Cost-Benefit Model System of Chronic Diseases in Australia to Assess and Rank Prevention and Treatment Options

Chronic diseases - eg heart disease, cancer, diabetes, mental disorders - affect around 80% of older Australians, are the main causes of disability and premature death, and account for 70% of total health expenditures. Because lifestyle patterns are major risk factors, chronic disease prevention and treatment are not only of medical concern, but also of considerable social, family-level and personal interest. While this makes microsimulation approaches particularly suitable for assessing intervention costs and benefits, such approaches will need to be combined with disease-progression models if health status and treatment choices are also to be simulated. AIMS: Describe methodological and technical proposals for the development of a cost-benefit model-system. METHODS: Several chronic disease progression models are to be linked to an ‘Umbrella’ microsimulation model representing the Australian population. To project 20 years ahead, use of reweighting techniques are proposed for population projections, disease-specific predictions and for health-related projections. The model-system is to account simultaneously for Australians’ demographic, socioeconomic and health-risk-factor characteristics; progression of their health status; the number of chronic diseases (comorbidities) they accumulate over time; health-related expenditures; and changes in quality of life. Standard methods are proposed to estimate costs versus benefits of simulated policy interventions and related quality of life improvements. KEY OUTCOME: Proposal of novel methods for modelling comorbidities - a task rarely attempted, although quality of life is known to decline and health expenditures to increase well above what a linear addition of the effects of individual chronic diseases would predict.Chronic Disease, Comorbidities, Cost-Benefit Model, Australia

Scaling up Type 2 Diabetes Prevention Programs: National and State Interventions in Australia

Australia has one of the world's largest systematic, government-funded diabetes prevention programs. This chapter describes a federally-funded national program, a state-funded program in Victoria and an implementation trial in New South Wales. A coincidence of events, influential individuals and policy directions has led to these initiatives

Prospective epidemiological study of injuries in the Australian National Soccer Competition

Sporting participation has numerous benefits to the individual and the community. Sports injury is an unfortunate consequence of participation and can have a negative physical, psychosocial and financial impact. Prevention of sporting injury can reduce the barriers to sporting participation. Injury prevention methodology considers injury surveillance to be one of the initial steps in the process of planning, developing and assessing the effectiveness of any prevention strategy implemented. Injury surveillance relies on a clear and unambiguous definition of injury and a reliable method of data collection to provide an accurate profile of injuries. Globally, there is published injury surveillance data available for professional soccer competitions in most regions of the world, with the notable exception of the Australian competition. Within Australia, injury surveillance results have been published for Rugby League, Rugby Union and Australian Rules Football. Our injury surveillance of the Australian professional soccer competition allows comparison to global injury data on soccer injuries and to other football codes within Australia. It also quantifies the significant risk of subsequent injury after an initial hip/groin injury and the player salary cost of injury in the Hyundai A-League. This new data advances the knowledge base of the sporting injury profile of professional soccer and informs the next stage of injury prevention program development

Expectancies in Double-Blind Randomised Placebo-Controlled Trials and Placebo-Induced Side Effects

The majority of research on the placebo effect has focused on beneficial effects in patients or participants told to expect an active treatment, but who are actually given a placebo. Two important and relatively understudied aspects of the placebo effect are the extent to which expectancies influence outcomes in double-blind randomised placebo-controlled trials (RCTs) and whether the placebo effect contributes to treatment side effects. The current project investigated these two issues in both clinical and experimental settings. The first study involved reanalysing a double-blind RCT of naltrexone and acamprosate for alcohol dependence based on whether participants believed they had been allocated to receive active treatment or placebo (perceived treatment). The second study extended on this by developing an experimental model for these effects using dummy (placebo only) double-blind RCTs for cognitive performance. This allowed for the manipulation of observable changes in the form of false feedback. The third study investigated whether warning participants about side effects increases their occurrence, frequency, and/or severity in three dummy trials for sleep difficulty in healthy volunteers. The final study complemented this by examining whether first time chemotherapy patients’ expectancies for nausea were associated with their post-chemotherapy nausea. The studies on perceived treatment in double-blind RCTs indicated that participants’ beliefs about their treatment allocation can influence their actual treatment outcomes via the placebo effect and that these beliefs are affected by the feedback they receive about their performance. The studies on placebo-induced side effects indicated that the placebo effect may contribute to treatment side effects but that this effect is generally likely to be small. These findings confirm that the placebo effect can influence treatment outcomes and emphasise the importance of considering patient expectancies when delivering medical treatment. They also highlight some general limitations associated with research on the placebo effect, which include, whether conveying uncertainty undermines the placebo effect and whether measuring or manipulating expectancies is the best way to evaluate the placebo effect

Follow-up of blood-pressure lowering and glucose control in type 2 diabetes.

