A cardiovascular disease policy model that predicts life expectancy taking into account socioeconomic deprivation

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.

Development and Validation of the US Diabetes, Obesity, Cardiovascular Disease Microsimulation (DOC-M) Model: Health Disparity and Economic Impact Model

BACKGROUND

Few simulation models have incorporated the interplay of diabetes, obesity, and cardiovascular disease (CVD); their upstream lifestyle and biological risk factors; and their downstream effects on health disparities and economic consequences.

METHODS

We developed and validated a US Diabetes, Obesity, Cardiovascular Disease Microsimulation (DOC-M) model that incorporates demographic, clinical, and lifestyle risk factors to jointly predict overall and racial-ethnic groups-specific obesity, diabetes, CVD, and cause-specific mortality for the US adult population aged 40 to 79 y at baseline. An individualized health care cost prediction model was further developed and integrated. This model incorporates nationally representative data on baseline demographics, lifestyle, health, and cause-specific mortality; dynamic changes in modifiable risk factors over time; and parameter uncertainty using probabilistic distributions. Validation analyses included assessment of 1) population-level risk calibration and 2) individual-level risk discrimination. To illustrate the application of the DOC-M model, we evaluated the long-term cost-effectiveness of a national produce prescription program.

RESULTS

Comparing the 15-y model-predicted population risk of primary outcomes among the 2001-2002 National Health and Nutrition Examination Survey (NHANES) cohort with the observed prevalence from age-matched cross-sectional 2003-2016 NHANES cohorts, calibration performance was strong based on observed-to-expected ratio and calibration plot analysis. In most cases, Brier scores fell below 0.0004, indicating a low overall prediction error. Using the Multi-Ethnic Study of Atherosclerosis cohorts, the c-statistics for assessing individual-level risk discrimination were 0.85 to 0.88 for diabetes, 0.93 to 0.95 for obesity, 0.74 to 0.76 for CVD history, and 0.78 to 0.81 for all-cause mortality, both overall and in three racial-ethnic groups. Open-source code for the model was posted at https://github.com/food-price/DOC-M-Model-Development-and-Validation.

CONCLUSIONS

The validated DOC-M model can be used to examine health, equity, and the economic impact of health policies and interventions on behavioral and clinical risk factors for obesity, diabetes, and CVD.

HIGHLIGHTS

We developed a novel microsimula'tion model for obesity, diabetes, and CVD, which intersect together and - critically for prevention and treatment interventions - share common lifestyle, biologic, and demographic risk factors.Validation analyses, including assessment of (1) population-level risk calibration and (2) individual-level risk discrimination, showed strong performance across the overall population and three major racial-ethnic groups for 6 outcomes (obesity, diabetes, CVD, and all-cause mortality, CVD- and DM-cause mortality)This paper provides a thorough explanation and documentation of the development and validation process of a novel microsimulation model, along with the open-source code (https://github.com/food-price/ DOCM_validation) for public use, to serve as a guide for future simulation model assessments, validation, and implementation.

Alternative cascade-testing protocols for identifying and managing patients with familial hypercholesterolaemia: systematic reviews, qualitative study and cost-effectiveness analysis

Background

Cascade testing the relatives of people with familial hypercholesterolaemia is an efficient approach to identifying familial hypercholesterolaemia. The cascade-testing protocol starts with identifying an index patient with familial hypercholesterolaemia, followed by one of three approaches to contact other relatives: indirect approach, whereby index patients contact their relatives; direct approach, whereby the specialist contacts the relatives; or a combination of both direct and indirect approaches. However, it is unclear which protocol may be most effective.

Objectives

The objectives were to determine the yield of cases from different cascade-testing protocols, treatment patterns, and short- and long-term outcomes for people with familial hypercholesterolaemia; to evaluate the cost-effectiveness of alternative protocols for familial hypercholesterolaemia cascade testing; and to qualitatively assess the acceptability of different cascade-testing protocols to individuals and families with familial hypercholesterolaemia, and to health-care providers.

Design and methods

This study comprised systematic reviews and analysis of three data sets: PASS (PASS Software, Rijswijk, the Netherlands) hospital familial hypercholesterolaemia databases, the Clinical Practice Research Datalink (CPRD)-Hospital Episode Statistics (HES) linked primary-secondary care data set, and a specialist familial hypercholesterolaemia register. Cost-effectiveness modelling, incorporating preceding analyses, was undertaken. Acceptability was examined in interviews with patients, relatives and health-care professionals.

