Objectives To describe the effect of multidisciplinary care on survival in women treated for breast cancer.Design Retrospective, comparative, non-randomised, interventional cohort study.Setting NHS ...hospitals, health boards in the west of Scotland, UK.Participants 14 358 patients diagnosed with symptomatic invasive breast cancer between 1990 and 2000, residing in health board areas in the west of Scotland. 13 722 (95.6%) patients were eligible (excluding 16 diagnoses of inflammatory cancers and 620 diagnoses of breast cancer at death).Intervention In 1995, multidisciplinary team working was introduced in hospitals throughout one health board area (Greater Glasgow; intervention area), but not in other health board areas in the west of Scotland (non-intervention area).Main outcome measures Breast cancer specific mortality and all cause mortality.Results Before the introduction of multidisciplinary care (analysed time period January 1990 to September 1995), breast cancer mortality was 11% higher in the intervention area than in the non-intervention area (hazard ratio adjusted for year of incidence, age at diagnosis, and deprivation, 1.11; 95% confidence interval 1.00 to 1.20). After multidisciplinary care was introduced (time period October 1995 to December 2000), breast cancer mortality was 18% lower in the intervention area than in the non-intervention area (0.82, 0.74 to 0.91). All cause mortality did not differ significantly between populations in the earlier period, but was 11% lower in the intervention area than in the non-interventional area in the later period (0.89, 0.82 to 0.97). Interrupted time series analyses showed a significant improvement in breast cancer survival in the intervention area in 1996, compared with the expected survival in the same year had the pre-intervention trend continued (P=0.004). This improvement was maintained after the intervention was introduced.Conclusion Introduction of multidisciplinary care was associated with improved survival and reduced variation in survival among hospitals. Further analysis of clinical audit data for multidisciplinary care could identify which aspects of care are most associated with survival benefits.
It has previously been hypothesized that lower socio-economic status can accelerate biological ageing, and predispose to early onset of disease. This study investigated the association of ...socio-economic and lifestyle factors, as well as traditional and novel risk factors, with biological-ageing, as measured by telomere length, in a Glasgow based cohort that included individuals with extreme socio-economic differences.
A total of 382 blood samples from the pSoBid study were available for telomere analysis. For each participant, data was available for socio-economic status factors, biochemical parameters and dietary intake. Statistical analyses were undertaken to investigate the association between telomere lengths and these aforementioned parameters.
The rate of age-related telomere attrition was significantly associated with low relative income, housing tenure and poor diet. Notably, telomere length was positively associated with LDL and total cholesterol levels, but inversely correlated to circulating IL-6.
These data suggest lower socio-economic status and poor diet are relevant to accelerated biological ageing. They also suggest potential associations between elevated circulating IL-6, a measure known to predict cardiovascular disease and diabetes with biological ageing. These observations require further study to tease out potential mechanistic links.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Meaningfully assessing effectiveness of interventions aimed at reducing health inequalities through tackling social determinants of health is challenging. Complex systems and real world delivery ...environments render many traditional academic tools obsolete. Does the production of big data and possibiliites this opens up in the realm of data science offer potential solutions? Methods: 1) Accessing large datasets from across the architecture of health and social services, including primary and secondary care, police, education and linking these using anonymised unique identifiers. 2) Machine learning (using algorithms developed in R Studio) can be employed to identify associations between grouped diverse indicators across the lifecourse. 3) Probabilistic models can then be developed to support better design, targetting and measurement of service redesign and implementation of interventions. 4) Embedded action learning and ethnographic approaches can be used to provide useful practical support to development of interventions and to provide quantitative and qualitative data to allow triangulation with patterns identified through the data science techniques. 5) Frontline staff and the general public will contribute to the refinement of specific research questions to be asked of the data. Results: Currently, identification of the range of datasets and data quality held by public sector actors in Scotland is ongoing. This will be followed by establishment of formal information governance arrangements before algorithms will be trained on training data and applied to the full range of datasets identified, linked and made available to the research team. Discussion: The experience of the Links Worker Programme, which implemented a new social practioner role within GP practices in deprived neighbourhoods in glasgow, highlighted the difficulty in sensitively measuring the biological impact of socially oriented interventions. Advances in big data and data science may or may not ulitmately aid enhanced understanding of social determinants of health and support reduction in health inequality, certainly though, it is a prescient and logical area to investigate and the inherent potential is exciting. The two pronged approach of data science and action learning supporting robust recod keeping on the ground, may offer viable and 'robust enough' alternatives to RCTs in real world environments. Conclusion: By time of conference the first findings from analysis of large datasets linking Chiild Health and Education data across Scottish local authorities will be available. Lessons learned: Current procedures for identifying and accessing publically held data are cumbersome and time consuming. Limitations: The extent, nature and completeness of the datasets will to some extent guide the research. Future research: Future collaborations with user experince and user led design will be of importance in helping design end user interfaces that are aligned to provide data amenable to data science approaches, should these prove useful in the field of social determinants/health inequalities.
