Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force--7

Cost Effectiveness of Nusinersen in the Treatment of Patients with Infantile-Onset and Later-Onset Spinal Muscular Atrophy in Sweden

BACKGROUND

Spinal muscular atrophy is a rare neuromuscular disorder with a spectrum of severity related to age at onset and the number of SMN2 gene copies. Infantile-onset (≤ 6 months of age) is the most severe spinal muscular atrophy and is the leading monogenetic cause of infant mortality; patients with later-onset (> 6 months of age) spinal muscular atrophy can survive into adulthood. Nusinersen is a new treatment for spinal muscular atrophy.

OBJECTIVE

The objective of this study was to evaluate the cost effectiveness of nusinersen for the treatment of patients with infantile-onset spinal muscular atrophy and later-onset spinal muscular atrophy in Sweden.

METHODS

One Markov cohort health-state transition model was developed for each population. The infantile-onset and later-onset models were based on the efficacy results from the ENDEAR phase III trial and the CHERISH phase III trial, respectively. The cost effectiveness of nusinersen in both models was compared with standard of care in Sweden.

RESULTS

For a time horizon of 40 years in the infantile-onset model and 80 years in the later-onset model, treatment with nusinersen resulted in 3.86 and 9.54 patient incremental quality-adjusted life-years and 0.02 and 2.39 caregiver incremental quality-adjusted life-years and an incremental cost of 21.9 and 38.0 million SEK (Swedish krona), respectively. These results translated into incremental cost-effectiveness ratios (including caregiver quality-adjusted life-years) of 5.64 million SEK (€551,300) and 3.19 million SEK (€311,800) per quality-adjusted life-year gained in the infantile-onset model and later-onset model, respectively.

CONCLUSIONS

Treatment with nusinersen resulted in overall survival and quality-adjusted life-year benefits but with incremental costs above 21 million SEK (€2 million) [mainly associated with maintenance treatment with nusinersen over a patient's lifespan]. Nusinersen was not cost effective when using a willingness-to-pay threshold of 2 million SEK (€195,600), which has been considered in a recent discussion by the Dental and Pharmaceutical Benefits Agency as a reasonable threshold for rare disease. Nonetheless, nusinersen gained reimbursement in Sweden in 2017 for paediatric patients (below 18 years old) with spinal muscular atrophy type I-IIIa.

Health gains, costs and cost-effectiveness of a population-based screening programme for abdominal aortic aneurysms

BACKGROUND

Abdominal aortic aneurysm (AAA) rupture carries a high fatality rate. AAAs can be detected before rupture by abdominal ultrasound imaging, allowing elective repair. Population-based screening for AAA in older men reduces AAA-related mortality by about 40 per cent. The UK began an AAA screening programme offering one-off scans to men aged 65 years in 2009. Sweden has a similar programme. Currently, there is no AAA screening programme in New Zealand. This cost-utility analysis aimed to assess the cost-effectiveness of a UK-style screening programme in the New Zealand setting.

METHODS

The analysis compared a formal AAA screening programme (one-off abdominal ultrasound imaging for about 20 000 men aged 65 years in 2011) with no systematic screening. A Markov macrosimulation model was adapted to estimate the health gains (in quality-adjusted life-years, QALYs), health system costs and cost-effectiveness in New Zealand. A health system perspective and lifetime horizon was adopted.

RESULTS

With New Zealand-specific inputs, the adapted model produced an estimate of about NZ $15 300 (€7746) per QALY gained, with a 95 per cent uncertainty interval (UI) of NZ $8700 to 31 000 (€4405 to 15 694) per QALY gained. Health gains were estimated at 117 (95 per cent UI 53 to 212) QALYs. Health system costs were NZ $1·68 million (€850 535), with a 95 per cent UI of NZ $820 200 to 3·24 million (€415 243 to €1·65 million).

CONCLUSION

Using New Zealand's gross domestic product per capita (about NZ $45 000 or €22 100) as a cost-effectiveness threshold, a UK-style AAA screening programme would be cost-effective in New Zealand.

Now Is the Time for Transparency in Value-Based Healthcare Decision Modeling

In contrast to many other countries, during the 20 years since the founding of Value in Health, the United States has moved further away from using value-based healthcare decision modeling (VHDM) for drugs and other medical care choices. US public and private health plans can be typically characterized as using "budget impact" decision making rather than VHDM, with drugs having low per-member per-month spending likely to be covered and reimbursed regardless of value. Orphan drugs and specialty drugs with relatively few patients (eg, end-stage cancer drugs) are often covered, whether cost-effective or not, because health plans want to avoid negative publicity. Although there are many explanations for the poor US uptake of VHDM, a key reason is that VHDM models and data often lack transparency and are not generally made available to researchers for independent verification and reproducibility. This violates the scientific method, and is counter to the stated position of the National Academy of Sciences and the top journals in the sciences and social sciences. Value in Health and related peer-reviewed journals could make a key contribution to improving scientific rigor and real-world healthcare decision-maker acceptability by requiring that VHDM models, source code, and data used in published articles be made freely available to interested readers.

Cost-Effectiveness of Treatment Options for Neuropathic Pain: a Systematic Review

BACKGROUND

Neuropathic pain significantly reduces an individual's quality of life and places a significant economic burden on society. As such, many cost-effectiveness analyses (CEAs) have been published for treatments available for neuropathic pain.

