use in future interventions to reduce distress

Perspectives and Integration in SOLAS Science

Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm. Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean–atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studies illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency. The exchange of energy, gases and particles across the air-sea interface is controlled by a variety of biological, chemical and physical processes that operate across broad spatial and temporal scales. These processes influence the composition, biogeochemical and chemical properties of both the oceanic and atmospheric boundary layers and ultimately shape the Earth system response to climate and environmental change, as detailed in the previous four chapters. In this cross-cutting chapter we present some of the SOLAS achievements over the last decade in terms of integration, upscaling observational information from process-oriented studies and expeditionary research with key tools such as remote sensing and modelling. Here we do not pretend to encompass the entire legacy of SOLAS efforts but rather offer a selective view of some of the major integrative SOLAS studies that combined available pieces of the immense jigsaw puzzle. These include, for instance, COST efforts to build up global climatologies of SOLAS relevant parameters such as dimethyl sulphide, interconnection between volcanic ash and ecosystem response in the eastern subarctic North Pacific, optimal strategy to derive basin-scale CO2 uptake with good precision, or significant reduction of the uncertainties in sea-salt aerosol source functions. Predicting the future trajectory of Earth’s climate and habitability is the main task ahead. Some possible routes for the SOLAS scientific community to reach this overarching goal conclude the chapter

What Makes Retirees Happier: A Gradual or 'Cold Turkey' Retirement?

This study explores the factors that affect an individual’s happiness while transitioning into retirement. Recent studies highlight gradual retirement as an attractive option to older workers as they approach full retirement. However, it is not clear whether phasing or cold turkey makes for a happier retirement. Using longitudinal data from the Health and Retirement Study, this study explores what shapes the change in happiness between the last wave of full employment and the first wave of full retirement. Results suggest that what really matters is not the type of transition (gradual retirement or cold turkey), but whether people perceive the transition as chosen or forced

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples