Lifetime effects and cost-effectiveness of standard and higher-intensity statin therapy across population categories in the UK: a microsimulation modelling study.

Background: Cardiovascular disease incidence and mortality have declined across developed economies and granular up-to-date cost-effectiveness evidence is required for treatments targeting large populations. To assess the health benefits and cost-effectiveness of standard and higher intensity statin therapy in the contemporary UK population 40-70 years old. Methods: A cardiovascular disease microsimulation model, developed using the Cholesterol Treatment Trialists' Collaboration data (117,896 participants; 5 years follow-up), and calibrated in the UK Biobank cohort (501,854 participants; 9 years follow-up), projected risks of myocardial infarction, stroke, coronary revascularization, diabetes, cancer and vascular and nonvascular death for all UK Biobank participants without and with statin treatment. Meta-analyses of trials and cohort studies informed statins' relative effects on cardiovascular events, incident diabetes, myopathy and rhabdomyolysis. UK healthcare perspective was taken (2020/2021 UK£) with costs per 28 tablets of £1.10 for standard (35%-45% LDL cholesterol (LDL-C) reduction) and £1.68 for higher intensity (≥45% LDL-C reduction) generic statin. Findings: Across categories by sex, age, LDL-C, and cardiovascular disease history/10-year cardiovascular risk, lifetime standard statin increased survival by 0.28-1.85 years (0.20-1.09 quality-adjusted life years (QALYs)), and higher intensity statin by further 0.06-0.40 years (0.03-0.20 QALYs) per person. Standard statin was cost-effective across all categories with incremental cost per QALY from £280 to £8530, with higher intensity statin cost-effective at higher cardiovascular risks and higher LDL-C levels. Stopping statin early reduced benefits and was not cost-effective. Interpretation: Lifetime low-cost statin therapy is cost-effective across all 40-70 years old in UK. Strengthening and widening statin treatment could cost-effectively improve population health. Funding: UK NIHR Health Technology Assessment Programme (17/140/02).

Long-term cardiovascular risks and the impact of statin treatment on socioeconomic inequalities: a microsimulation model.

BACKGROUND: UK cardiovascular disease (CVD) incidence and mortality have declined in recent decades but socioeconomic inequalities persist. AIM: To present a new CVD model, and project health outcomes and the impact of guideline-recommended statin treatment across quintiles of socioeconomic deprivation in the UK. DESIGN AND SETTING: A lifetime microsimulation model was developed using 117 896 participants in 16 statin trials, 501 854 UK Biobank (UKB) participants, and quality-of-life data from national health surveys. METHOD: A CVD microsimulation model was developed using risk equations for myocardial infarction, stroke, coronary revascularisation, cancer, and vascular and non-vascular death, estimated using trial data. The authors calibrated and further developed this model in the UKB cohort, including further characteristics and a diabetes risk equation, and validated the model in UKB and Whitehall II cohorts. The model was used to predict CVD incidence, life expectancy, quality-adjusted life years (QALYs), and the impact of UK guideline-recommended statin treatment across socioeconomic deprivation quintiles. RESULTS: Age, sex, socioeconomic deprivation, smoking, hypertension, diabetes, and cardiovascular events were key CVD risk determinants. Model-predicted event rates corresponded well to observed rates across participant categories. The model projected strong gradients in remaining life expectancy, with 4-5-year (5-8 QALYs) gaps between the least and most socioeconomically deprived quintiles. Guideline-recommended statin treatment was projected to increase QALYs, with larger gains in quintiles of higher deprivation. CONCLUSION: The study demonstrated the potential of guideline-recommended statin treatment to reduce socioeconomic inequalities. This CVD model is a novel resource for individualised long-term projections of health outcomes of CVD treatments.

Estimating Costs Associated with Disease Model States Using Generalized Linear Models: A Tutorial.