Result

Systematic review of protocols: based on data from 4 of the 24 studies, the combined approach led to a slightly higher yield of relatives tested [40%, 95% confidence interval (CI) 37% to 42%] than the direct (33%, 95% CI 28% to 39%) or indirect approaches alone (34%, 95% CI 30% to 37%). The PASS databases identified that those contacted directly were more likely to complete cascade testing (p < 0.01); the CPRD-HES data set indicated that 70% did not achieve target treatment levels, and demonstrated increased cardiovascular disease risk among these individuals, compared with controls (hazard ratio 9.14, 95% CI 8.55 to 9.76). The specialist familial hypercholesterolaemia register confirmed excessive cardiovascular morbidity (standardised morbidity ratio 7.17, 95% CI 6.79 to 7.56). Cost-effectiveness modelling found a net health gain from diagnosis of -0.27 to 2.51 quality-adjusted life-years at the willingness-to-pay threshold of £15,000 per quality-adjusted life-year gained. The cost-effective protocols cascaded from genetically confirmed index cases by contacting first- and second-degree relatives simultaneously and directly. Interviews found a service-led direct-contact approach was more reliable, but combining direct and indirect approaches, guided by index patients and family relationships, may be more acceptable.

Limitations

Systematic reviews were not used in the economic analysis, as relevant studies were lacking or of poor quality. As only a proportion of those with primary care-coded familial hypercholesterolaemia are likely to actually have familial hypercholesterolaemia, CPRD analyses are likely to underestimate the true effect. The cost-effectiveness analysis required assumptions related to the long-term cardiovascular disease risk, the effect of treatment on cholesterol and the generalisability of estimates from the data sets. Interview recruitment was limited to white English-speaking participants.

Conclusions

Based on limited evidence, most cost-effective cascade-testing protocols, diagnosing most relatives, select index cases by genetic testing, with services directly contacting relatives, and contacting second-degree relatives even if first-degree relatives have not been tested. Combined approaches to contact relatives may be more suitable for some families.

Future work

Establish a long-term familial hypercholesterolaemia cohort, measuring cholesterol levels, treatment and cardiovascular outcomes. Conduct a randomised study comparing different approaches to contact relatives.

Study registration

This study is registered as PROSPERO CRD42018117445 and CRD42019125775.

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 27, No. 16. See the NIHR Journals Library website for further project information.

How does cholesterol burden change the case for investing in familial hypercholesterolaemia? A cost-effectiveness analysis

BACKGROUND AND AIMS

This study aimed to ascertain how the long-term benefits and costs of diagnosis and treatment of familial hypercholesterolaemia (FH) vary by prognostic factors and 'cholesterol burden', which is the effect of long-term exposure to low-density lipoprotein cholesterol (LDL-C) on cardiovascular disease (CVD) risk.

METHODS

A new cost-effectiveness model was developed from the perspective of the UK National Health Service (NHS), informed by routine data from individuals with FH. The primary outcome was net health gain (i.e., health benefits net of the losses due to costs), expressed in quality-adjusted life years (QALYs) at the £15,000/QALY threshold. Prognostic factors included pre-treatment LDL-C, age, gender, and CVD history.

RESULTS

If cholesterol burden is considered, diagnosis resulted in positive net health gain (i.e., it is cost-effective) in all individuals with pre-treatment LDL-C ≥ 4 mmol/L, and in those with pre-treatment LDL-C ≥ 2 mmol/L aged ≥50 years or who have CVD history. If cholesterol burden is not considered, diagnosis resulted in lower net health gain, but still positive in children aged 10 years with pre-treatment LDL-C ≥ 6 mmol/L and adults aged 30 years with pre-treatment LDL-C ≥ 4 mmol/L.

CONCLUSIONS

Diagnosis and treatment of most people with FH results in large net health gains, particularly in those with higher pre-treatment LDL-C. Economic evaluations of FH interventions should consider the sensitivity of the study conclusions to cholesterol burden, particularly where interventions target younger patients, and explicitly consider prognostic factors such as pre-treatment LDL-C, age, and CVD history.

Beyond Ten-Year Risk: A Cost-Effectiveness Analysis of Statins for the Primary Prevention of Cardiovascular Disease

Cholesterol guidelines typically prioritize primary prevention statin therapy on the basis of 10-year risk of cardiovascular disease. The advent of generic pricing may justify expansion of statin eligibility. Moreover, 10-year risk may not be the optimal approach for statin prioritization. We estimated the cost-effectiveness of expanding preventive statin eligibility and evaluated novel approaches to prioritization from a Scottish health sector perspective.

From Spreadsheets to Script: Experiences From Converting a Scottish Cardiovascular Disease Policy Model into R

Given the advantages in transparency, reproducibility, adaptability and computational efficiency in R, there is a growing interest in converting existing spreadsheet-based models into an R script for model re-use and upskilling training among health economic modellers. The objective of this exercise was to convert the Scottish Cardiovascular Disease (CVD) Policy Model from Excel to R and discuss the lessons learnt throughout this process. The CVD model is a competing risk state transition cohort model. Four health economists, with varied experience of R, attempted to replicate an identical model structure in R based on the model in Excel and reproduce the intermediate and final results. Replications varied in their use of specialist health economics packages in addition to standard data management packages. Two versions of the CVD model were created in R along with a Shiny app. Version 1 was developed without health economics specialist packages and produced identical results to the Excel version. Version 2 used the heemod package and did not achieve the same results, possibly due to the non-standard elements of the model and limited time to adapt the functions. The R model requires less than half the computational time than the Excel model. Conversion of the spreadsheet models to script models is feasible for health economists. A step-by-step guide for the conversion process is provided and modellers' experience is discussed. Coding without specialist packages allows full flexibility, while specialist packages may add convenience if the model structure is suitable. Whichever approach is taken, transparency and replicability remain the key criteria in model programming. Model conversions must maintain standards in these areas regardless of the choice of software.

Health care utilisation and costs associated with different treatment protocols for newly diagnosed childhood acute lymphoblastic leukaemia: A population-based study in Ontario, Canada

BACKGROUND

Although different treatment protocols for childhood acute lymphoblastic leukaemia (ALL) all achieve high cure rates, their health care utilisation and costs have not been rigorously compared.

METHODS

Disease, treatment, and outcome data were chart abstracted for all children with ALL in Ontario, Canada, diagnosed 2002-2012. Linkage to population-based databases identified health care utilisation. Utilisation-associated costs were determined through validated algorithms. Chemotherapy-associated costs were calculated separately. Health care utilisation and costs were compared between patients receiving Children's Oncology Group (COG) versus Dana-Farber Cancer Institute (DFCI)-based treatment.

FINDINGS

Of 802 patients, 146 (18.2%) were treated on DFCI-based protocols. COG patients experienced significantly higher rates of emergency department (ED) visits (adjusted rate ratio [aRR]: 1.3, 95% confidence interval [CI]: 1.1-1.5; p = 0·01), whereas outpatient visit rates were 60% higher among DFCI patients (aRR: 1.6, 95% CI: 1.5-1.7, p < 0.0001). In adjusted analyses, DFCI-associated cost intensity was 70% higher (aRR: 1.7, 95% CI: 1.5-1.9; p < 0.0001), mainly attributable to outpatient visit costs. Total chemotherapy costs were higher among COG-treated patients ($39,400 ± $1100 versus $33,400 ± $2800; p = 0.02). Among PEG-ASNase-treated patients, total chemotherapy costs were highest among DFCI patients (median $54,200 ± $7400; p = 0.003 versus COG patients).

INTERPRETATION

COG and DFCI treatments were associated with higher ED visit rates and higher outpatient visit rates, respectively. Overall utilisation-associated costs were increased in DFCI-treated patients. Administration of some intravenous chemotherapy at home and decreases in PEG-ASNase cost would decrease health care utilisation and costs for all patients and mitigate differences between COG and DFCI protocols.

FUNDING

C¹⁷ Research Network.

Risk of fatal and nonfatal coronary heart disease and stroke events among adult patients with hypertension: basic Markov model inputs for evaluating cost-effectiveness of hypertension treatment: systematic review of cohort studies

Objectives

Hypertension is a risk factor for a number of vascular and cardiac complications. A Markov like simulation based on cardiovascular disease (CVD) policy model is being used for evaluating cost-effectiveness of hypertension treatment. Stroke, angina, myocardial infarction (MI), cardiac arrest and all-cause mortality were only included CVD outcome variables in the model. Therefore this systematic review was conducted to evaluate completeness of CVD policy model for evaluation of cost-effectiveness across different regions.

Key findings

Fourteen cohort studies involving a total of 1 674 773 hypertensive adult population and 499 226 adults with treatment resistant hypertension were included in this systematic review. Hypertension is clearly associated with coronary heart disease (CHD) and stroke mortality, unstable angina, stable angina, MI, heart failure (HF), sudden cardiac death, transient ischemic attack, ischemic stroke, sub-arachnoid hemorrhage, intracranial hemorrhage, peripheral arterial disease (PAD), and abdominal aortic aneurism (AAA). Lifetime risk of developing HF is higher among hypertensives across all ages, with slight variation among regions. Treatment resistant hypertension is associated with higher relative risk of developing major CVD events and mortality when compared with the non-resistant hypertension.

Summary

The CVD policy model can be used in most of the regions for evaluation of cost-effectiveness of hypertension treatment. However, hypertension is highly associated with HF in Latin America, Eastern Europe, and Sub-Saharan Africa. Therefore, it is important to consider HF in CVD policy model for evaluating cost-effectiveness of hypertension treatment in these regions. We do not suggest the inclusion of PAD and AAA in CVD policy model for evaluating cost-effectiveness of hypertension treatment due to lack of sufficient evidence. Researchers should consider the effect of treatment resistant hypertension either through including in the basic model or during setting the model assumptions.

Age at Diagnosis of Type 2 Diabetes Mellitus and Associations With Cardiovascular and Mortality Risks

BACKGROUND

Risk of cardiovascular disease (CVD) and mortality for patients with versus without type 2 diabetes mellitus (T2DM) appears to vary by the age at T2DM diagnosis, but few population studies have analyzed mortality and CVD outcomes associations across the full age range.

METHODS

With use of the Swedish National Diabetes Registry, everyone with T2DM registered in the Registry between 1998 and 2012 was included. Controls were randomly selected from the general population matched for age, sex, and county. The analysis cohort comprised 318 083 patients with T2DM matched with just <1.6 million controls. Participants were followed from 1998 to 2013 for CVD outcomes and to 2014 for mortality. Outcomes of interest were total mortality, cardiovascular mortality, noncardiovascular mortality, coronary heart disease, acute myocardial infarction, stroke, heart failure, and atrial fibrillation. We also examined life expectancy by age at diagnosis. We conducted the primary analyses using Cox proportional hazards models in those with no previous CVD and repeated the work in the entire cohort.

RESULTS

Over a median follow-up period of 5.63 years, patients with T2DM diagnosed at ≤40 years had the highest excess risk for most outcomes relative to controls with adjusted hazard ratio (95% CI) of 2.05 (1.81-2.33) for total mortality, 2.72 (2.13-3.48) for cardiovascular-related mortality, 1.95 (1.68-2.25) for noncardiovascular mortality, 4.77 (3.86-5.89) for heart failure, and 4.33 (3.82-4.91) for coronary heart disease. All risks attenuated progressively with each increasing decade at diagnostic age; by the time T2DM was diagnosed at >80 years, the adjusted hazard ratios for CVD and non-CVD mortality were <1, with excess risks for other CVD outcomes substantially attenuated. Moreover, survival in those diagnosed beyond 80 was the same as controls, whereas it was more than a decade less when T2DM was diagnosed in adolescence. Finally, hazard ratios for most outcomes were numerically greater in younger women with T2DM.

CONCLUSIONS

Age at diagnosis of T2DM is prognostically important for survival and cardiovascular risks, with implications for determining the timing and intensity of risk factor interventions for clinical decision making and for guideline-directed care. These observations amplify support for preventing/delaying T2DM onset in younger individuals.

How Does Preterm Delivery Contribute to the Increased Burden of Cardiovascular Disease? Quantifying the Economic Impact of Cardiovascular Disease in Women with a History of Preterm Delivery

Background: The association between preterm delivery (PTD) and maternal risk of cardiovascular disease (CVD) was demonstrated, but the economic burden of CVD in these women was unknown. Methods: A Markov microsimulation model, comprising no event, postacute coronary event (ACE, including acute myocardial infarction and unstable angina), poststroke, post-ACE and stroke, postheart failure, and death, was constructed to quantify the CVD burden in women with PTD from 2017 to 2066 using the Australian health care system perspective. Both first-ever and recurrent CVD events were accounted for in the model. Population with PTD histories was sourced from Australian Bureau of Statistics and costs of acute hospitalization and long-term management from government websites. Nonmonetary burden as years of life lost (YLL) was compared between women with and without PTD histories. Both dynamic (i.e., new cohort added every cycle) and static (i.e., population was stabilized) approaches were used to measure the CVD burden, with sensitivity analyses examining the robustness of results. Results: The dynamic model showed the total CVD burden caused by PTD as AUD11.4 billion for the next 50 years and the YLL as 0.34/capita, while the static model generated a cost of AUD4.5 billion and the YLL as 0.52/capita. Long-term management cost was the primary cost determinant (AUD9.4 billion and AUD3.7 billion, respectively) in the two models, with the results most sensitive to the discount rate and time horizon. Conclusions: Considering the substantial economic burden, recognizing PTD as a potential risk factor and encouraging women with PTD histories to participate in primary prevention programs would potentially curb the ever-increasing CVD burden.

Transparency in Decision Modelling: What, Why, Who and How?

Transparency in decision modelling is an evolving concept. Recently, discussion has moved from reporting standards to open-source implementation of decision analytic models. However, in the debate about the supposed advantages and disadvantages of greater transparency, there is a lack of definition. The purpose of this article is not to present a case for or against transparency, but rather to provide a more nuanced understanding of what transparency means in the context of decision modelling and how it could be addressed. To this end, we review and summarise the discourse to date, drawing on our collective experience. We outline a taxonomy of the different manifestations of transparency, including reporting standards, reference models, collaboration, model registration, peer review and open-source modelling. Further, we map out the role and incentives for the various stakeholders, including industry, research organisations, publishers and decision makers. We outline the anticipated advantages and disadvantages of greater transparency with respect to each manifestation, as well as the perceived barriers and facilitators to greater transparency. These are considered with respect to the different stakeholders and with reference to issues including intellectual property, legality, standards, quality assurance, code integrity, health technology assessment processes, incentives, funding, software, access and deployment options, data protection and stakeholder engagement. For each manifestation of transparency, we discuss the 'what', 'why', 'who' and 'how'. Specifically, their meaning, why the community might (or might not) wish to embrace them, whose engagement as stakeholders is required and how relevant objectives might be realised. We identify current initiatives aimed to improve transparency to exemplify efforts in current practice and for the future.

