Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes

AIMS/HYPOTHESIS

This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed.

RESULTS

Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%.

CONCLUSIONS/INTERPRETATION

Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators.

A Blueprint for Multi-use Disease Modeling in Health Economics: Results from Two Expert-Panel Consultations

BACKGROUND

The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs.

METHODS

We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings.

RESULTS

In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2).

CONCLUSIONS

MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerning which diseases and policy decisions they will be helpful for.

The Association between Deductibles and Cardiovascular Medication Adherence: A Retrospective Inception Cohort Study

OBJECTIVE

Drug non-adherence in primary preventive cardiovascular therapy is one of the most important modifiable drivers of cardiovascular events. The effect of deductibles in healthcare cost-sharing plans (the amount that has to be paid for healthcare services before the insurance company starts to pay) on such non-adherence in a European setting is unknown. Therefore, we estimated the association between deductibles and the adherence to primary preventive antihypertensive and antihyperlipidemic medication.

METHODS

Using the claims database of Menzis Health Insurer in the Netherlands, we applied ordered beta regression mixed modelling to estimate the association between deductibles and adherence taking several demographic and social-economic factors, repeated measurements and within-patient variation into account.

RESULTS

All in all, 106,316 patients starting primary preventive antihypertensive or antihyperlipidemic monotherapy were eligible for analysis. At index date, mean age of the study population was 58 years and 52% were male. Reaching the deductible limit and no need to pay for medication anymore increased the adherence [relative adherence ratio (RAR) 1.03, 95% confidence interval (95% CI): 1.00-1.05] for antihyperlipidemic therapy and 1.02 (95% CI: 1.00-1.04) for antihypertensive therapy. A larger deductible amount decreases the adherence of antihyperlipidemic and antihypertensive therapy (RAR 0.83; 95% CI: 0.69-1.00 and RAR 0.85, 95% CI: 0.74-0.98, respectively).

CONCLUSION

Independent of other risk factors for non-adherence, presence of deductibles in health insurance is associated with a small negative effect on the adherence to both primary preventive antihypertensive as well as antihyperlipidemic therapy. Further study is needed on the potential health-economic consequences.

Tailoring Type II Diabetes Treatment: Investigating the Effect of 5-HTT Polymorphisms on HbA1c Levels after Metformin Initiation

Aims

To investigate the effect of serotonin transporter (5-HTT) polymorphisms on change in HbA1c levels six months after metformin initiation in type 2 diabetes patients.

Materials and Methods

Participants of PROVALID (PROspective cohort study in patients with type 2 diabetes mellitus for VALidation of biomarkers) within the GIANTT (Groningen Initiative to ANalyse Type 2 Diabetes Treatment) cohort who initiated metformin were genotyped for combined 5-HTTLPR/rs25531 (L∗L∗, L∗S∗, and S∗S∗) and 5-HTT VNTR (STin 2.12, 12/-, and 10/-) polymorphisms, respectively. Multiple linear regression was applied to determine the change in HbA1c level from baseline date to six months across 5-HTTLPR/VNTR genotype groups, adjusted for baseline HbA1c, age, gender, triglyceride level, low-density lipoprotein level, and serum creatinine.

Results

157 participants were included, of which 56.2% were male. The average age was 59.3 ± 9.23 years, and the mean baseline HbA1c was 7.49% ± 1.21%. 5-HTTLPR was characterized in 46 patients as L∗L∗, 70 patients as L∗S∗, and 41 patients as S∗S∗ genotypes. No significant association was found between 5-HTTLPR and 5-HTT VNTR genotypes and change in HbA1c after adjustments.

Conclusions

5-HTT polymorphisms did not affect HbA1c levels six months after the start of metformin. Further long-term studies in large samples would be relevant to determine which polymorphisms can explain the variation in response to metformin treatment.

Comparative analysis of algorithm-guided treatment and predefined duration treatment programmes for depression: exploring cost-effectiveness using routine care data

BACKGROUND

More knowledge on the cost-effectiveness of various depression treatment programmes can promote efficient treatment allocation and improve the quality of depression care.

OBJECTIVE

This study aims to compare the real-world cost-effectiveness of an algorithm-guided programme focused on remission to a predefined duration, patient preference-centred treatment programme focused on response using routine care data.

METHODS

A naturalistic study (n=6295 in the raw dataset) was used to compare the costs and outcomes of two programmes in terms of quality-adjusted life years (QALY) and depression-free days (DFD). Analyses were performed from a healthcare system perspective over a 2-year time horizon. Incremental cost-effectiveness ratios were calculated, and the uncertainty of results was assessed using bootstrapping and sensitivity analysis.

FINDINGS

The algorithm-guided treatment programme per client yielded more DFDs (12) and more QALYs (0.013) at a higher cost (€3070) than the predefined duration treatment programme. The incremental cost-effectiveness ratios (ICERs) were around €256/DFD and €236 154/QALY for the algorithm guided compared with the predefined duration treatment programme. At a threshold value of €50 000/QALY gained, the programme had a probability of <10% of being considered cost-effective. Sensitivity analyses confirmed the robustness of these findings.

CONCLUSIONS

The algorithm-guided programme led to larger health gains than the predefined duration treatment programme, but it was considerably more expensive, and hence not cost-effective at current Dutch thresholds. Depending on the preferences and budgets available, each programme has its own benefits.

CLINICAL IMPLICATION

This study provides valuable information to decision-makers for optimising treatment allocation and enhancing quality of care cost-effectively.

Cost-Effectiveness of Four Tobacco Control Interventions in Mongolia

INTRODUCTION

The aim of this study is to quantify the cost-effectiveness of four tobacco control interventions: Tobacco taxation, mass media campaigns, school programs, and cessation support, and to illustrate how available evaluation tools can be adapted to the local setting.

AIMS AND METHODS

We used the dynamic population health modeling-health impact assessment tool to project the future smoking prevalence associated with the interventions and to simulate the resulting smoking-related disease burden over time. Applying the most recent available national Mongolian data as input, the costs and effects of four interventions were compared to a business-as-usual scenario, resulting in costs per life year gained and per disability-adjusted life years (DALYs) averted.