OBJECTIVES

The primary objective of this systematic review was to provide a detailed summary of the estimates of cost-effectiveness from published CEAs comparing available treatments for neuropathic pain. The secondary objectives were to identify the key drivers of cost-effectiveness and to assess the quality of published CEAs in neuropathic pain.

METHODS

We searched Embase, MEDLINE, Cochrane CENTRAL and seven other databases to identify CEAs reporting the costs, health benefits (e.g., quality-adjusted life-years or disability-adjusted life-years) and summary statistics, such as incremental cost-effectiveness ratios, of treatments for neuropathic pain. We excluded studies reporting diseases other than neuropathic pain, those for which the full text was not available (e.g., conference abstracts), studies not written in English or not published in peer-reviewed journals, and narrative reviews, editorials and opinion papers. Titles and abstract reviews, full-text reviews, and data extraction were all performed by two independent reviewers, with disagreement resolved by a third reviewer. Mean costs, health benefits, and summary statistics were reported and qualitatively compared across studies, stratified by time horizon. Drivers of cost-effectiveness were assessed using reported one-way sensitivity analyses. The quality of all included studies was evaluated using the Tufts CEA Registry Quality Score and study reporting using the CHEERS (Consolidated Health Economic Evaluation Reporting Standards) checklist.

RESULTS

A total of 22 studies were identified and included in this systematic review. Included studies were heterogeneous in the treatments compared, methodology and design, perspectives, and time horizons considered, making cross-study comparisons difficult. No single treatment was consistently the most cost-effective across all studies, but tricyclic antidepressants were the preferred treatment at a willingness-to-pay threshold of $US50,000 per quality-adjusted life-year in several studies with a short time horizon and a US payer perspective. Among the 14 studies reporting one-way sensitivity analyses, drivers of cost-effectiveness included utility values for health states and the likelihood of pain relief with treatment. The quality of the identified CEAs was moderate to high, and overall reporting largely met CHEERS recommendations.

LIMITATIONS

To assess drivers of cost-effectiveness and quality, we only included studies with the full text available and thus excluded some CEAs that reported cost-effectiveness results. The heterogeneity of the included studies meant that the study results could not be synthesized and comparison across studies was limited.

CONCLUSIONS

Though many pulished studies have evaluated the cost-effectiveness of treatments for neuropathic pain, significant heterogeneity between CEAs prevented synthesis of the results. Standardized methodology and improved reporting would allow for more reliable comparisons across studies.

A scoping review of simulation modeling in built environment and physical activity research: Current status, gaps, and future directions for improving translation

Existing reviews have suggested that simulation studies of physical activity and environments are an emerging area, but none have explored findings in this area systematically. We used a scoping review framework to assess the use of simulation modeling to inform decision-making about built environment influences on physical activity. A systematic literature search was conducted in multiple databases in January 2018. Sixteen articles met the inclusion criteria. The studies evaluated interventions and features that were related to neighborhood safety (crime or traffic), active transportation, land use design, and walking and biking infrastructure. All of the studies focused on urban areas and most considered heterogeneity of outcomes based on local context. The majority of studies (70%) did not appear to have engaged or been used by practitioners or policy-makers to inform real-world decisions. There has been a growth of simulation modeling studies, but there remain gaps. The studies evaluated built environment interventions that have been recommended by expert panels, but more were of interventions related to active transportation; few considered recommended interventions to support recreational activity. Furthermore, studies have all focused on urban settings and there is a need to consider non-urban settings and how heterogeneity could reduce or exacerbate health disparities. More work to involve and evaluate practices for engaging stakeholders in model development and interpretation is also needed to overcome the translation of simulation research to practice gap, and realize its potential impact on the built environment and physical activity.

Cost-effectiveness-analysis of ultrasound guidance for central venous catheterization compared with landmark method: a decision-analytic model

BACKGROUND

Ultrasound guidance for central venous catheterization is a commonly used alternative to the conventional landmark method. Because from the German perspective, the cost-effectiveness of ultrasound guidance is unclear, this study examined the cost-effectiveness of ultrasound guidance versus the landmark method for adults undergoing a central venous catheterization.

METHODS

A decision-tree based model was built to estimate the costs of averted catheter-related complications. Clinical data (e.g. arterial puncture, failed attempts) were obtained from a Cochrane review and a randomized controlled trial, whilst information about cost parameters were taken from a German hospital of maximum care. The analysis was conducted from the perspective of the German Statutory Health Insurance. Results were presented as incremental cost-effectiveness ratios. To assess the parameter uncertainty, several sensitivity analyses were performed (deterministic, probabilistic and with regard to the model structure).

RESULTS

Our analysis revealed that ultrasound guidance resulted in fewer complications per person (0.04 versus 0.17 for the landmark method) and was less expensive (€51 versus €230 for the landmark method). Results were robust to changes in the model parameters and in the model structure. Whilst our model population reflected approximately 49% of adults undergoing a central venous catheterization cannulation per year, structural sensitivity analyses (e.g. extending the study cohort to patients at higher baseline risk of complications, pediatric patients, or using real-time/indirect catheterization) indicated the cost-effectiveness of ultrasound guidance for a broader spectrum of patients. The results should be interpreted by considering the assumptions (e.g. target population) and approximations (e.g. cost parameters) underpinning the model.