Linking agroecosystems producing farmed seafood with food security and health status to better address the nutritional challenges in Bangladesh

OBJECTIVE

Aquaculture is one of the fastest-growing food production sectors in many low-income and food-deficit countries with aquatic ecozones. Yet its specific impact on nutrition and livelihood in local communities, where commercial and/or export-orientated aquaculture activities are developed, is largely unknown.

DESIGN

The present narrative and argumentative review aims to provide an overview of our current understanding of the connections between aquaculture agroecosystems, local and national fish production, fish consumption patterns and nutrition and health outcomes.

RESULTS

The agroecological dynamic in a coastal-estuarine zone, where the aquatic environment ranges from fully saline to freshwater, is complex, with seasonal and annual fluctuations in freshwater supply creating a variable salinity gradient which impacts on aquatic food production and on food production more generally. The local communities living in these dynamic aquatic ecozones are vulnerable to poverty, poor diet and health, while these ecosystems produce highly valuable and nutritious aquatic foods. Policies addressing the specific challenges of risk management of these communities are limited by the sectoral separation of aquatic food production - the fisheries and aquaculture sector, the broader food sector - and public health institutions.

CONCLUSIONS

Here we provide an argument for the integration of these factors to improve aquaculture value chains to better address the nutritional challenges in Bangladesh.

Mechanical circulatory support for refractory cardiogenic shock post-acute myocardial infarction-a decade of lessons

Background

There are 0.9 catheterization labs per 100,000 inhabitants in Scotland for percutaneous coronary intervention (PCI) for acute myocardial infarction (AMI), which are much less accessible to patients in remote and rural areas. An uncommon but sinister sequalae following AMI is cardiogenic shock (CS) that could be refractory to inotropic support. CS complicates 5-15% of AMIs occurring in ST-segment elevation myocardial infarctions (STEMIs). Outcomes of CS are poor with mortalities of up to 90% reported in the literature in the absence of experienced care. We report our experience as the tertiary referral centre in Scotland for MCS and heart transplantation over 8 years.

Methods

A retrospective review of prospectively collected data was undertaken on all patients registered to the MCS service. The database was interrogated for patient demographics, type of mechanical circulatory support (MCS) and duration of MCS support, PCI-outcomes and survival to 30 days. A time-to-event analysis was performed using patient survival as the primary outcome measure.

Results

Twenty-three patients (16 male, 7 females) were included. The median age of the patients as 50 years (range, 45-56 years). VA-ECMO was the initial MCS of choice in 17 (73.9%) patients with BIVAD for 4 (17.4%) patients and LVAD for 2 (8.7%) patients. Thirty-day mortality was 21.8% in this cohort, however survival to discharge was 52.2%. Eleven (47.8%) patients recovered without the need for any further support, however only 9 (81.8%) patients in this subgroup survived to discharge. Three (13.0%) patients received a durable LVAD. In this subgroup, one patient was transplanted whereas two patients died due to complications while on support. The median length of in-hospital MCS support was 4 days. Median in-hospital stay was 27 days. Long-term follow up of up to 8 years demonstrates a high mortality beyond 30-day up to the first 6-month post MCS support.

Conclusions

MCS usage in these patients carries a high mortality in the early post-implantation period. However, there is a significant benefit to patients who survive the initial bridging period to recovery or destination therapy.

Brazilian Analytical Decision Model for Cardiovascular Disease: An Adaptation of the Scottish Cardiovascular Disease Policy Model

INTRODUCTION

Despite the significant impact of cardiovascular disease (CVD), there is not yet an analytical decision tool for assessing efficiency of interventions to prevent primary CVD events in Brazil. Therefore, we sought to adapt a Scottish CVD Policy Model to be used in the proposed population.

METHODS

Calibration consisted of identifying multiplicative factors for linear predictors of existing survival analysis models to produce predictions that closely match observed data (Life-table and Brazilian cohort study). Target data were life expectancy (LE) and cumulative incidence of coronary heart disease (CHD), cerebrovascular disease (CBVD), fatal CVD and fatal non-CVD. Root-Mean-Square-Error (RMSE) was used to estimate differences between predictions and observations. Acceptance criteria were defined as a fit of less than one year for LE and 1% for cumulative incidence. Male and female models were built separately.

RESULTS

The original model underestimated LE (RMSE=2.85 for men and 1.91 for women), CHD and CBVD for women (RMSE=0.044 and 0.041, respectively). The calibration process identified multiplicative factors to reach acceptance criteria for the four target data mentioned above (RMSE=0.61, 0.21, 0.016 and 0.017, respectively). Over prediction was identified only for CHD events in men (RMSE=0.031) being further calibrated (RMSE=0.008). All other target data met the acceptance criteria. Overall, the calibrated model predicts properly to individuals aging 35-80 years old, diabetics or not, smokers or not, with or without family history of CVD, and presenting at least one of the risk factors uncontrolled: Systolic Blood Pressure, Total Cholesterol or HDL-Cholesterol.