RESULTS

Three years after implementation, all interventions reduce the prevalence of current smoking, with the strongest reduction observed with the increase in tobacco tax (5.1% points), followed by mass media campaigns (1.6% points), school programs (1.3% points), and cessation support interventions (0.6% points). School programs were a cost-saving tobacco control intervention compared to current practice in Mongolia, while the other programs resulted in additional costs compared to business as usual. Compared to the World Health Organization (WHO) thresholds, all interventions would be considered "very cost-effective" in terms of cost per DALY averted (below US$ 4295 per DALY averted) in Mongolia.

CONCLUSIONS

Large-scale interventions such as taxation and mass media campaigns result in both cost-effectiveness and important health benefits in relation to intervention costs. Reducing the prevalence of smoking among the male population would be particularly worthwhile in Mongolia.

IMPLICATIONS

This study shows that in Mongolia school programs were a cost-saving intervention, while the cost-effectiveness ratios were US$ 25 per disability-adjusted life year (DALY) averted for mass media campaigns, US$ 74 for taxation, and US$ 1961 for cessation support interventions. Compared to the WHO thresholds, all interventions would be considered "very cost-effective" in terms of expenses per DALY averted ( Collapse

Key Words Collapse

MESH Headings

• Humans
• Male
• Cost-Benefit Analysis
• Tobacco Control
• Mongolia/epidemiology
• Smoking/epidemiology
• Cost of Illness

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Grants

• Mongolian government and the UMCG

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Affiliation(s)

Ariuntuya Tuvdendorj Department of Health Policy, School of Public Health, Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Talitha Feenstra Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands Faculty of Science and Engineering, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, The Netherlands Faculty of Science and Engineering, Centre for Nutrition, Prevention, and Health Services, Institute for Public Health and the Environment, Bilthoven, The Netherlands
Erik Buskens Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

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Early symptom change contributes to the outcome prediction of cognitive behavioral therapy for depression patients: A machine learning approach

BACKGROUND

Limited evidence exists regarding the association between early symptom change and later outcomes of cognitive behavioral therapy (CBT). This study aimed to apply machine learning algorithms to predict continuous treatment outcomes based on pre-treatment predictors and early symptom changes and to uncover whether additional variance could be explained compared to regression methods. Additionally, the study examined early subscale symptom changes to determine the most significant predictors of treatment outcome.

METHODS

We investigated CBT outcomes in a large naturalistic dataset (N = 1975 depression patients). The sociodemographic profile, pre-treatment predictors, and early symptom change, including total and subscale scores were used to predict the Symptom Questionnaire (SQ)48 score at the 10th session as a continuous outcome. Different machine learners were compared to linear regression.

RESULTS

Early symptom change and baseline symptom score were the only significant predictors. Models with early symptom change explained 22.0 % to 23.3 % more variance than those without early symptom change. Specifically, the baseline total symptom score, and the early symptom score changes of the subscales pertaining to depression and anxiety were the top three predictors of treatment outcome.

LIMITATION

Excluded patients with missing treatment outcomes had slightly higher symptom scores at baseline, indicating possible selection bias.

CONCLUSION

Early symptom change improved the prediction of treatment outcomes. The prediction performance achieved is far from clinical relevance: the best learner could only explain 51.2 % of the variance in outcomes. Compared to linear regression, more sophisticated preprocessing and learning methods did not substantially improve performance.

A Promising Approach to Optimizing Sequential Treatment Decisions for Depression: Markov Decision Process

The most appropriate next step in depression treatment after the initial treatment fails is unclear. This study explores the suitability of the Markov decision process for optimizing sequential treatment decisions for depression. We conducted a formal comparison of a Markov decision process approach and mainstream state-transition models as used in health economic decision analysis to clarify differences in the model structure. We performed two reviews: the first to identify existing applications of the Markov decision process in the field of healthcare and the second to identify existing health economic models for depression. We then illustrated the application of a Markov decision process by reformulating an existing health economic model. This provided input for discussing the suitability of a Markov decision process for solving sequential treatment decisions in depression. The Markov decision process and state-transition models differed in terms of flexibility in modeling actions and rewards. In all, 23 applications of a Markov decision process within the context of somatic disease were included, 16 of which concerned sequential treatment decisions. Most existing health economic models relating to depression have a state-transition structure. The example application replicated the health economic model and enabled additional capacity to make dynamic comparisons of more interventions over time than was possible with traditional state-transition models. Markov decision processes have been successfully applied to address sequential treatment-decision problems, although the results have been published mostly in economics journals that are not related to healthcare. One advantage of a Markov decision process compared with state-transition models is that it allows extended action space: the possibility of making dynamic comparisons of different treatments over time. Within the context of depression, although existing state-transition models are too basic to evaluate sequential treatment decisions, the assumptions of a Markov decision process could be satisfied. The Markov decision process could therefore serve as a powerful model for optimizing sequential treatment in depression. This would require a sufficiently elaborate state-transition model at the cohort or patient level.

Exploring Structural Uncertainty and Impact of Health State Utility Values on Lifetime Outcomes in Diabetes Economic Simulation Models: Findings from the Ninth Mount Hood Diabetes Quality-of-Life Challenge

BACKGROUND

Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models.

METHODS

Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences.

RESULTS

Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (-0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models (P = 0.049).

CONCLUSIONS

Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions.HighlightsThe findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs).There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.

Health-related quality of life for normal glycaemia, prediabetes and type 2 diabetes mellitus: Cross-sectional analysis of the ADDITION-PRO study

AIMS

We estimated and compared health-related quality of life for individuals with normal glucose tolerance, prediabetes and diabetes.

METHODS

Participants in the ADDITION-PRO study, Denmark, who attended a health assessment between 2009 and 2011, and who completed the 3-level EuroQoL 5-dimensions (EQ-5D-3L) questionnaire were included. For the present study, they were classified as normal glucose tolerance, prediabetes and diabetes (screen-detected and known) using the 2019 American Diabetes Association criteria. Prediabetes was defined as impaired fasting glucose, impaired glucose tolerance or HbA1c between 5.7-6.4% (39-47 mmol/mol). EQ-5D-3L data were converted into utility scores using Danish and UK values, where '1' equals full health and '0' equals death. Regression models estimated the association between utility and the different glucose health states.