BACKGROUND In the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) factorial trial, the combination of perindopril and indapamide reduced mortality among patients with type 2 diabetes, but intensive glucose control, targeting a glycated hemoglobin level of less than 6.5%, did not. We now report results of the 6-year post-trial follow-up. METHODS We invited surviving participants, who had previously been assigned to perindopril–indapamide or placebo and to intensive or standard glucose control (with the glucose-control comparison extending for an additional 6 months), to participate in a post-trial follow-up evaluation. The primary end points were death from any cause and major macrovascular events. RESULTS The baseline characteristics were similar among the 11,140 patients who originally underwent randomization and the 8494 patients who participated in the post-trial follow-up for a median of 5.9 years (blood-pressure–lowering comparison) or 5.4 years (glucose-control comparison). Between-group differences in blood pressure and glycated hemoglobin levels during the trial were no longer evident by the first post-trial visit. The reductions in the risk of death from any cause and of death from cardiovascular causes that had been observed in the group receiving active blood-pressure–lowering treatment during the trial were attenuated but significant at the end of the post-trial follow-up; the hazard ratios were 0.91 (95% confidence interval [CI], 0.84 to 0.99; P=0.03) and 0.88 (95% CI, 0.77 to 0.99; P=0.04), respectively. No differences were observed during follow-up in the risk of death from any cause or major macrovascular events between the intensive-glucose-control group and the standard-glucose-control group; the hazard ratios were 1.00 (95% CI, 0.92 to 1.08) and 1.00 (95% CI, 0.92 to 1.08), respectively. CONCLUSIONS The benefits with respect to mortality that had been observed among patients originally assigned to blood-pressure–lowering therapy were attenuated but still evident at the end of follow-up. There was no evidence that intensive glucose control during the trial led to long-term benefits with respect to mortality or macrovascular events

A Systematic Review of the Effect of Expectancy on Treatment Responses to Acupuncture

Randomised controlled trials (RCTs) of acupuncture often find equivalent responses to real and placebo acupuncture despite both appearing superior to no treatment. This raises questions regarding the mechanisms of acupuncture, especially the contribution of patient expectancies. We systematically reviewed previous research assessing the relationship between expectancy and treatment responses following acupuncture, whether real or placebo. To be included, studies needed to assess and/or manipulate expectancies about acupuncture and relate these to at least one health-relevant outcome. Nine such independent studies were identified through systematic searches of Medline, PsycInfo, PubMed, and Cochrane Clinical Trials Register. The methodology and reporting of these studies were quite heterogeneous, meaning that meta-analysis was not possible. A descriptive review revealed that five studies found statistically significant effects of expectancy on a least one outcome, with three also finding evidence suggestive of an interaction between expectancy and type of acupuncture (real or placebo). While there were some trends in significant effects in terms of study characteristics, their generality is limited by the heterogeneity of study designs. The differences in design across studies highlight some important methodological considerations for future research in this area, particularly regarding whether to assess or manipulate expectancies and how best to assess expectancies

Factors influencing participant enrolment in a diabetes prevention program in general practice: lessons from the Sydney diabetes prevention program