Estimates of costs associated with disease states are required to inform decision analytic disease models to evaluate interventions that modify disease trajectory. Increasingly, decision analytic models are developed using patient-level data with a focus on heterogeneity between patients, and there is a demand for costs informing such models to reflect individual patient costs. Statistical models of health care costs need to recognize the specific features of costs data which typically include a large number of zero observations for non-users, and a skewed and heavy right-hand tailed distribution due to a small number of heavy healthcare users. Different methods are available for modelling costs, such as generalized linear models (GLMs), extended estimating equations and latent class approaches. While there are tutorials addressing approaches to decision modelling, there is no practical guidance on the cost estimation to inform such models. Therefore, this tutorial aims to provide a general guidance on estimating healthcare costs associated with disease states in decision analytic models. Specifically, we present a step-by-step guide to how individual participant data can be used to estimate costs over discrete periods for participants with particular characteristics, based on the GLM framework. We focus on the practical aspects of cost modelling from the conceptualization of the research question to the derivation of costs for an individual in particular disease states. We provide a practical example with step-by-step R code illustrating the process of modelling the hospital costs associated with disease states for a cardiovascular disease model.

Strong and graded associations between level of asthma severity and all-cause hospital care use and costs in the UK.

BACKGROUND: Hospital admissions account for a large share of the healthcare costs incurred by people with asthma. We assessed the hospital care use and costs associated with asthma severity using the UK Biobank cohort and linked healthcare data. METHODS: Adult participants with asthma at recruitment were classified using their prescription data into mild and moderate-to-severe asthma and matched separately to asthma-free controls by age, sex, ethnicity and location. The associations of asthma, by severity, with the annual number of all-cause hospital admissions, days spent in hospital and hospital costs were estimated over a 10-year follow-up period using three specifications of negative binomial regression models that differed according to the sociodemographic and clinical characteristics adjusted for. RESULTS: Of the 25 031 participants with active asthma, 80% had mild asthma and 20% had moderate-to-severe asthma. Compared with participants with mild asthma, those with moderate-to-severe asthma were on average 2.7 years older, more likely to be current (13.7% vs 10.4%) or previous (40.2% vs 35.2%) smokers, to have a higher body mass index (BMI), and to be suffering from a variety of comorbid diseases. Following adjustments for age, sex, ethnicity and location, people with mild asthma experienced on average 36% more admissions (95% CI 28% to 40%), 43% more days in hospital (95% CI 35% to 51%) and 36% higher hospital costs (95% CI 31% to 41%) annually than asthma-free individuals, while people with moderate-to-severe asthma experienced excesses of 93% (95% CI 81% to 107%), 142% (95% CI 124% to 162%) and 98% (95% CI 88% to 108%), respectively. Further adjustments for socioeconomic deprivation, smoking status, BMI and comorbidities resulted in smaller though still highly significant positive associations, graded by severity, between asthma and hospital use and costs. CONCLUSIONS: Strong graded associations are reported between asthma severity and the extent of hospital use and costs in the UK. These findings could inform future assessments of the value of asthma management interventions.

Prediction Models for Individual-Level Healthcare Costs Associated with Cardiovascular Events in the UK.