RESULTS

The mean EQ-5D-3L score in the sample population was 0.86 ± 0.17 (median 0.85, interquartile range 0.76 to 1) using UK values. Almost half of the sample (48%) reported full health with an EQ-5D score of '1'. Individuals with known diabetes reported the lowest EQ-5D-3L utility scores (0.81 ± 0.20), followed by individuals with screen-detected diabetes (0.85 ± 0.19), prediabetes (0.86 ± 0.17) and normal glucose tolerance (0.90 ± 0.15). The differences were statistically significant for normal glucose and known diabetes relative to prediabetes, after adjusting for sex, age, smoking, BMI and physical activity. These findings also held using Danish values albeit the differences were of smaller magnitude.

CONCLUSIONS

Having prediabetes and diabetes was significantly associated with lower health-related quality of life relative to normal glucose tolerance. Our estimates will be useful to inform the value of interventions to prevent diabetes or prediabetes.

Four Aspects Affecting Health Economic Decision Models and Their Validation

Health care decision makers in many jurisdictions use cost-effectiveness analysis based on health economic decision models for policy decisions regarding coverage and price negotiation for medicines and medical devices. While validation of health economic decision models has always been considered important, many reviews of model-based cost-effectiveness studies report limitations regarding their validation. The current opinion paper discusses four aspects of current health economic decision modeling with relevance for future directions in model validation: increased use of complex models, international cooperation, open-source modeling, and stakeholder involvement. First, new, more complex clinical study designs and treatment strategies may require relatively complex model structures and/or input data analyses. Simultaneously, more widespread technical knowledge along with wider data availability have led to a broader range of model types. This puts extra requirements on model validation and transparency. Second, increased international cooperation of policy makers and, in particular, health technology assessment (HTA) authorities in performing model assessments is discussed in relation to the repeated use of health economic models (multi-use disease models). We argue such coordinated efforts may benefit model validity. Third, open-source modeling is discussed as one possible answer to increased transparency requirements. Finally, involvement of all relevant stakeholders throughout the whole decision process is an ongoing development that necessarily also includes health economic modeling. We argue this implies that model validity should be considered in a broader perspective, with more focus on conceptual modeling, model transparency, accuracy requirements, and choice of relevant model outcomes than previously.

The costs of inappropriate referral pathways in inpatient care for three major noncommunicable diseases in Mongolia: a national registry-based analysis

BACKGROUND

Non-communicable diseases (NCDs) consistently pose a huge economic burden to health systems and countries in general. The aim of this study was to quantify inpatient costs associated with chronic obstructive pulmonary disease, stroke and ischemic heart disease stratified by type of referral pathway, and to investigate key factors that drive these costs.

METHODS

A registry-based data analysis was performed using national public hospital inpatient records from 2016 to 2018 for 117,600 unique patients and linking patient-level inpatient health care use with hospital-specific unit cost per bed-day. These were combined to calculate the annual inpatient costs for each of the three disorders per person and per year. Generalized linear modeling was used to assess the association of inpatient costs with age, gender, location, comorbidity, treatment referral pathways and years.

RESULTS

Across three diagnoses, the majority of patients were female. Most were over 50-60 years old, with more than half being a pensioner, typically with at least one comorbidity. About 25% of patients followed what might be considered inappropriate (unofficial) inpatient referral pathways. Mean annual inpatient costs were int$ 721. These costs rose to int$ 849 for unofficial pathways and dropped to int$677 for official pathways. Further covariates significantly associated with high inpatient costs were location, age, gender, and comorbidity.

CONCLUSION

Our findings provide background information essential to develop evidence-based and cost-effective interventions aimed at health promotion, prevention and service delivery. Reducing the unofficial use of inpatient care can improve efficient resource allocation in health care and prevent further escalation of inpatient costs in the future.

Costs of minor bleeds in atrial fibrillation patients using a non-vitamin K antagonist oral anticoagulant

BACKGROUND

A very common side effect of non-vitamin K antagonist oral anticoagulant (NOAC) is (minor) bleeding. Data about impact and costs of minor bleeds in NOAC therapy is still limited or not present in current literature. In this patient orientated study, we aim to provide an estimate of the costs of minor bleeds in patients with atrial fibrillation (AF) treated with a NOAC.

METHODS

A retrospective observational cohort study was conducted. Patients with AF and on NOAC therapy were included. Data was obtained by questionnaires and information from electronic patient records. Reference prices were used to calculate the costs per patient. Furthermore, cost of minor bleeds per patient is compared with literature-based costs of minor and major bleeding.

RESULTS

139 patients were included. A total of 94 minor bleed were reported by 71 patients. The sum of minor bleeding costs from societal perspective were €9,851.49, or on average €70,87 (95% CI €54,37- €85,68) per patient with AF. The biggest cost drivers were rectal and vaginal bleeds, epistaxis was most commonly reported.

CONCLUSION

Total costs of minor bleeds from a societal perspective, in AF patients using NOACs, are non-trivial and exceed the costs presented in existing literature.

Prognostic models for predicting the risk of foot ulcer or amputation in people with type 2 diabetes: a systematic review and external validation study

AIMS/HYPOTHESIS

Approximately 25% of people with type 2 diabetes experience a foot ulcer and their risk of amputation is 10-20 times higher than that of people without type 2 diabetes. Prognostic models can aid in targeted monitoring but an overview of their performance is lacking. This study aimed to systematically review prognostic models for the risk of foot ulcer or amputation and quantify their predictive performance in an independent cohort.

METHODS

A systematic review identified studies developing prognostic models for foot ulcer or amputation over minimal 1 year follow-up applicable to people with type 2 diabetes. After data extraction and risk of bias assessment (both in duplicate), selected models were externally validated in a prospective cohort with a 5 year follow-up in terms of discrimination (C statistics) and calibration (calibration plots).

RESULTS

We identified 21 studies with 34 models predicting polyneuropathy, foot ulcer or amputation. Eleven models were validated in 7624 participants, of whom 485 developed an ulcer and 70 underwent amputation. The models for foot ulcer showed C statistics (95% CI) ranging from 0.54 (0.54, 0.54) to 0.81 (0.75, 0.86) and models for amputation showed C statistics (95% CI) ranging from 0.63 (0.55, 0.71) to 0.86 (0.78, 0.94). Most models underestimated the ulcer or amputation risk in the highest risk quintiles. Three models performed well to predict a combined endpoint of amputation and foot ulcer (C statistics >0.75).

CONCLUSIONS/INTERPRETATION

Thirty-four prognostic models for the risk of foot ulcer or amputation were identified. Although the performance of the models varied considerably, three models performed well to predict foot ulcer or amputation and may be applicable to clinical practice.

Informing policy makers on the efficiency of population level tobacco control interventions in Asia: A systematic review of model-based economic evaluations

BACKGROUND

Economic evaluations of tobacco control interventions support decisions regarding resource allocation in public health policy. Our systematic review was aimed at identifying potential bias in decision models used to estimate the long-term costs and effects of population-based tobacco control interventions in Asia.

METHODS

We included studies conducted in Asian countries and using a modelling technique to evaluate the economic impacts of one or more population-based tobacco interventions in line with the Framework Convention on Tobacco Control (FCTC). We assessed the structure, input parameters, and risk of bias for each model, and performed a narrative synthesis of the included studies.

RESULTS

Nine model-based economic evaluation studies of population-based tobacco interventions were identified. About 60% of the criteria for reporting quality were met in all studies, indicating that reporting generally lacked transparency. The studies were highly heterogeneous in terms of the scope, types, and structures of their models and the quality of input parameters. One-third of the models applied in the studies scored a high risk of bias, with problems mostly falling into the following categories: model type, time horizons, and smoking transition probabilities.

CONCLUSIONS

More data are needed to provide high-quality evidence regarding the cost-effectiveness of tobacco control policies in Asia. Strong evidence at the country level hinges on the availability of accurate estimates of the effects of the interventions, the relative risks of smoking, and the price elasticity of the demand for tobacco. Simple transfers of models built in Western populations do not suffice.

PROTOCOL REGISTRATION

PROSPERO CRD 42019141679.

Evaluating the Ability of Economic Models of Diabetes to Simulate New Cardiovascular Outcomes Trials: A Report on the Ninth Mount Hood Diabetes Challenge

OBJECTIVES

The cardiovascular outcomes challenge examined the predictive accuracy of 10 diabetes models in estimating hard outcomes in 2 recent cardiovascular outcomes trials (CVOTs) and whether recalibration can be used to improve replication.

METHODS

Participating groups were asked to reproduce the results of the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPA-REG OUTCOME) and the Canagliflozin Cardiovascular Assessment Study (CANVAS) Program. Calibration was performed and additional analyses assessed model ability to replicate absolute event rates, hazard ratios (HRs), and the generalizability of calibration across CVOTs within a drug class.

RESULTS

Ten groups submitted results. Models underestimated treatment effects (ie, HRs) using uncalibrated models for both trials. Calibration to the placebo arm of EMPA-REG OUTCOME greatly improved the prediction of event rates in the placebo, but less so in the active comparator arm. Calibrating to both arms of EMPA-REG OUTCOME individually enabled replication of the observed outcomes. Using EMPA-REG OUTCOME-calibrated models to predict CANVAS Program outcomes was an improvement over uncalibrated models but failed to capture treatment effects adequately. Applying canagliflozin HRs directly provided the best fit.

CONCLUSIONS

The Ninth Mount Hood Diabetes Challenge demonstrated that commonly used risk equations were generally unable to capture recent CVOT treatment effects but that calibration of the risk equations can improve predictive accuracy. Although calibration serves as a practical approach to improve predictive accuracy for CVOT outcomes, it does not extrapolate generally to other settings, time horizons, and comparators. New methods and/or new risk equations for capturing these CV benefits are needed.

Are quality-adjusted medical prices declining for chronic disease? Evidence from diabetes care in four health systems

Improvements in medical treatment have contributed to rising health spending. Yet there is relatively little evidence on whether the spending increase is "worth it" in the sense of producing better health outcomes of commensurate value-a critical question for understanding productivity in the health sector and, as that sector grows, for deriving an accurate quality-adjusted price index for an entire economy. We analyze individual-level panel data on medical spending and health outcomes for 123,548 patients with type 2 diabetes in four health systems: Japan, The Netherlands, Hong Kong and Taiwan. Using a "cost-of-living" method that measures value based on improved survival, we find a positive net value of diabetes care: the value of improved survival outweighs the added costs of care in each of the four health systems. This finding is robust to accounting for selective survival, end-of-life spending, and a range of values for a life-year or fraction of benefits attributable to medical care. Since the estimates do not include the value from improved quality of life, they are conservative. We, therefore, conclude that the increase in medical spending for management of diabetes is offset by an increase in quality.

Smoking-attributable burden of lung cancer in Mongolia a data synthesis study on differences between men and women

BACKGROUND

Smoking is widely recognized as one of the most prevalent and preventable causes of many cancer types. This study aimed to quantify the population attributable fraction (PAF) of the lung cancer burden for smoking in Mongolia.

METHODS

Lung cancer incidence and lung cancer-related death data came from the population-based national registry covering the period 2007-2016. Smoking prevalence data came from the STEPwise approach (STEP) national survey. The lung cancer-related disease burden was calculated and expressed in Disability Adjusted Life Years (DALYs) lost by gender and by year. This was combined with current smoking and former smoking prevalence data, and relative risks (RR) of lung cancer-related deaths for current smokers and former smokers versus never smokers from region-specific cohort studies to estimate the PAF of lung cancer attributable to "ever-smoking" in Mongolia.

RESULTS

Between 2007 and 2016, lung cancer accounted for the loss of over 63,000 DALYs in Mongolia. The PAF of lung cancer-related deaths attributable to current and former smoking combined was 58.1% (95% IR = 43.1%-72.2%) for men and 8.9% (95% IR = 4.1% -13.5%) for women. Smoking-attributable DALYs loss amounted to 2589 years (95% IR = 1907-3226) in 2016.

CONCLUSIONS

A considerable health loss may be prevented with an effective anti-smoking policy. In Mongolia, more than one third of lung cancer-related DALY loss is attributable to active smoking, and thus is potentially preventable. Furthermore, a gender-specific tobacco control policy may be worthwhile because of the large gender difference in smoking exposure in Mongolia. Next to this, age specific policy, including a smoke-free generation policy for adolescents, with targeted education, and mass media campaigns is needed.

The implementation of HTA in medicine pricing and reimbursement policies in Indonesia: Insights from multiple stakeholders

Objectives

This study aimed to identify the barriers and facilitators to improve the use of health technology assessment (HTA) for the selection of medicines listed in the e-Catalogue and the national formulary in Indonesia.

Methods

Semi-structured interviews were conducted to collect qualitative data. Purposive sampling was used to recruit the stakeholders consisting of policymakers, a pharmaceutical industry representative, healthcare providers, and patients. The data were analyzed using directed content analysis and following the COnsolidated criteria for REporting Qualitative studies (COREQ).