DISCUSSION

This is the first decision analytic model capable of assessing efficiency of interventions that prevent primary CVD events in Brazil. In future research, independent external validation should be carried out to corroborate the reliability of the model outputs.

Long-term weight loss following a randomised controlled trial of a weight management programme for men delivered through professional football clubs: the Football Fans in Training follow-up study

Background

Rising levels of obesity require interventions that support people in long-term weight loss. The Football Fans in Training (FFIT) programme uses loyalty to football teams to engage men in weight loss. In 2011/12, a randomised controlled trial (RCT) found that the FFIT programme was effective in helping men lose weight up to 12 months.

Objectives

To investigate the long-term weight, and other physical, behavioural and psychological outcomes up to 3.5 years after the start of the RCT; the predictors, mediators and men’s qualitative experiences of long-term weight loss; cost-effectiveness; and the potential for long-term follow-up via men’s medical records.

Design

A mixed-methods, longitudinal cohort study.

Setting

Thirteen professional Scottish football clubs from the RCT and 16 additional Scottish football clubs that delivered the FFIT programme in 2015/16.

Participants

A total of 665 men who were aged 35–65 years at the RCT baseline measures and who consented to follow-up after the RCT (intervention group, n = 316; comparison group, n = 349), and 511 men who took part in the 2015/16 deliveries of the FFIT programme.

Interventions

None as part of this study.

Main outcome measures

Objectively measured weight change from the RCT baseline to 3.5 years.

Results

In total, 488 out of 665 men (73.4%) attended 3.5-year measurements. Participants in the FFIT follow-up intervention group sustained a mean weight loss from baseline of 2.90 kg [95% confidence interval (CI) 1.78 to 4.02 kg; p < 0.001], and 32.2% (75/233) weighed ≥ 5% less than at baseline. Participants in the FFIT follow-up comparison group (who participated in routine deliveries of the FFIT programme after the RCT) lost a mean of 2.71 kg (95% CI 1.65 to 3.77 kg; p < 0.001), and 31.8% (81/255) achieved ≥ 5% weight loss. Both groups showed long-term improvements in body mass index, waist circumference, percentage body fat, blood pressure, self-reported physical activity (PA) (including walking), the consumption of fatty and sugary foods, fruit and vegetables and alcohol, portion sizes, self-esteem, positive and negative affect, and physical and mental health-related quality of life (HRQoL). Mediators included self-reported PA (including walking) and sitting time, the consumption of fatty and sugary foods and fruit and vegetables, portion sizes, self-esteem, positive affect, physical HRQoL, self-monitoring of weight, autonomous regulation, internal locus of control, perceived competence, and relatedness to other FFIT programme participants and family members. In qualitative interviews, men described continuing to self-monitor weight and PA. Many felt that PA was important for weight control, and walking remained popular; most were still aware of portion sizes and tried to eat fewer snacks. The FFIT programme was associated with an incremental cost-effectiveness of £10,700–15,300 per quality-adjusted life-year (QALY) gained at 3.5 years, and around £2000 per QALY gained in the lifetime analysis. Medical record linkage provided rich information about the clinical health outcomes of the FFIT RCT participants, and 90% of men (459/511) who took part in the 2015/16 FFIT programme gave permission for future linkage.

Conclusions

Participation in the FFIT programme under both research (during the FFIT RCT) and routine (after the FFIT RCT) delivery conditions led to significant long-term weight loss. Further research should investigate (1) how to design programmes to improve long-term weight loss maintenance, (2) longer-term follow-up of FFIT RCT participants and (3) very long-term follow-up via medical record linkage.

Trial registration

Current Controlled Trials ISRCTN32677491.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 6, No. 9. See the NIHR Journals Library website for further project information. The Scottish Executive Health Department Chief Scientist Office (CSO) funded the feasibility pilot that preceded the FFIT RCT (CZG/2/504). The Medical Research Council (MRC) funded Kate Hunt and additional developmental research through the MRC/CSO Social and Public Health Sciences Unit Gender and Health programme (5TK50/25605200-68094).

Modeling Clinical Outcomes in Prostate Cancer: Application and Validation of the Discrete Event Simulation Approach

OBJECTIVES

Treatment landscape in prostate cancer has changed dramatically with the emergence of new medicines in the past few years. The traditional survival partition model (SPM) cannot accurately predict long-term clinical outcomes because it is limited by its ability to capture the key consequences associated with this changing treatment paradigm. The objective of this study was to introduce and validate a discrete-event simulation (DES) model for prostate cancer.

METHODS

A DES model was developed to simulate overall survival (OS) and other clinical outcomes based on patient characteristics, treatment received, and disease progression history. We tested and validated this model with clinical trial data from the abiraterone acetate phase III trial (COU-AA-302). The model was constructed with interim data (55% death) and validated with the final data (96% death). Predicted OS values were also compared with those from the SPM.