CONCLUSIONS

Ultrasound guidance for central venous catheterization averts more catheter-related complications and may save the resources of the German Statutory Health Insurance compared with landmark method.

Rationale and protocol for estimating the economic value of a multicomponent quality improvement strategy for diabetes care in South Asia

BACKGROUND

Economic dimensions of implementing quality improvement for diabetes care are understudied worldwide. We describe the economic evaluation protocol within a randomised controlled trial that tested a multi-component quality improvement (QI) strategy for individuals with poorly-controlled type 2 diabetes in South Asia.

METHODS/DESIGN

This economic evaluation of the Centre for Cardiometabolic Risk Reduction in South Asia (CARRS) randomised trial involved 1146 people with poorly-controlled type 2 diabetes receiving care at 10 diverse diabetes clinics across India and Pakistan. The economic evaluation comprises both a within-trial cost-effectiveness analysis (mean 2.5 years follow up) and a microsimulation model-based cost-utility analysis (life-time horizon). Effectiveness measures include multiple risk factor control (achieving HbA1c < 7% and blood pressure < 130/80 mmHg and/or LDL-cholesterol< 100 mg/dl), and patient reported outcomes including quality adjusted life years (QALYs) measured by EQ-5D-3 L, hospitalizations, and diabetes related complications at the trial end. Cost measures include direct medical and non-medical costs relevant to outpatient care (consultation fee, medicines, laboratory tests, supplies, food, and escort/accompanying person costs, transport) and inpatient care (hospitalization, transport, and accompanying person costs) of the intervention compared to usual diabetes care. Patient, healthcare system, and societal perspectives will be applied for costing. Both cost and health effects will be discounted at 3% per year for within trial cost-effectiveness analysis over 2.5 years and decision modelling analysis over a lifetime horizon. Outcomes will be reported as the incremental cost-effectiveness ratios (ICER) to achieve multiple risk factor control, avoid diabetes-related complications, or QALYs gained against varying levels of willingness to pay threshold values. Sensitivity analyses will be performed to assess uncertainties around ICER estimates by varying costs (95% CIs) across public vs. private settings and using conservative estimates of effect size (95% CIs) for multiple risk factor control. Costs will be reported in US$ 2018.

DISCUSSION

We hypothesize that the additional upfront costs of delivering the intervention will be counterbalanced by improvements in clinical outcomes and patient-reported outcomes, thereby rendering this multi-component QI intervention cost-effective in resource constrained South Asian settings.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01212328.

Planning for the future: Modelling daily emergency department presentations in an Australian capital city

OBJECTIVE

To describe and model a decade of ED presentations in metropolitan Melbourne, Australia, from July 2000 to June 2010 and to validate the model of ED presentations by testing the model's performance in forecasting the subsequent 2 year period of daily presentations, from July 2010 to June 2012.

METHODS

Retrospective analyses of prospectively collected data sourced from the Victorian Emergency Minimum Dataset were performed and included 13 public hospitals. Time series modelling involved unobserved components modelling and forward selection of variables using incidence rate ratios. Forecasting with the model and validation were performed using the 2 year period up to June 2012. Model performance was calculated using the mean average percentage error.

RESULTS

A total of 7 031 242 patient presentations occurred to the sample metropolitan EDs in the 12 year study period. An absolute increase in mean daily ED presentations of 81.3% was observed. Presentations increased on Sunday and Monday incidence rate ratio of 1.10 (95% CI 1.08-1.11, P < 0.05). No monthly or seasonal pattern was evident. Public holidays were associated with increased presentations, incidence rate ratio of 1.11 (95% CI 1.08-1.15, P < 0.05). The model with the best goodness-of-fit and Wald χ² value included Sunday-Monday (vs Tuesday-Saturday), public holidays, the trend of gradual increase over time and a stochastic (random white noise) cycle. The mean average percentage error for the 2 year forecast period was 3.6%.

CONCLUSION

We have produced and validated a model for predicting daily ED presentations across a major city. Even though ED presentations are multifactorial, city-wide daily presentations are predictable and explained by a small number of variables. The model will have implications for future health planning.

Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review

BACKGROUND

Heart failure (HF) is a well-recognized public health concern and imposes high economic and societal costs. Decision analytic models exist for evaluating the economic ramifications associated with HF. Despite this, studies that appraise these modelling approaches for augmenting best-practice decisions remain scarce.

OBJECTIVE

Our objective was to conduct a systematic literature review (SLR) of published economic models for the management of HF and describe their general and methodological features.

METHODS

This SLR employed a combination of relevant search terms associated with HF, which were used in a number of databases, including MEDLINE, Embase, the National Health Service Economic Evaluation Database, Cost-Effectiveness Analysis Registry, ScHARR Health Utilities Database and Cochrane Library Database. A number of model features (i.e. model structure, specification, outcomes assessed, scenario and sensitivity analysis, key model drivers) were extracted and subsequently summarized.