Results

The twenty-five participants interviewed agreed with the use of HTA for supporting the e-Catalogue and the national formulary and perceived the advantages of HTA implementation outweighed the disadvantages. Barriers mentioned were a lack of capability of local human resources, financial incentives, a clear framework and insufficient data. Strategies suggested to overcome the barriers were establishing (inter)national networks to build up capacity, setting up departments of HTA in several universities in Indonesia, and introducing a clear HTA framework. Facilitators mentioned were the ambition to achieve universal health coverage, the presence of legal frameworks to implement HTA in the e-Catalogue and the national formulary, and the demands for appropriate medicine policies.

Conclusions

Several barriers are currently hampering broad implementation of HTA in medicine pricing and reimbursement policy in Indonesia. Solutions to these issues appear feasible and important facilitators exist.

The Challenge of Transparency and Validation in Health Economic Decision Modelling: A View from Mount Hood

Transparency in health economic decision modelling is important for engendering confidence in the models and in the reliability of model-based cost-effectiveness analyses. The Mount Hood Diabetes Challenge Network has taken a lead in promoting transparency through validation with biennial conferences in which diabetes modelling groups meet to compare simulated outcomes of pre-specified scenarios often based on the results of pivotal clinical trials. Model registration is a potential method for promoting transparency, while also reducing the duplication of effort. An important network initiative is the ongoing construction of a diabetes model registry (https://www.mthooddiabeteschallenge.com). Following the 2012 International Society for Pharmacoeconomics and Outcomes Research and the Society of Medical Decision Making (ISPOR-SMDM) guidelines, we recommend that modelling groups provide technical and non-technical documentation sufficient to enable model reproduction, but not necessarily provide the model code. We also request that modelling groups upload documentation on the methods and outcomes of validation efforts, and run reference case simulations so that model outcomes can be compared. In this paper, we discuss conflicting definitions of transparency in health economic modelling, and describe the ongoing development of a registry of economic models for diabetes through the Mount Hood Diabetes Challenge Network, its objectives and potential further developments, and highlight the challenges in its construction and maintenance. The support of key stakeholders such as decision-making bodies and journals is key to ensuring the success of this and other registries. In the absence of public funding, the development of a network of modellers is of huge value in enhancing transparency, whether through registries or other means.

Decision models of prediabetes populations: A systematic review

AIMS

With evidence supporting the use of preventive interventions for prediabetes populations and the use of novel biomarkers to stratify the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. Our aim is to summarize and assess the quality and validity of decision models and model-based economic evaluations of populations with prediabetes, to evaluate their potential use for the assessment of novel prevention strategies and to discuss the knowledge gaps, challenges and opportunities.

MATERIALS AND METHODS

We searched Medline, Embase, EconLit and NHS EED between 2000 and 2018 for studies reporting computer simulation models of the natural history of individuals with prediabetes and/or we used decision models to evaluate the impact of treatment strategies on these populations. Data were extracted following PRISMA guidelines and assessed using modelling checklists. Two reviewers independently assessed 50% of the titles and abstracts to determine whether a full text review was needed. Of these, 10% was assessed by each reviewer to cross-reference the decision to proceed to full review. Using a standardized form and double extraction, each of four reviewers extracted 50% of the identified studies.

RESULTS

A total of 29 published decision models that simulate prediabetes populations were identified. Studies showed large variations in the definition of prediabetes and model structure. The inclusion of complications in prediabetes (n = 8) and type 2 diabetes (n = 17) health states also varied. A minority of studies simulated annual changes in risk factors (glycaemia, HbA1c, blood pressure, BMI, lipids) as individuals progressed in the models (n = 7) and accounted for heterogeneity among individuals with prediabetes (n = 7).

CONCLUSIONS

Current prediabetes decision models have considerable limitations in terms of their quality and validity and do not allow evaluation of stratified strategies using novel biomarkers, highlighting a clear need for more comprehensive prediabetes decision models.

Use of medicine pricing and reimbursement policies for universal health coverage in Indonesia

OBJECTIVES

This study aimed to define the problems of the current use of the e-Catalogue and the national formulary (NF)-two elements of medicine pricing and reimbursement policies in Indonesia for achieving universal health coverage (UHC)-by examining the knowledge and attitudes of stakeholders. Specifically, to investigate (1) the perceived challenges involved in the further implementation of the e-Catalogue and the NF, (2) reasons of prescribing medicines not listed in the NF, and (3) possible improvements in the acceptance and use of the e-Catalogue and the NF.

METHODS

Semi-structured interviews were conducted with stakeholders (policymakers, healthcare providers, a pharmaceutical industry representative, and experienced patients) to collect the qualitative data. The data was analysed using directed content analysis, following the guidelines of the COnsolidated criteria for REporting Qualitative studies (COREQ) in reporting the findings.

RESULTS

Interestingly, 20 of 45 participants decided to withdraw from the interview due to their lack of knowledge of the e-Catalogue and the NF. All 25 stakeholders who fully participated in this research were in favor of the e-Catalogue and the NF. However, interviewees identified a range of challenges. A major challenge was the lack of harmonization between the lists of medicines in the e-Catalogue and the NF. Several system and personal reasons for prescribing medicines not listed in the NF were identified. Important reasons were a lack of incentives for physicians as well as a lack of transparent and evidence-based methods of selection for the medicines to be listed in the NF.

CONCLUSIONS

The e-Catalogue and the NF have not been fully utilized for achieving UHC in Indonesia. Some possible improvements suggested were harmonization of medicines listed in the e-Catalogue and the NF, restructuring incentive programs for prescribing NF medicines, and increasing the transparency and evidence-based approach for selection of medicines listed in the e-Catalogue and the NF.

Long-term incidence and risk factors of cardiovascular events in Asian populations: systematic review and meta-analysis of population-based cohort studies

BACKGROUND

Scientific studies on cardiovascular disease (CVD) burden and risk factors are predominantly based on short-term risk in Westerner populations, and such information may not be applicable to Asian populations, especially over the longer term. This review aims to estimate the long-term (>10 years) CVD burden, including coronary heart disease (CHD) and stroke, as well as associated risk factors in Asian populations.