RESULTS

The DES model's predicted time to chemotherapy and OS are highly consistent with the final observed data. The model accurately predicts the OS hazard ratio from the final data cut (predicted: 0.74; 95% confidence interval [CI] 0.64-0.85 and final actual: 0.74; 95% CI 0.6-0.88). The log-rank test to compare the observed and predicted OS curves indicated no statistically significant difference between observed and predicted curves. However, the predictions from the SPM based on interim data deviated significantly from the final data.

CONCLUSIONS

Our study showed that a DES model with properly developed risk equations presents considerable improvements to the more traditional SPM in flexibility and predictive accuracy of long-term outcomes.

Using nationwide ‘big data’ from linked electronic health records to help improve outcomes in cardiovascular diseases: 33 studies using methods from epidemiology, informatics, economics and social science in the ClinicAl disease research using LInked Bespoke studies and Electronic health Records (CALIBER) programme

Background

Electronic health records (EHRs), when linked across primary and secondary care and curated for research use, have the potential to improve our understanding of care quality and outcomes.

Objective

To evaluate new opportunities arising from linked EHRs for improving quality of care and outcomes for patients at risk of or with coronary disease across the patient journey.

Design

Epidemiological cohort, health informatics, health economics and ethnographic approaches were used.

Setting

230 NHS hospitals and 226 general practices in England and Wales.

Participants

Up to 2 million initially healthy adults, 100,000 people with stable coronary artery disease (SCAD) and up to 300,000 patients with acute coronary syndrome.

Main outcome measures

Quality of care, fatal and non-fatal cardiovascular disease (CVD) events.

Data platform and methods

We created a novel research platform [ClinicAl disease research using LInked Bespoke studies and Electronic health Records (CALIBER)] based on linkage of four major sources of EHR data in primary care and national registries. We carried out 33 complementary studies within the CALIBER framework. We developed a web-based clinical decision support system (CDSS) in hospital chest pain clinics. We established a novel consented prognostic clinical cohort of SCAD patients.

Results

CALIBER was successfully established as a valid research platform based on linked EHR data in nearly 2 million adults with > 600 EHR phenotypes implemented on the web portal (seehttps://caliberresearch.org/portal). Despite national guidance, key opportunities for investigation and treatment were missed across the patient journey, resulting in a worse prognosis for patients in the UK compared with patients in health systems in other countries. Our novel, contemporary, high-resolution studies showed heterogeneous associations for CVD risk factors across CVDs. The CDSS did not alter the decision-making behaviour of clinicians in chest pain clinics. Prognostic models using real-world data validly discriminated risk of death and events, and were used in cost-effectiveness decision models.

Conclusions

Emerging ‘big data’ opportunities arising from the linkage of records at different stages of a patient’s journey are vital to the generation of actionable insights into the diagnosis, risk stratification and cost-effective treatment of people at risk of, or with, CVD.

Future work

The vast majority of NHS data remain inaccessible to research and this hampers efforts to improve efficiency and quality of care and to drive innovation. We propose three priority directions for further research. First, there is an urgent need to ‘unlock’ more detailed data within hospitals for the scale of the UK’s 65 million population. Second, there is a need for scaled approaches to using EHRs to design and carry out trials, and interpret the implementation of trial results. Third, large-scale, disease agnostic genetic and biological collections linked to such EHRs are required in order to deliver precision medicine and to innovate discovery.

Study registration

CALIBER studies are registered as follows: study 2 – NCT01569139, study 4 – NCT02176174 and NCT01164371, study 5 – NCT01163513, studies 6 and 7 – NCT01804439, study 8 – NCT02285322, and studies 26–29 – NCT01162187. Optimising the Management of Angina is registered as Current Controlled Trials ISRCTN54381840.

Funding

The National Institute for Health Research (NIHR) Programme Grants for Applied Research programme (RP-PG-0407-10314) (all 33 studies) and additional funding from the Wellcome Trust (study 1), Medical Research Council Partnership grant (study 3), Servier (study 16), NIHR Research Methods Fellowship funding (study 19) and NIHR Research for Patient Benefit (study 33).

You Only Die Once: Accounting for Multi-Attributable Mortality Risks in Multi-Disease Models for Health-Economic Analyses

Mortality rates in Markov models, as used in health economic studies, are often estimated from summary statistics that allow limited adjustment for confounders. If interventions are targeted at multiple diseases and/or risk factors, these mortality rates need to be combined in a single model. This requires them to be mutually adjusted to avoid ‘double counting’ of mortality. We present a mathematical modeling approach to describe the joint effect of mutually dependent risk factors and chronic diseases on mortality in a consistent manner. Most importantly, this approach explicitly allows the use of readily available external data sources. An additional advantage is that existing models can be smoothly expanded to encompass more diseases/risk factors. To illustrate the usefulness of this method and how it should be implemented, we present a health economic model that links risk factors for diseases to mortality from these diseases, and describe the causal chain running from these risk factors (e.g., obesity) through to the occurrence of disease (e.g., diabetes, CVD) and death. Our results suggest that these adjustment procedures may have a large impact on estimated mortality rates. An improper adjustment of the mortality rates could result in an underestimation of disease prevalence and, therefore, disease costs.