OBJECTIVES: The aim of this study was to develop prediction models for the individual-level impacts of cardiovascular events on UK healthcare costs. METHODS: In the UK Biobank, people 40-70 years old, recruited in 2006-2010, were followed in linked primary (N = 192,983 individuals) and hospital care (N = 501,807 individuals) datasets. Regression models of annual primary and annual hospital care costs (2020 UK£) associated with individual characteristics and experiences of myocardial infarction (MI), stroke, coronary revascularization, incident diabetes mellitus and cancer, and vascular and nonvascular death are reported. RESULTS: For both people without and with previous cardiovascular disease (CVD), primary care costs were modelled using one-part generalised linear models (GLMs) with identity link and Poisson distribution, and hospital costs with two-part models (part 1: logistic regression models the probability of incurring costs; part 2: GLM with identity link and Poisson distribution models the costs conditional on incurring any). In people without previous CVD, mean annual primary and hospital care costs were £360 and £514, respectively. The excess primary care costs were £190 and £360 following MI and stroke, respectively, whereas excess hospital costs decreased from £4340 and £5590, respectively, in the year of these events, to £190 and £410 two years later. People with previous CVD had more than twice higher annual costs, and incurred higher excess costs for cardiovascular events. Other characteristics associated with higher costs included older age, female sex, south Asian ethnicity, higher socioeconomic deprivation, smoking, lower level of physical activities, unhealthy body mass index, and comorbidities. CONCLUSIONS: These individual-level healthcare cost prediction models could inform assessments of the value of health technologies and policies to reduce cardiovascular and other disease risks and healthcare costs. An accompanying Excel calculator is available to facilitate the use of the models.

Analysing the impact of private health insurance on inequities in health care utilization: a longitudinal study from China.

Since the early 2000s, Chinese government has sought to encourage the growth of private health insurance (PHI) while simultaneously expanding the breadth of coverage in its social health insurance (SHI) system. This paper examines how the prevalence of PHI has changed during this period and the extent to which PHI contributed to the growth of horizontal and geographical inequities with a focus on healthcare utilization. National data from China Health and Nutrition Survey between 2000 and 2015 were analysed using a multilevel modelling approach. The analysis investigated the impact of SHI membership as related to PHI uptake, PHI enrolees' utilization of health services and out-of-pocket (OOP) expenses. This study found being covered by an SHI scheme reduced the uptake of PHI between 2004 and 2015. Having PHI caused an increase in utilizing outpatient care but did not affect OOP expenses. Coverage prevalence of PHI in a residential community was positively associated with the average level of healthcare utilization. Coverage prevalence of PHI and its effects on healthcare utilization varied geographically. The findings suggest that expanding the role of PHI was not effective without clear support from government policy. Furthermore, the expansion of PHI may cause an increase in horizontal and geographical inequities in healthcare utilization.

Health insurance enrollment strategies during the Affordable Care Act (ACA): a scoping review on what worked and for whom.

BACKGROUND: The Affordable Care Act (ACA) provided an opportunity for millions of people in the U.S. to get coverage from the publicly funded Medicaid program or private insurance from the newly established marketplace. However, enrolling millions of people for health insurance was an enormous task. The aim of this review was to examine the strategies used to enroll people for health insurance and their effectiveness after implementing the ACA's coverage expansion. METHODS: The PRISMA Extension for Scoping Review (PRISMA-ScR) guided this review. Included studies were empirical studies that met the inclusion criteria and published between 2010 and 2020. Studies were searched mainly from two scholarly databases, CINAHL Plus and Medline (PubMed) using keyword searches. Hand searches from the references of selected journals were also performed. Content analysis was conducted by two authors in which codes were inductively developed to identify themes. RESULTS: There were 2213 potential studies identified from the search, but 10 met the inclusion criteria. The research design of the studies varied. Two studies were randomized trials, one quasi-experimental trial, three mixed-methods, two qualitative and two quantitative. All studies focused on strategies used to inform and help people enroll for either Medicaid or private insurance from the marketplace. This review identified three key strategies used to help enroll people for coverage: 1) individual assistance; 2) community outreach; and 3) health education and promotion (HE&P). CONCLUSION: Community-based organizations were likely to use a combination of the three strategies simultaneously to reach uninsured individuals and directly help them enroll for health insurance. Other organizations that aimed to reach a wider segment of the population used single strategies, such as community outreach or HE&P.

Gaps in antihypertensive and statin treatments and benefits of optimisation: a modelling study in a 1 million ethnically diverse urban population in UK.