RESULTS

Of 64 publications retained, a selection of modelling approaches were identified, including Markov (n = 28), trial-based analytic (n = 22), discrete-event simulation (n = 6), survival analytic (n = 7) and decision-tree modelling (n = 1) approaches. The bulk of publications employed either a cost-utility (n = 27) or cost-effectiveness (n = 36) analysis and evaluated more than one study outcome, which typically included overall costs (n = 59), incremental cost-effectiveness ratios (n = 55), life-years gained (n = 48) and willingness-to-pay thresholds (n = 37). Most publications focused on patients with chronic HF (n = 40) and used New York Heart Association (NYHA) disease classifications to categorize patients and determine disease severity. Few (n = 19) publications documented the use of hospitalization states for modelling patient outcomes and associated costs. A quality assessment of the included publications revealed most articles demonstrated reasonable methodological value.

CONCLUSIONS

We identified numerous decision analytic modelling approaches for evaluating the cost effectiveness of pharmacologic treatments in HF. A Markov cohort model approach was most commonly used, and most models relied on NYHA classes as a proxy of HF severity, disease progression and prognosis.

Microsimulation model for the health economic evaluation of osteoporosis interventions: study protocol

INTRODUCTION

Osteoporosis is a systemic skeletal disease that is characterised by reduced bone strength and increased fracture risk. Osteoporosis-related fractures impose enormous disease and economic burden to the society. Although many treatments and health interventions are proven effective to prevent fractures, health economic evaluation adds evidence to their economic merits. Computer simulation modelling is a useful approach to extrapolate clinical and economic outcomes from clinical trials and it is increasingly used in health economic evaluation. Many osteoporosis health economic models have been developed in the past decades; however, they are limited to academic use and there are no publicly accessible health economic models of osteoporosis.

METHODS AND ANALYSIS

We will develop the Australian osteoporosis health economic model based on our previously published microsimulation model of osteoporosis in the Chinese population. The development of the model will follow the recommendations for the conduct of economic evaluations in osteoporosis by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases and the US branch of the International Osteoporosis Foundation. The model will be a state-transition semi-Markov model with memory. Clinical parameters in the model will be mainly obtained from the Dubbo Osteoporosis Epidemiology Study and the health economic parameters will be collected from the Australian arm of the International Costs and Utilities Related to Osteoporotic Fractures Study. Model transparency and validates will be tested using the recommendations from Good Research Practices in Modelling Task Forces. The model will be used in economic evaluations of osteoporosis interventions including pharmaceutical treatments and primary care interventions. A user-friendly graphical user interface will be developed, which will connect the user to the calculation engine and the results will be generated. The user interface will facilitate the use of our model by people in different sectors.

ETHICS AND DISSEMINATION

No ethical approval is needed for this study. Results of the model validation and future economic evaluation studies will be submitted to journals. The user interface of the health economic model will be publicly available online accompanied with a user manual.

Cost-utility of Sunitinib Versus Pazopanib in Metastatic Renal Cell Carcinoma in Canada using Real-world Evidence

BACKGROUND AND OBJECTIVE

The development of new targeted therapies in kidney cancer has shaped disease management in the metastatic phase. Our study aims to conduct a cost-utility analysis of sunitinib versus pazopanib in first-line setting in Canada for metastatic renal cell carcinoma (mRCC) patients using real-world data.

METHODS

A Markov model with Monte-Carlo microsimulations was developed to estimate the clinical and economic outcomes of patients treated in first-line with sunitinib versus pazopanib. Transition probabilities were estimated using observational data from a Canadian database where real-life clinical practice was captured. The costs of therapies, disease progression, and management of adverse events were included in the model in Canadian dollars ($Can). Utility and disutility values were included for each health state. Incremental cost-utility ratio (ICUR) and incremental cost-effectiveness ratios (ICER) were calculated for a time horizon of 5 years, from the Canadian Healthcare System perspective.

RESULTS

The cost difference was $36,303 and the difference in quality-adjusted life year (QALY) was 0.54 in favour of sunitinib with an ICUR of $67,227/QALY for sunitinib versus pazopanib. The major cost component (56%) is related to best supportive care (BSC) where patients tend to stay for a longer period of time compared to other states. The difference in life years gained (LYG) between sunitinib and pazopanib was 1.21 LYG (33.51 vs 19.03 months) and the ICER was $30,002/LYG. Sensitivity analysis demonstrated the robustness of the model with a high probability of sunitinib being a cost-effective option when compared to pazopanib.

CONCLUSION

When using real-world evidence, sunitinib is found to be a cost-effective treatment compared to pazopanib in mRCC patients in Canada.

The impact of food reformulation on nutrient intakes and health, a systematic review of modelling studies

BACKGROUND

Unhealthy diet is a risk factor for adverse health outcomes. Reformulation of processed foods has the potential to improve population diet, but evidence of its impact is limited. The purpose of this review was to explore the impact of reformulation on nutrient intakes, health outcomes and quality of life; and to evaluate the quality of modelling studies on reformulation interventions.

METHODS

A systematic review of peer-reviewed articles published between January 2000 and December 2017 was performed using MEDLINE, ScienceDirect, Embase, Scopus, Cochrane, and the Centre for Reviews and Dissemination of the University of York. Additional studies were identified through informal searches on Google and specialized websites. Only simulation studies modelling the impact of food reformulation on nutrient intakes and health outcomes were included. Included articles were independently extracted by 2 reviewers using a standardized, pre-piloted data form, including a self-developed tool to assess study quality.