A cardiovascular disease policy model: part 2-preparing for economic evaluation and to assess health inequalities

Objectives

This is the second of the two papers introducing a cardiovascular disease (CVD) policy model. The first paper described the structure and statistical underpinning of the state-transition model, demonstrating how life expectancy estimates are generated for individuals defined by ASSIGN risk factors. This second paper describes how the model is prepared to undertake economic evaluation.

Design

To generate quality-adjusted life expectancy (QALE), the Scottish Health Survey was used to estimate background morbidity (health utilities) and the impact of CVD events (utility decrements). The SF-6D algorithm generated utilities and decrements were modelled using ordinary least squares (OLS). To generate lifetime hospital costs, the Scottish Heart Health Extended Cohort (SHHEC) was linked to the Scottish morbidity and death records (SMR) to cost each continuous inpatient stay (CIS). OLS and restricted cubic splines estimated annual costs before and after each of the first four events. A Kaplan-Meier sample average (KMSA) estimator was then used to weight expected health-related quality of life and costs by the probability of survival.

Results

The policy model predicts the change in QALE and lifetime hospital costs as a result of an intervention(s) modifying risk factors. Cost-effectiveness analysis and a full uncertainty analysis can be undertaken, including probabilistic sensitivity analysis. Notably, the impacts according to socioeconomic deprivation status can be made.

Conclusions

The policy model can conduct cost-effectiveness analysis and decision analysis to inform approaches to primary prevention, including individually targeted and population interventions, and to assess impacts on health inequalities.

Which Patients with Giant Cell Arteritis Will Develop Cardiovascular or Cerebrovascular Disease? A Clinical Practice Research Datalink Study

Objective.

To evaluate the risk of cerebrovascular disease and cardiovascular disease (CVD) in patients with giant cell arteritis (GCA), and to identify predictors.

Methods.

The UK Clinical Practice Research Datalink 1991–2010 was used for a parallel cohort study of 5827 patients with GCA and 37,090 age-, sex-, and location-matched controls. A multivariable competing risk model (non-cerebrovascular/CV-related death as the competing risk) determined the relative risk [subhazard ratio (SHR)] between patients with GCA compared with background controls for cerebrovascular disease, CVD, or either. Each cohort (GCA and controls) was then analyzed individually using the same multivariable model, with age and sex now present, to identify predictors of CVD or cerebrovascular disease.

Results.

Patients with GCA, compared with controls, had an increased risk SHR (95% CI) of cerebrovascular disease (1.45, 1.31–1.60), CVD (1.49, 1.37–1.62), or either (1.47, 1.37–1.57). In the GCA cohort, predictors of “cerebrovascular disease or CVD” included increasing age, > 80 years versus < 65 years (1.98, 1.62–2.42), male sex (1.20, 1.05–1.38), and socioeconomic status, most deprived quintile versus least deprived (1.34, 1.01–1.78). These predictors were also present within the non-GCA cohort.

Conclusion.

Patients with GCA are more likely to develop cerebrovascular disease or CVD than age-, sex-, and location-matched controls. In common with the non-GCA cohort, patients who are older, male, and from the most deprived compared with least deprived areas have a higher risk of cerebrovascular disease or CVD. Further work is needed to understand how this risk may be mediated by specific behavioral, social, and economic factors.

Using electronic health records to predict costs and outcomes in stable coronary artery disease

Objectives

To use electronic health records (EHR) to predict lifetime costs and health outcomes of patients with stable coronary artery disease (stable-CAD) stratified by their risk of future cardiovascular events, and to evaluate the cost-effectiveness of treatments targeted at these populations.

Methods

The analysis was based on 94 966 patients with stable-CAD in England between 2001 and 2010, identified in four prospectively collected, linked EHR sources. Markov modelling was used to estimate lifetime costs and quality-adjusted life years (QALYs) stratified by baseline cardiovascular risk.

Results

For the lowest risk tenth of patients with stable-CAD, predicted discounted remaining lifetime healthcare costs and QALYs were £62 210 (95% CI £33 724 to £90 043) and 12.0 (95% CI 11.5 to 12.5) years, respectively. For the highest risk tenth of the population, the equivalent costs and QALYs were £35 549 (95% CI £31 679 to £39 615) and 2.9 (95% CI 2.6 to 3.1) years, respectively. A new treatment with a hazard reduction of 20% for myocardial infarction, stroke and cardiovascular disease death and no side-effects would be cost-effective if priced below £72 per year for the lowest risk patients and £646 per year for the highest risk patients.

Conclusions

Existing EHRs may be used to estimate lifetime healthcare costs and outcomes of patients with stable-CAD. The stable-CAD model developed in this study lends itself to informing decisions about commissioning, pricing and reimbursement. At current prices, to be cost-effective some established as well as future stable-CAD treatments may require stratification by patient risk.