METHODS

PubMed, Embase and Web of Science were systematically searched, and hits screened on: Asian adults, free of CVD at baseline; cohort study design (follow-up >10 years). Primary outcomes were fatal and non-fatal CVD events. Pooled estimates and between-study heterogeneity were calculated using random effects models, Q and I² statistics.

RESULTS

Overall, 32 studies were eligible for inclusion (follow-up: 11-29 years). The average long-term rate of fatal CVD is 3.68 per 1000 person-years (95% CI 2.84-4.53), the long-term cumulative risk 6.35% (95% CI 4.69%-8.01%, mean 20.13 years) and the cumulative fatal stroke/CHD risk ratio 1.5:1. Important risk factors for long-term fatal CVD (RR, 95% CI) were male gender (1.49, 1.36-1.64), age over 60/65 years (7.55, 5.59-10.19) and current smoking (1.68, 1.26-2.24). High non-HDL-c, and β- and γ-tocopherol serum were associated only with CHD (HR 2.46 [95% CI 1.29-4.71] and 2.47 [1.10-5.61] respectively), while stage 1 and 2 hypertensions were associated only with fatal stroke (2.02 [1.19-3.44] and 2.89 [1.68-4.96] respectively).

CONCLUSIONS

Over a 10 year + follow-up period Asian subjects had a higher risk of stroke than CHD. Contrary to CVD prevention in Western countries, strategies should also consider stroke instead of CHD only.

In vitro studies show synergistic effects of a procoagulant bispecific antibody and bypassing agents

Essentials Patients with hemophilia A and inhibitors receiving emicizumab experience breakthrough bleeding. Safety concerns may exist when combining emicizumab with bypassing agents. Combined bypassing agent and bispecific antibody increased thrombin generation up to 17-fold. Thrombotic effects should be considered when combining emicizumab with plasma bypassing agent.

SUMMARY

Background Investigational non-factor products such as emicizumab offer a treatment option for patients with hemophilia and inhibitors. However, their mechanism of action raises questions regarding safety when they are combined with treatments for breakthrough bleeding. Objectives To evaluate in vitro thrombin generation (TG) and clot formation for combinations of activated prothrombin complex concentrate (aPCC), recombinant activated factor VII (rFVIIa), and a sequence-identical analog of emicizumab (SIA). Methods Therapeutic concentrations of SIA (20-600 nm) alone or with aPCC (0.05-1 U mL-1 ), isolated aPCC components or rFVIIa (0.88-5.25 μg mL-1 ) were tested for TG and compared with reference ranges for healthy donor plasma. Coagulation of FVIII-inhibited blood was determined with a widely established method, i.e. rotational thromboelastometry (ROTEM), and confirmed with the Total Thrombus-formation Analysis System. Results and conclusions SIA (600 nm) or aPCC (0.5 U mL-1 ) alone resulted in peak thrombin levels of 21.4 nm and 38.6 nm, respectively, both of which are lower than normal (83.7 ± 29.8 nm). SIA plus aPCC (0.5 U mL-1 ) increased the peak thrombin level 17-fold over SIA alone, exceeding the reference plasma value by 4.2-fold. This hypercoagulable effect occurred with 600 nmSIA combined with as little as 0.25 U mL-1 aPCC, confirmed by ROTEM. FIX was the main driver for enhanced TG. SIA plus rFVIIa (1.75 μg mL-1 ) induced a 1.8-fold increase in the peak thrombin level in platelet-rich plasma, but it did not reach the normal range. These in vitro experiments demonstrate excessive TG after administration of a combination of aPCC and SIA at clinically relevant doses. Careful judgement may be required when breakthrough bleeding is treated in patients receiving emicizumab.

Computer Modeling of Diabetes and Its Transparency: A Report on the Eighth Mount Hood Challenge

OBJECTIVES

The Eighth Mount Hood Challenge (held in St. Gallen, Switzerland, in September 2016) evaluated the transparency of model input documentation from two published health economics studies and developed guidelines for improving transparency in the reporting of input data underlying model-based economic analyses in diabetes.

METHODS

Participating modeling groups were asked to reproduce the results of two published studies using the input data described in those articles. Gaps in input data were filled with assumptions reported by the modeling groups. Goodness of fit between the results reported in the target studies and the groups' replicated outputs was evaluated using the slope of linear regression line and the coefficient of determination (R²). After a general discussion of the results, a diabetes-specific checklist for the transparency of model input was developed.

RESULTS

Seven groups participated in the transparency challenge. The reporting of key model input parameters in the two studies, including the baseline characteristics of simulated patients, treatment effect and treatment intensification threshold assumptions, treatment effect evolution, prediction of complications and costs data, was inadequately transparent (and often missing altogether). Not surprisingly, goodness of fit was better for the study that reported its input data with more transparency. To improve the transparency in diabetes modeling, the Diabetes Modeling Input Checklist listing the minimal input data required for reproducibility in most diabetes modeling applications was developed.

CONCLUSIONS

Transparency of diabetes model inputs is important to the reproducibility and credibility of simulation results. In the Eighth Mount Hood Challenge, the Diabetes Modeling Input Checklist was developed with the goal of improving the transparency of input data reporting and reproducibility of diabetes simulation model results.

Research Costs Investigated: A Study Into the Budgets of Dutch Publicly Funded Drug-Related Research

BACKGROUND

The costs of performing research are an important input in value of information (VOI) analyses but are difficult to assess.

OBJECTIVE

The aim of this study was to investigate the costs of research, serving two purposes: (1) estimating research costs for use in VOI analyses; and (2) developing a costing tool to support reviewers of grant proposals in assessing whether the proposed budget is realistic.

METHODS

For granted study proposals from the Netherlands Organization for Health Research and Development (ZonMw), type of study, potential cost drivers, proposed budget, and general characteristics were extracted. Regression analysis was conducted in an attempt to generate a 'predicted budget' for certain combinations of cost drivers, for implementation in the costing tool.

RESULTS

Of 133 drug-related research grant proposals, 74 were included for complete data extraction. Because an association between cost drivers and budgets was not confirmed, we could not generate a predicted budget based on regression analysis, but only historic reference budgets given certain study characteristics. The costing tool was designed accordingly, i.e. with given selection criteria the tool returns the range of budgets in comparable studies. This range can be used in VOI analysis to estimate whether the expected net benefit of sampling will be positive to decide upon the net value of future research.