RESULTS

A total of 33 studies met the selected inclusion criteria, with 20, 5 and 3 studies addressing sodium, sugar and fats reformulation respectively, and 5 studies addressing multiple nutrients. Evidence on the positive effects of reformulation on consumption and health was stronger for sodium interventions, less conclusive for sugar and fats. Study features were highly heterogeneous including differences in methods, the type of policy implemented, the extent of the reformulation, and the spectrum of targeted foods and nutrients. Nonetheless, partial between-study comparisons show a consistent relationship between percentages reformulated and reductions in individual consumption. Positive results are also shown for health outcomes and quality of life measures, although comparisons across studies are limited by the heterogeneity in model features and reporting. Study quality was often compromised by short time-horizons, disregard of uncertainty and time dependencies, and lack of model validation.

CONCLUSIONS

Reformulation models highlight relevant improvements in diets and population health. While models are valuable tools to evaluate reformulation interventions, comparisons are limited by non-homogeneous designs and assumptions. The use of validated models and extensive scenario analyses would improve models' credibility, providing useful insights for policy-makers.

REVIEW REGISTRATION

A research protocol was registered within the PROSPERO database (ID number CRD42017057341).

Recommendations for the conduct of economic evaluations in osteoporosis: outcomes of an experts' consensus meeting organized by the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) and the US branch of the International Osteoporosis Foundation

Economic evaluations are increasingly used to assess the value of health interventions, but variable quality and heterogeneity limit the use of these evaluations by decision-makers. These recommendations provide guidance for the design, conduct, and reporting of economic evaluations in osteoporosis to improve their transparency, comparability, and methodologic standards.

INTRODUCTION

This paper aims to provide recommendations for the conduct of economic evaluations in osteoporosis in order to improve their transparency, comparability, and methodologic standards.

METHODS

A working group was convened by the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis to make recommendations for the design, conduct, and reporting of economic evaluations in osteoporosis, to define an osteoporosis-specific reference case to serve a minimum standard for all economic analyses in osteoporosis, to discuss methodologic challenges and initiate a call for research. A literature review, a face-to-face meeting in New York City (including 11 experts), and a review/approval by a larger group of experts worldwide (including 23 experts in total) were conducted.

RESULTS

Recommendations on the type of economic evaluation, methods for economic evaluation, modeling aspects, base-case analysis and population, excess mortality, fracture costs and disutility, treatment characteristics, and model validation were provided. Recommendations for reporting economic evaluations in osteoporosis were also made and an osteoporosis-specific checklist was designed that includes items to report when performing an economic evaluation in osteoporosis. Further, 12 minimum criteria for economic evaluations in osteoporosis were identified and 12 methodologic challenges and need for further research were discussed.

CONCLUSION

While the working group acknowledges challenges and the need for further research, these recommendations are intended to supplement general and national guidelines for economic evaluations, improve transparency, quality, and comparability of economic evaluations in osteoporosis, and maintain methodologic standards to increase their use by decision-makers.

Risk prediction models for lung cancer: Perspectives and dissemination

Objective

The objective was to systematically assess lung cancer risk prediction models by critical evaluation of methodology, transparency and validation in order to provide a direction for future model development.

Methods

Electronic searches (including PubMed, EMbase, the Cochrane Library, Web of Science, the China National Knowledge Infrastructure, Wanfang, the Chinese BioMedical Literature Database, and other official cancer websites) were completed with English and Chinese databases until April 30th, 2018. Main reported sources were input data, assumptions and sensitivity analysis. Model validation was based on statements in the publications regarding internal validation, external validation and/or cross-validation.

Results

Twenty-two studies (containing 11 multiple-use and 11 single-use models) were included. Original models were developed between 2003 and 2016. Most of these were from the United States. Multivariate logistic regression was widely used to identify a model. The minimum area under the curve for each model was 0.57 and the largest was 0.87. The smallest C statistic was 0.59 and the largest 0.85. Six studies were validated by external validation and three were cross-validated. In total, 2 models had a high risk of bias, 6 models reported the most used variables were age and smoking duration, and 5 models included family history of lung cancer.

Conclusions

The prediction accuracy of the models was high overall, indicating that it is feasible to use models for high-risk population prediction. However, the process of model development and reporting is not optimal with a high risk of bias. This risk affects prediction accuracy, influencing the promotion and further development of the model. In view of this, model developers need to be more attentive to bias risk control and validity verification in the development of models.

Dynamic Models of Infectious Disease Transmission in Prisons and the General Population

Incarcerated populations experience elevated burdens of infectious diseases, which are exacerbated by limited access to prevention measures. Dynamic models are used to assess the spread and control of diseases within correctional facilities and repercussions on the general population. Our systematic review of dynamic models of infectious diseases within correctional settings identified 34 studies published between 1996 and 2017. Of these, 23 focused on disease dynamics and intervention in prison without accounting for subsequent spread to the community. The main diseases modeled in these studies were human immunodeficiency virus (HIV; n = 14, 41%), tuberculosis (TB; n = 10, 29%), and hepatitis C virus (HCV; n = 7, 21%). Models were fitted to epidemiologic data in 14 studies; uncertainty and sensitivity analyses were conducted in 8, and validation of model projection against empirical data was done in 1 study. According to the models, prison-based screening and treatment may be highly effective strategies for reducing the burden of HIV, TB, HCV, and other sexually transmissible infections among prisoners and the general community. Decreasing incarceration rates were projected to reduce HIV and HCV infections among people who inject drugs and TB infections among all prisoners. Limitations of the modeling studies and opportunities for using dynamic models to develop quantitative evidence for informing prison infection control measures are discussed.