OBJECTIVES: To characterise gaps in antihypertensive treatment in people with hypertension and statin treatment in people with cardiovascular diseases (CVD) in a large urban population and quantify the health and economic impacts of their optimisation. DESIGN: A cross-sectional population study and a long-term CVD decision model. SETTING: Primary care, UK. PARTICIPANTS: All adults with diagnosed hypertension or CVD in a population of about 1 million people, served by 123 primary care practices in London, UK in 2019. INTERVENTIONS: Following UK clinical guidelines, all adults with diagnosed hypertension were categorised into optimal, suboptimal and untreated groups with respect to their antihypertensive treatment, and all adults with diagnosed CVD were categorised in the same manner with respect to their statin treatment. OUTCOMES: Proportion of patients suboptimally treated or untreated. Projected cardiovascular events avoided, years and quality-adjusted life years (QALYs) gained and healthcare costs saved with optimised treatments. RESULTS: 21 954 of the 91 828 adults with hypertension (24%; mean age 59 years; 49% women) and 9062 of the 23 723 adults with CVD (38%; mean age 69 years; 43% women) were not optimally treated with antihypertensive or statin treatment, respectively. Per 1000 additional patients optimised over 5 years, hypertension treatment is projected to prevent 25 (95% CI 16 to 32) major vascular events (MVEs) and 7 (3 to 10) vascular deaths, statin treatment, 28 (22 to 33) MVEs and 6 (4 to 7) vascular deaths. Over their lifespan, a patient with uncontrolled hypertension aged 60-69 years is projected to gain 0.64 (95% CI 0.36 to 0.87) QALYs with optimised hypertension treatment, and a similarly aged patient with previous CVD not optimally treated with statin is projected to gain 0.3 (0.24 to 0.37) QALYs with optimised statin treatment. In both cases, the hospital cost savings minus extra medication costs were about £1100 per person over remaining lifespan. CONCLUSIONS: Optimising cardiovascular treatments can cost-effectively reduce cardiovascular risk and improve life expectancy.

The Effects of Private Health Insurance on Universal Health Coverage Objectives in China: A Systematic Literature Review.

BACKGROUND: We conducted a systematic review on the role of private health insurance to complement the social health insurance system towards achieving universal health coverage in China. This review presents the impacts of private health insurance on expanding coverage, increasing access to healthcare, and financial protection. METHODS: A systematic review was conducted by searching peer-reviewed articles published between January 2000 and March 2018 in Web of Science, PubMed, and China Knowledge Resource Integrated Database. The search terms included coverage prevalence, access and financial protection related to private health insurance in China. A total of 31 studies were selected. RESULTS: Coverage prevalence of private health insurance gradually increased but it was unequally distributed across regions and populations. The expansion of social health insurance has enhanced the total aggregate premium of private health insurance but has had a mixed impact on the take-up of private health insurance. Private insurance beneficiaries were found to limit their utilisation of healthcare services and there was no evidence that it ensured financial protection. CONCLUSION: The role of private health insurance (PHI) in extending universal health coverage in China was limited and therefore should not be overstated.

Trait Anxiety and Economic Risk Avoidance Are Not Necessarily Associated: Evidence from the Framing Effect.

According to previous literature, trait anxiety is related to the tendency to choose safety options during risk decision-making, that is, risk avoidance. In our opinion, anxious people's risk preference might actually reflect their hypersensitivity to emotional information. To examine this hypothesis, a decision-making task that could elicit the framing effect was employed. The framing effect indicates that risk preference could be modulated by emotional messages contained in the description (i.e., frame) of options. The behavioral results have showed the classic framing effect. In addition, individual level of trait anxiety was positively correlated with the framing effect size. However, trait anxiety was not correlated with risk-avoidance ratio in any condition. Finally, the relationship between anxiety and the framing effect remained significant after the level of depression was also taken into account. The theoretical significance and the major limitations of this study are discussed.

Neural basis of emotional decision making in trait anxiety.