Preliminary data mostly from animal models suggest the sST2/IL-33 pathway may have causal relevance for vascular disease and diabetes and thus point to a potential novel inflammatory link to ...cardiometabolic disease. However, the characterisation of sST2 levels in terms of metabolic or vascular risk in man is completely lacking. We sought to address this gap via a comprehensive analysis of risk factor and vascular correlates of sST2 in a cross-sectional study (pSoBid). We measured sST2 in plasma in 639 subjects and comprehensively related it to cardiovascular and diabetes risk factors and imaged atherosclerosis measures. Circulating sST2 levels increased with age, were lower in women and in highest earners. After adjusting for age and gender, sST2 levels associated strongly with markers of diabetes, including triglycerides effect estimate (EE) per 1 standard deviation increase in sST2:1.05 95%CI 1.01,1.10), liver function (alanine aminotransaminase ALT and γ-glutamyl transferase GGT: EE 1.05 1.01,1.09 and 1.13 1.07,1.19 respectively), glucose (1.02 1.00,1.03) and sICAM-1 (1.05 1.02,1.07). However, sST2 levels were not related to smoking, cholesterol, blood pressure, or atheroma (carotid intima media thickness, plaque presence). These results suggest that sST2 levels, in individuals largely without vascular disease, are related principally to markers associated with diabetes and ectopic fat and add support for a role of sST2 in diabetes. Further mechanistic studies determining how sST2 is linked to diabetes pathways may offer new insights into the inflammatory paradigm for type 2 diabetes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Socioeconomic gradients in health persist despite public health campaigns and improvements in healthcare. The Psychosocial and Biological Determinants of Ill-health (pSoBid) study was designed to ...uncover novel biomarkers of chronic disease that may help explain pathways between socioeconomic adversity and poorer physical and mental health.
We examined links between indicators of early life adversity, possible intermediary phenotypes, and markers of ill health in adult subjects (n = 666) recruited from affluent and deprived areas. Classical and novel risk factors for chronic disease (lung function and atherosclerosis) and for cognitive performance were assessed, and associations sought with early life variables including conditions in the parental home, family size and leg length.
Associations were observed between father's occupation, childhood home status (owner-occupier; overcrowding) and biomarkers of chronic inflammation and endothelial activation in adults (C reactive protein, interleukin 6, intercellular adhesion molecule; P < 0.0001) but not number of siblings and leg length. Lung function (forced expiratory volume in 1 second) and cognition (Choice Reaction Time, the Stroop test, Auditory Verbal Learning Test) were likewise related to early life conditions (P < 0.001). In multivariate models inclusion of inflammatory variables reduced the impact and independence of early life conditions on lung function and measures of cognitive ability. Including variables of adult socioeconomic status attenuated the early life associations with disease biomarkers.
Adverse levels of biomarkers of ill health in adults appear to be influenced by father's occupation and childhood home conditions. Chronic inflammation and endothelial activation may in part act as intermediary phenotypes in this complex relationship. Reducing the 'health divide' requires that these life course determinants are taken into account.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Associations between socio-economic status (SES), personality and inflammation were examined to determine whether low SES subjects scoring high on neuroticism or hostility might suffer relatively ...higher levels of inflammation than affluent subjects.
In a cross-sectional design, 666 subjects were recruited from areas of high (most deprived - "MD") and low (least deprived - "LD") deprivation. IL-6, ICAM-1, CRP and fibrinogen were measured along with demographic and health-behaviour variables, and personality traits of neuroticism, extraversion and psychoticism (hostility). Regression models assessed the prediction of inflammation as a function of personality, deprivation and their interaction.
Levels of CRP and IL-6 were an increasing function of neuroticism and extraversion only in LD subjects opposite trends were seen in MD subjects. The result was ascribed parsimoniously to an inflammatory ceiling effect or, more speculatively, to SES-related health-behaviour differences. Psychoticism was strongly associated with ICAM-1 in both MD and LD subjects.
The association between neuroticism, CRP and IL-6 may be reduced in MD subjects confirming speculation that the association differs across population sub-groups. The association between psychoticism and ICAM-1 supports evidence that hostility has adverse effects upon the endothelium, with consequences for cardiovascular health. Health interventions may be more effective by accounting for personality-related effects upon biological processes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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