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.

Application of dynamic modelling techniques to the problem of antibacterial use and resistance: a scoping review

Selective pressure exerted by the widespread use of antibacterial drugs is accelerating the development of resistant bacterial populations. The purpose of this scoping review was to summarise the range of studies that use dynamic models to analyse the problem of bacterial resistance in relation to antibacterial use in human and animal populations. A comprehensive search of the peer-reviewed literature was performed and non-duplicate articles (n = 1486) were screened in several stages. Charting questions were used to extract information from the articles included in the final subset (n = 81). Most studies (86%) represent the system of interest with an aggregate model; individual-based models are constructed in only seven articles. There are few examples of inter-host models outside of human healthcare (41%) and community settings (38%). Resistance is modelled for a non-specific bacterial organism and/or antibiotic in 40% and 74% of the included articles, respectively. Interventions with implications for antibacterial use were investigated in 67 articles and included changes to total antibiotic consumption, strategies for drug management and shifts in category/class use. The quality of documentation related to model assumptions and uncertainty varies considerably across this subset of articles. There is substantial room to improve the transparency of reporting in the antibacterial resistance modelling literature as is recommended by best practice guidelines.

Decision modelling for economic evaluation of liver transplantation

As the gap between a shortage of organs and the immense demand for liver grafts persists, every available donor liver needs to be optimized for utility, urgency and equity. To overcome this challenge, decision modelling might allow us to gather evidence from previous studies as well as compare the costs and consequences of alternative options. For public health policy and clinical intervention assessment, it is a potentially powerful tool. The most commonly used types of decision analytical models include decision trees, the Markov model, microsimulation, discrete event simulation and the system dynamic model. Analytic models could support decision makers in the field of liver transplantation when facing specific problems by synthesizing evidence, comprising all relevant options, generalizing results to other contexts, extending the time horizon and exploring the uncertainty. For modeling studies of economic evaluation for transplantation, understanding the current nature of the disease is crucial, as well as the selection of appropriate modelling techniques. The quality and availability of data is another key element for the selection and development of decision analytical models. In addition, good practice guidelines should be complied, which is important for standardization and comparability between economic outputs.

Modeling in Colorectal Cancer Screening: Assessing External and Predictive Validity of MISCAN-Colon Microsimulation Model Using NORCCAP Trial Results

BACKGROUND

Microsimulation models are increasingly being used to inform colorectal cancer (CRC) screening recommendations. MISCAN-Colon is an example of such a model, used to inform the Dutch CRC screening program and US Preventive Services Task Force guidelines. Assessing the validity of these models is essential to provide transparency regarding their performance. In this study, we tested the external and predictive validity of MISCAN-Colon.

METHODS

We validated MISCAN-Colon using the Norwegian Colorectal Cancer Prevention (NORCCAP) trial, a randomized controlled trial that examined the effectiveness of once-only flexible sigmoidoscopy (FS) screening. We simulated the study population and design of the NORCCAP trial in MISCAN-Colon and compared 10- to 12-year model-predicted hazard ratios (HRs) for overall and distal CRC incidence and mortality to those observed. In addition, we compared the numbers of screen-detected neoplasia. Finally, we predicted the trial's future results to allow for the assessment of predictive validity.

RESULTS

MISCAN-Colon predicted an HR for overall CRC incidence (0.85), distal CRC incidence (0.82), overall CRC mortality (0.68), and distal CRC mortality (0.62). These were within the limits of the 95% confidence intervals of the NORCCAP trial results. Similar results were observed for the number of screen-detected cancers. The model significantly underestimated the number of screen-detected adenomas. Model-predicted HRs for CRC incidence and mortality up to 15- to 17-year follow-up were 0.84 and 0.72, respectively.

CONCLUSION

Although the underestimation of screen-detected adenomas requires further investigation, MISCAN-Colon is able to make a valid replication of the CRC incidence and mortality reduction of an FS screening trial, which suggests that it can be considered a useful tool to support decision making on CRC screening.

Matching the model with the evidence: comparing discrete event simulation and state-transition modeling for time-to-event predictions in a cost-effectiveness analysis of treatment in metastatic colorectal cancer patients

BACKGROUND

Individual patient data, e.g. from clinical trials, often need to be extrapolated or combined with additional evidence when assessing long-term impact in cost-effectiveness modeling studies. Different modeling methods can be used to represent the complex dynamics of clinical practice; the choice of which may impact cost-effectiveness outcomes. We compare the use of a previously designed cohort discrete-time state-transition model (DT-STM) with a discrete event simulation (DES) model.

METHODS

The original DT-STM was replicated and a DES model developed using AnyLogic software. Models were populated using individual patient data of a phase III study in metastatic colorectal cancer patients, and compared based on their evidence structure, internal validity, and cost-effectiveness outcomes. The DT-STM used time-dependent transition probabilities, whereas the DES model was populated using parametric distributions.