Although trait anxiety has been associated with risk decision making, whether it is related to risk per se or to the feeling of the risk, as well as the underlying neurocognitive mechanisms, remains unclear. Using a decision-making task with a manipulation of frame (i.e., written description of options as a potential gain or loss) and functional magnetic resonance imaging, we investigated the neurocognitive relationship between trait anxiety and decision making. The classic framing effect was observed: participants chose the safe option when it was described as a potential gain, but they avoided the same option when it was described as a potential loss. Most importantly, trait anxiety was positively correlated with this behavioral bias. Trait anxiety was also positively correlated with amygdala-based "emotional" system activation and its coupling with the ventromedial prefrontal cortex (vmPFC) when decisions were consistent with the framing effect, but negatively correlated with the dorsal anterior cingulate cortex (dACC)-based "analytic" system activation and its connectivity to the vmPFC when decisions ran counter to the framing effect. Our findings suggest that trait anxiety is not associated with subjective risk preference but an evaluative bias of emotional information in decision making, underpinned by a hyperactive emotional system and a hypoactive analytic system in the brain.

Synergism and rules from combination of Baicalin, Jasminoidin and Desoxycholic acid in refined Qing Kai Ling for treat ischemic stroke mice model.

Refined Qing-Kai-Ling (QKL), a modified Chinese medicine, consists of three main ingredients (Baicalin, Jasminoidin and Desoxycholic acid), plays a synergistic effect on the treatment of the acute stage of ischemic stroke. However, the rules of the combination and synergism are still unknown. Based on the ischemic stroke mice model, all different kinds of combination of Baicalin, Jasminoidin, and Desoxycholic acid were investigated by the methods of neurological examination, microarray, and genomics analysis. As a result, it confirmed that the combination of three drugs offered a better therapeutical effect on ischemic stroke than monotherapy of each drug. Additionally, we used Ingenuity pathway Analysis (IPA) and principal component analysis (PCA) to extract the dominant information of expression changes in 373 ischemia-related genes. The results suggested that 5 principal components (PC1-5) could account for more than 95% energy in the gene data. Moreover, 3 clusters (PC1, PC2+PC5, and PC3+PC4) were addressed with cluster analysis. Furthermore, we matched PCs on the drug-target networks, the findings demonstrated that Baicalin related with PC1 that played the leading role in the combination; Jasminoidin related with PC2+PC5 that played a compensatory role; while Desoxycholic acid had the least performance alone which could relate with PC3+PC4 that played a compatible role. These manifestations were accorded with the principle of herbal formulae of Traditional Chinese Medicine (TCM), emperor-minister-adjuvant-courier. In conclusion, we firstly provided scientific evidence to the classic theory of TCM formulae, an initiating holistic viewpoint of combination therapy of TCM. This study also illustrated that PCA might be an applicable method to analyze the complicated data of drug combination.

Baicalin administration is effective in positive regulation of twenty-four ischemia/reperfusion-related proteins identified by a proteomic study.

Baicalin is a major plant polyphenolic compound derived from the dried root of Scutellaria baicalensis Georgi, a Traditional Chinese Medicine material. The current study applied proteomics to investigate the different protein expression modes in mice brains after middle cerebral artery occlusion (MCAO) with or without administration of baicalin. Twenty-four proteins which had a 3-fold change in abundance compared to the sham control sample were selected to be identified. Statistical analysis demonstrated that there was no significant difference in expression between the twenty-four proteins baicalin-treated MCAO group and the sham-operation group (n=24, p=0.102). Gene Ontology analysis linked these proteins to fifteen biological processes, including cellular process, developmental process and biological regulation. Results indicated that baicalin performed well in regulating proteins in energy metabolism but had a relatively weak effect in the regulation of proteins in neurogenesis and apoptosis. In sum, our findings suggest baicalin may be a potential therapeutic agent in treating stroke and may also be a strong candidate for future research in its actions on individual proteins.