Background: The effectiveness of lifestyle interventions in reducing diabetes incidence has been well established. Little is known, however, about factors influencing the reach of diabetes prevention programs. This study examines the predictors of enrolment in the Sydney Diabetes Prevention Program (SDPP), a community-based diabetes prevention program conducted in general practice, New South Wales, Australia from 2008&ndash;2011.Methods: SDPP was an effectiveness trial. Participating general practitioners (GPs) from three Divisions of General Practice invited individuals aged 50&ndash;65 years without known diabetes to complete the Australian Type 2 Diabetes Risk Assessment tool. Individuals at high risk of diabetes were invited to participate in a lifestyle modification program. A multivariate model using generalized estimating equations to control for clustering of enrolment outcomes by GPs was used to examine independent predictors of enrolment in the program. Predictors included age, gender, indigenous status, region of birth, socio-economic status, family history of diabetes, history of high glucose, use of anti-hypertensive medication, smoking status, fruit and vegetable intake, physical activity level and waist measurement.Results: Of the 1821 eligible people identified as high risk, one third chose not to enrol in the lifestyle program. In multivariant analysis, physically inactive individuals (OR: 1.48, P = 0.004) and those with a family history of diabetes (OR: 1.67, P = 0.000) and history of high blood glucose levels (OR: 1.48, P = 0.001) were significantly more likely to enrol in the program. However, high risk individuals who smoked (OR: 0.52, P = 0.000), were born in a country with high diabetes risk (OR: 0.52, P = 0.000), were taking blood pressure lowering medications (OR: 0.80, P = 0.040) and consumed little fruit and vegetables (OR: 0.76, P = 0.047) were significantly less likely to take up the program.Conclusions: Targeted strategies are likely to be needed to engage groups such as smokers and high risk ethnic groups. Further research is required to better understand factors influencing enrolment in diabetes prevention programs in the primary health care setting, both at the GP and individual level.<br /

A bi-directional relationship between obesity and health-related quality of life : evidence from the longitudinal AusDiab study

Objective: To assess the prospective relationship between obesity and health-related quality of life, including a novel assessment of the impact of health-related quality of life on weight gain.Design and setting: Longitudinal, national, population-based Australian Diabetes, Obesity and Lifestyle (AusDiab) study, with surveys conducted in 1999/2000 and 2004/2005.Participants: A total of 5985 men and women aged 25 years at study entry.Main outcome measure(s): At both time points, height, weight and waist circumference were measured and self-report data on health-related quality of life from the SF-36 questionnaire were obtained. Cross-sectional and bi-directional, prospective associations between obesity categories and health-related quality of life were assessed.Results: Higher body mass index (BMI) at baseline was associated with deterioration in health-related quality of life over 5 years for seven of the eight health-related quality of life domains in women (all P0.01, with the exception of mental health, P&gt;0.05), and six out of eight in men (all P&lt;0.05, with the exception of role-emotional, P=0.055, and mental health, P&gt;0.05). Each of the quality-of-life domains related to mental health as well as the mental component summary were inversely associated with BMI change (all P&lt;0.0001 for women and P0.01 for men), with the exception of vitality, which was significant in women only (P=0.008). For the physical domains, change in BMI was inversely associated with baseline general health in women only (P=0.023).Conclusions: Obesity was associated with a deterioration in health-related quality of life (including both physical and mental health domains) in this cohort of Australian adults followed over 5 years. Health-related quality of life was also a predictor of weight gain over 5 years, indicating a bi-directional association between obesity and health-related quality of life. The identification of those with poor health-related quality of life may be important in assessing the risk of future weight gain, and a focus on health-related quality of life may be beneficial in weight management strategies.<br /

The healthiness of food and beverage advertising on Sydney train stations: regulation and policy implications

The results of this study highlight the inadequacy of Australia’s voluntary self-regulatory system in protecting train commuters from exposure to unhealthy food and beverage advertising. Regulatory action by state government, such as placing a cap on the number of discretionary food advertisements per station, is required to address this issue

Attentional bias modification and pain: The role of sensory and affective stimuli

There is growing evidence to support attentional bias modification (ABM) techniques such as the modified dot-probe task within the pain literature. Such techniques can help to inform theoretical models of pain by identifying the causal role of attentional bias constructs. The aim of this research was to explore the effects of dot-probe ABM that trains individuals towards (+) or away from (-) sensory (S) and affective (A) pain words, on attentional biases, interpretation biases, and pain outcomes. Healthy undergraduate students (N= 106) completed questionnaires, an attentional bias dot-probe task, and an interpretation bias task before and after ABM, one of four ABM versions that differed in training direction (S+A+, S-A+, S+A-, S-A-), and pain outcomes using the cold pressor task. Those trained towards affective pain words were found to have a greater pain threshold but also greater distress at tolerance. However, mechanisms of change could not be established, as ABM did not affect attentional or interpretation bias, even though changes in attentional bias were associated with pain outcomes. These findings provide partial support for the threat interpretation model and highlight the utility of affective pain ABM, although further investigation of causal mechanisms is warranted