RESULTS

The estimated time-dependent transition probabilities for the DT-STM were irregular and more sensitive to single events due to the required small cycle length and limited number of event observations, whereas parametric distributions resulted in smooth time-to-event curves for the DES model. Although the DT-STM and DES model both yielded similar time-to-event curves, the DES model represented the trial data more accurately in terms of mean health-state durations. The incremental cost-effectiveness ratio (ICER) was €172,443 and €168,383 per Quality Adjusted Life Year gained for the DT-STM and DES model, respectively.

CONCLUSION

DES represents time-to-event data from clinical trials more naturally and accurately than DT-STM when few events are observed per time cycle. As a consequence, DES is expected to yield a more accurate ICER.

Modeling Approaches in Cost-Effectiveness Analysis of Disease-Modifying Therapies for Relapsing-Remitting Multiple Sclerosis: An Updated Systematic Review and Recommendations for Future Economic Evaluations

BACKGROUND

Numerous cost-effectiveness analyses (CEAs) of disease-modifying therapies (DMTs) for relapsing-remitting multiple sclerosis (RRMS) have been published in the last three decades. Literature reviews of the modeling methods and results from these CEAs have also been published. The last literature review that focused on modeling methods, without country or time horizon in the inclusion criteria, included studies published up to 2012. Since then, new DMTs have become available, and new models and data sources have been used to assess their cost effectiveness.

OBJECTIVE

The aim of this systematic review was to provide a detailed and comprehensive description of the relevant aspects of economic models used in CEAs of DMTs for RRMS, to understand how these models have progressed from recommendations provided in past reviews, what new approaches have been developed, what issues remain, and how they could be addressed.

METHODS

EMBASE, MEDLINE, Cochrane Central Register of Controlled Trials (CENTRAL), the National Health System (NHS) Economic Evaluations Database, the Health Technology Assessment (HTA) Database, and EconLit were searched for cost-effectiveness studies of DMTs for RRMS that used decision-analytic models, published in English between 1 January 2012 and 24 December 2017. The inclusion criteria were as follows: being a full economic evaluation, a decision-analytic model was used, the target population concerned adult patients with RRMS, and being available in full-text format. Studies were not excluded based on the methodological quality. The background information of the included studies, as well as specific information on the components of the economic models related to the areas of recommendation from previous reviews were extracted.

RESULTS

Twenty-three studies from ten countries were included. The model structure of these studies has converged over time, characterizing the course of disease progression in terms of changes in disability and the occurrence of relapses over time. Variations were found in model approach; data sources for the natural course of the disease and comparative efficacy between DMTs; number of lines of treatment modeled; long-term efficacy waning and treatment discontinuation assumptions; type of withdrawal; and criteria for selecting adverse events. Main areas for improvement include using long-term time horizons and societal perspective; reporting relevant health outcomes; conducting scenario analyses using different sources of natural history and utility values; and reporting how the model was validated.

CONCLUSION

The structure of economic models used in CEAs of DMTs for RRMS has converged over time. However, variation remains in terms of model approach, inputs, and assumptions. Though some recommendations from previous reviews have been incorporated in later models, areas for improvement remain.

A Generic Model for Follicular Lymphoma: Predicting Cost, Life Expectancy, and Quality-Adjusted-Life-Year Using UK Population-Based Observational Data

OBJECTIVES

To use real-world data to develop a flexible generic decision model to predict cost, life expectancy, and quality-adjusted life-years (QALYs) for follicular lymphoma (FL) in the general patient population.

METHODS

All patients newly diagnosed with FL in the UK's population-based Haematological Malignancy Research Network (www.hmrn.org) between 2004 and 2011 were followed until 2015 (N = 740). Treatment pathways, QALYs, and costs were incorporated into a discrete event simulation to reflect patient heterogeneity, including age and disease management. Two scenario analyses, based on the latest National Institute for Health and Clinical Excellence (NICE) guidelines (rituximab induction therapy for newly diagnosed asymptomatic patients and rituximab maintenance therapy for patients between treatments), were conducted and their economic impacts were compared to current practice.

RESULTS

Incidence-based analysis revealed expected average lifetime costs ranging from £6,165 [US$7,709] to £63,864 [US$79,862] per patient, and average life expectancy from 75 days to 17.56 years. Prevalence-based analysis estimated average annual treatment costs of £60-65 million [US$75-80 million], accounting for approximately 10% of the United Kingdom's annual National Health Service budget for hematological cancers as a whole. Assuming that treatment effects reported in trials are applicable to all patient groups, scenario analyses for two recent NICE guidelines demonstrated potential annual cost savings for the United Kingdom that ranged with uptake frequency from £0.6 million to £11 million [US$0.75-2.75 million].

CONCLUSIONS

Costs, survival, and QALYs associated with FL vary markedly with patient characteristics and disease management. Allowing the production of more realistic outcomes across the patient population as a whole, our model addresses this heterogeneity and is a useful tool with which to evaluate new technologies/treatments to support healthcare decision makers.