CONCLUSION

The absence of association between study characteristics and budgets may indicate inconsistencies in the budgeting or granting process. Nonetheless, the tool generates useful information on historical budgets, and the option to formally relate VOI to budgets. To our knowledge, this is the first attempt at creating such a tool, which can be complemented with new studies being granted, enlarging the underlying database and keeping estimates up to date.

Computer simulation models of pre-diabetes populations: a systematic review protocol

INTRODUCTION

Diabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision models due to their ability to forecast long-term health outcomes and costs beyond the time frame of clinical trials. To support good implementation and reimbursement decisions of interventions in these populations, models should be clinically credible, based on best available evidence, reproducible and validated against clinical data. Our aim is to identify recent studies on computer simulation models and model-based economic evaluations of populations of individuals with prediabetes, qualify them and discuss the knowledge gaps, challenges and opportunities that need to be addressed for future evaluations.

METHODS AND ANALYSIS

A systematic review will be conducted in MEDLINE, Embase, EconLit and National Health Service Economic Evaluation Database. We will extract peer-reviewed studies published between 2000 and 2016 that describe computer simulation models of the natural history of individuals with prediabetes and/or decision models to evaluate the impact of interventions, risk stratification and/or screening on these populations. Two reviewers will independently assess each study for inclusion. Data will be extracted using a predefined pro forma developed using best practice. Study quality will be assessed using a modelling checklist. A narrative synthesis of all studies will be presented, focussing on model structure, quality of models and input data, and validation status.

ETHICS AND DISSEMINATION

This systematic review is exempt from ethics approval because the work is carried out on published documents. The findings of the review will be disseminated in a related peer-reviewed journal and presented at conferences.

REVIEWREGISTRATION NUMBER

CRD42016047228.

Adhesion of Escherichia coli under flow conditions reveals potential novel effects of FimH mutations

FimH-mediated adhesion of Escherichia coli to bladder epithelium is a prerequisite for urinary tract infections. FimH is also essential for blood-borne bacterial dissemination, but the mechanisms are poorly understood. The purpose of this study was to assess the influence of different FimH mutations on bacterial adhesion using a novel adhesion assay, which models the physiological flow conditions bacteria are exposed to. We introduced 12 different point mutations in the mannose binding pocket of FimH in an E. coli strain expressing type 1 fimbriae only (MSC95-FimH). We compared the bacterial adhesion of each mutant across several commonly used adhesion assays, including agglutination of yeast, adhesion to mono- and tri-mannosylated substrates, and static adhesion to bladder epithelial and endothelial cells. We performed a comparison of these assays to a novel method that we developed to study bacterial adhesion to mammalian cells under flow conditions. We showed that E. coli MSC95-FimH adheres more efficiently to microvascular endothelium than to bladder epithelium, and that only endothelium supports adhesion at physiological shear stress. The results confirmed that mannose binding pocket mutations abrogated adhesion. We demonstrated that FimH residues E50 and T53 are crucial for adhesion under flow conditions. The coating of endothelial cells on biochips and modelling of physiological flow conditions enabled us to identify FimH residues crucial for adhesion. These results provide novel insights into screening methods to determine the effect of FimH mutants and potentially FimH antagonists.

Use of Value of Information in Healthcare Decision Making: Exploring Multiple Perspectives

BACKGROUND

Value of information (VOI) is a tool that can be used to inform decisions concerning additional research in healthcare. VOI estimates the value of obtaining additional information and indicates the optimal design for additional research. Although it is recognized as good practice in handling uncertainty, it is still hardly used in decision making in the Netherlands.

OBJECTIVE

This paper aims to examine the potential value of VOI, barriers and facilitators and the way forward with the use of VOI in the decision-making process for reimbursement of pharmaceuticals in the Netherlands.

METHODS

Three focus group interviews were conducted with researchers, policy makers, and representatives of pharmaceutical companies.

RESULTS

The results revealed that although all stakeholders recognize the relevance of VOI, it is hardly used and many barriers to the performance and use of VOI were identified. One of these barriers is that not all uncertainties are easily incorporated in VOI, and the results may be biased if structural uncertainties are ignored. Furthermore, not all research designs indicated by VOI may be feasible in practice.

CONCLUSIONS

To fully embed VOI into current decision-making processes, a threshold incremental cost-effectiveness ratio and guidelines that clarify when and how VOI should be performed are needed. In addition, it should be clear to all stakeholders how the results of VOI are used in decision making.

Continuous-Time Semi-Markov Models in Health Economic Decision Making

Continuous-time state transition models may end up having large unwieldy structures when trying to represent all relevant stages of clinical disease processes by means of a standard Markov model. In such situations, a more parsimonious, and therefore easier-to-grasp, model of a patient’s disease progression can often be obtained by assuming that the future state transitions do not depend only on the present state (Markov assumption) but also on the past through time since entry in the present state. Despite that these so-called semi-Markov models are still relatively straightforward to specify and implement, they are not yet routinely applied in health economic evaluation to assess the cost-effectiveness of alternative interventions. To facilitate a better understanding of this type of model among applied health economic analysts, the first part of this article provides a detailed discussion of what the semi-Markov model entails and how such models can be specified in an intuitive way by adopting an approach called vertical modeling. In the second part of the article, we use this approach to construct a semi-Markov model for assessing the long-term cost-effectiveness of 3 disease management programs for heart failure. Compared with a standard Markov model with the same disease states, our proposed semi-Markov model fitted the observed data much better. When subsequently extrapolating beyond the clinical trial period, these relatively large differences in goodness-of-fit translated into almost a doubling in mean total cost and a 60-d decrease in mean survival time when using the Markov model instead of the semi-Markov model. For the disease process considered in our case study, the semi-Markov model thus provided a sensible balance between model parsimoniousness and computational complexity.

Evaluation of patient registries supporting reimbursement decisions: the case of oxaliplatin for treatment of stage III colon cancer

BACKGROUND

Access with evidence development has been established for expensive intramural drugs in The Netherlands. The procedure involves a 4-year period of conditional reimbursement. During this period, additional evidence has to be gathered usually through a patient registry. Given the costs and time involved in gathering the data, it is important to carefully evaluate the registry.

OBJECTIVES

This study aimed to develop a model for the regular evaluation of patient registries during an access with evidence development process and find the optimal length of the registry period.

METHODS

We used data from a recent registry in The Netherlands on oxaliplatin as a treatment option for stage III colon cancer. We added simulated follow-up data to the empirical data available and applied value of information analysis to balance the gains of extending the period and amount of data gathering against the costs of registering patients.

RESULTS

We show that given the assumptions on cohort size, follow-up time, and purpose of the registry, the current (partly simulated) registry was not very efficient. Notably, the observation period could have been stopped to make a definite reimbursement decision after a maximum of 2 years rather than the fixed 4-year period.

CONCLUSIONS

Patient registries may be an efficient way to gather data on new medical treatments, but they need to be carefully designed and evaluated, in particular regarding their follow-up time. For each purpose, data gathering can be tailored to make sure decisions are taken at the moment that sufficient data are available.

Value of information analysis from a societal perspective: a case study in prevention of major depression

OBJECTIVES

Productivity losses usually have a considerable impact on cost-effectiveness estimates while their estimated values are often relatively uncertain. Therefore, parameters related to these indirect costs play a role in setting priorities for future research from a societal perspective. Until now, however, value of information analyses have usually applied a health care perspective for economic evaluations. Hence, the effect of productivity losses has rarely been investigated in such analyses. The aim of the current study therefore was to investigate the effects of including or excluding productivity costs in value of information analyses.

METHODS

Expected value of information analysis (EVPI) was performed in cost-effectiveness evaluation of prevention from both societal and health care perspectives, to give us the opportunity to compare different perspectives. Priorities for future research were determined by partial EVPI. The program to prevent major depression in patients with subthreshold depression was opportunistic screening followed by minimal contact psychotherapy.

RESULTS

The EVPI indicated that regardless of perspective, further research is potentially worthwhile. Partial EVPI results underlined the importance of productivity losses when a societal perspective was considered. Furthermore, priority setting for future research differed according to perspective.

CONCLUSIONS

The results illustrated that advise for future research will differ for a health care versus a societal perspective and hence the value of information analysis should be adjusted to the perspective that is relevant for the decision makers involved. The outcomes underlined the need for carefully choosing the suitable perspective for the decision problem at hand.

Which screening strategy should be offered to women with BRCA1 or BRCA2 mutations? A simulation of comparative cost-effectiveness

Background:

There is no consensus on the most effective strategy (mammography or magnetic resonance imaging (MRI)) for screening women with BRCA1 or BRCA2 mutations. The effectiveness and cost-effectiveness of the Dutch, UK and US screening strategies, which involve mammography and MRI at different ages and intervals were evaluated in high-risk women with BRCA1 or BRCA2 mutations.

Methods:

Into a validated simulation screening model, outcomes and cost parameters were integrated from published and cancer registry data. Main outcomes were life-years gained and incremental cost-effectiveness ratios. The simulation was situated in the Netherlands as well as in the United Kingdom, comparing the Dutch, UK and US strategies with the population screening as a reference. A discount rate of 3% was applied to both costs and health benefits.

Results:

In terms of life-years gained, the strategies from least to most cost-effective were the UK, Dutch and US screening strategy, respectively. However, the differences were small. Applying the US strategy in the Netherlands, the costs were €43 800 and 68 800 for an additional life-year gained for BRCA1 and BRCA2, respectively. At a threshold of €20 000 per life-year gained, implementing the US strategy in the Netherlands has a very low probability of being cost-effective. Stepping back to the less-effective UK strategy would save relatively little in costs and results in life-years lost. When implementing the screening strategies in the United Kingdom, the Dutch, as well as the US screening strategy have a high probability of being cost-effective.

Conclusion:

From a cost-effectiveness perspective, the Dutch screening strategy is preferred for screening high-risk women in the Netherlands as well as in the United Kingdom.

Decision makers’ views on health care objectives and budget constraints: results from a pilot study

Economic evaluations aim to inform policy makers about the costs and effects of medical interventions to support their decisions on the allocation of health care resources. Decision makers combine information on cost-effectiveness with their preferences and with possible constraints for the allocation of health care resources. That is, decision makers need to specify an optimality criterion and all possible (budget) constraints. Usually this is a more or less implicit process. The aim of our pilot study was to find out whether decision makers consider the objectives and budget constraints we selected for a theoretical model of resource allocation relevant, and to set priorities for these objectives.

A decision chart for assessing and improving the transferability of economic evaluation results between countries

OBJECTIVE

To develop a user-friendly tool for managing the transfer of economic evaluation results.

METHODS

Factors that may influence the transfer of health economic study results were systematically identified and the way they impact on transferability was investigated. A transferability decision chart was developed that includes: knock-out criteria; a checklist based on the transferability factors; and methods for improving transferability and for assessing the uncertainty of transferred results. This approach was tested on various international cost-effectiveness studies in the areas of interventional cardiology, vaccination and screening.

RESULTS

The transfer of study results is possible pending the outcomes of the transferability check and necessary adjustments. Transferability factors can be grouped into areas of methodological, healthcare system and population characteristics. Different levels of effort are required for analysis of factors, ranging from very low (e.g. discount rate) to very high (e.g. practice variation). The impact of differences of most transferability factors can be estimated via the key health economic determinants: capacity utilisation, effectiveness, productivity loss and returns to scale. Depending on the outcomes of the transferability check a correction of the study results for inflation and for differences related to currencies or purchasing power might be sufficient. Otherwise, modelling-based adjustments might be necessary, requiring the (re-)building and sometimes structural modification of the study model. For determination of the most essential adjustments, a univariate sensitivity analysis seems appropriate. If not all relevant study parameters can be substituted with country-specific ones, multivariate or probabilistic sensitivity analysis seems to be a promising way to quantify the uncertainty associated with a transfer. If study results cannot be transferred, the transfer of study models or designs should be investigated as this can significantly save time when conducting a new study.

CONCLUSIONS

Our transferability decision chart is a transparent and user-friendly tool for assessing and improving the transferability of economic evaluation results. A state of the art description of the methodology in a study, providing detailed components for calculation, is not only essential for determining its transferability but also for improving it via modelling adjustments.

Borrelia infections of ruminants in Europe

The occurrence of Borrelia spirochaetes in cattle in the Netherlands is reported for the second time, and in red deer and roe-deer in Austria for the first time. It is postulated that these spirochaetes are Borrelia burgdorferi rather than B. theileri. The reservoir role of ruminants in the epidemiology of human disease caused by B. burgdorferi in Europe should be investigated.