Economic Analysis of Vaccination Programs: An ISPOR Good Practices for Outcomes Research Task Force Report

This report provides recommendations for budget holders and decision makers in high-, middle, and low-income countries requiring economic analyses of new vaccination programs to allocate scarce resources given budget constraints. ISPOR's Economic Evaluation of Vaccines Designed to Prevent Infectious Disease: Good Practices Task Force wrote guidelines for three analytic methods and solicited comments on them from external reviewers. Cost-effectiveness analyses use decision-analytic models to estimate cumulative changes in resource use, costs, and changes in quality- or disability-adjusted life-years attributable to changes in disease outcomes. Constrained optimization modeling uses a mathematical objective function to be optimized (e.g. disease cases avoided) for a target population for a set of interventions including vaccination programs within established constraints. Fiscal health modeling estimates changes in net present value of government revenues and expenditures attributable to changes in disease outcomes. The task force recommends that those designing economic analyses for new vaccination programs take into account the decision maker's policy objectives and country-specific decision context when estimating: uptake rate in the target population; vaccination program's impact on disease cases in the population over time using a dynamic transmission epidemiologic model; vaccination program implementation and operating costs; and the changes in costs and health outcomes of the target disease(s). The three approaches to economic analysis are complementary and can be used alone or together to estimate a vaccination program's economic value for national, regional, or subregional decision makers in high-, middle-, and low-income countries.

Event simulation and external validation applied in published health economic models for obesity: a systematic review

INTRODUCTION

This study aims to determine methodological variations in the event simulation approaches of published health economic decision models, in the field of obesity, and to investigate whether their predictiveness and validity were investigated via external event validation techniques, which investigate how well the model reproduces reality.

AREAS COVERED

A systematic review identified a total of 87 relevant papers, of which 72 that simulated obesity-associated events were included. Most frequently simulated events were coronary heart disease (≈ 83%), type 2 diabetes (≈ 74%), and stroke (≈ 66%). Only for ten published model-based health economic assessments in obesity an external event validation was performed (14%; 10 of 72), and only for one the predictiveness and validity of the event simulation was investigated in a cohort of obese subjects.

EXPERT COMMENTARY

We identified a wide range of obesity related event simulation approaches. Published obesity models lack information on the predictive quality and validity of the applied event simulation approaches. Further work on comparing and validating these event simulation approaches is required to investigate their predictiveness and validity, which will offer guidance future modelling in the field of obesity.

Budget impact analysis of the adoption of new hypertension guidelines in Colombia

BACKGROUND

Hypertension represents a high burden of disease in different healthcare systems. Recent guideline published in 2017 by the American Heart Association and the American College of Cardiology has generated a debate between clinicians and policymakers due to the lowering of diagnosis threshold and the subsequent increase of the prevalence and healthcare costs. No empirical research exists addressing the question about the pressure on healthcare costs generated by new standards. This study aims to quantify the impact on the hypertension diagnosis and treatment costs for healthcare system using the new hypertension guideline.

METHODS

We conducted a budget impact analysis from a Colombian healthcare payer's perspective with a 3-year time horizon (2018-2020), in which we estimated the difference in total medical care costs between previous hypertension cut-off points (140/90 mmHg) and new guideline cut-off points (130/80 mmHg).

RESULTS

Our results show that the impact of the adoption of the new hypertension guideline would represent a decrease close to 22% in total annual high blood pressure costs in Colombia. This reduction is mainly driven by a lower number of cardiovascular complications. It is worth noting that these results should be taken with caution due to local available data.

CONCLUSIONS

A high-middle income country such as Colombia should carry out an exhaustive revision of the recommendations of the new hypertension guideline, due to its high probability of saving medical treatment costs for the healthcare system.

The Cost Effectiveness of Lubiprostone in Chronic Idiopathic Constipation

OBJECTIVE

The objective of this study was to evaluate the cost effectiveness of lubiprostone, prucalopride, placebo and immediate referral to secondary care in chronic idiopathic constipation (CIC) in an economic model that was used by the UK National Institute for Health and Care Excellence (NICE) in developing guidance.

METHODS

We developed a cohort state-transition model to reflect the treatment pathway in CIC from the UK NHS and personal social services perspective. Time on treatment was determined by a treatment continuation rule using data from an indirect comparison and survival curves fitted to long-term data. Quality of life was defined by whether CIC was resolved or unresolved, using published values. Costs were determined by drug acquisition costs, invasive procedures and healthcare resource use (associated with resolved or unresolved CIC), using published UK sources. Deterministic and probabilistic sensitivity analyses were conducted.

RESULTS

Over a 10-year time horizon, lubiprostone was more costly and more effective than placebo and immediate referral to secondary care, with incremental cost-effectiveness ratios (ICERs) of £58,979 and £21,152. Lubiprostone dominated prucalopride in the base case and with a time horizon of 1 year. The main sensitivity for the comparison against placebo was the assumptions around placebo cost and efficacy. The main sensitivity for the comparison against prucalopride was the endpoint used in the indirect comparison.

CONCLUSION

Lubiprostone may be cost effective compared with prucalopride or immediate referral but not compared with placebo in the base case. The implementation of the guidance issued by NICE should increase quality of life for patients with CIC and provide a further treatment option.

Cost-effectiveness of three different strategies for the treatment of first recurrent Clostridium difficile infection diagnosed in a community setting

OBJECTIVE

A significant portion of patients with Clostridium difficile infections (CDI) experience recurrence, and there is little consensus on its treatment. With the availability of newer agents for CDI and the added burdens of recurrent disease, a cost-effectiveness analysis may provide insight on the most efficient use of resources.

DESIGN

A decision-tree analysis was created to compare the cost-effectiveness of 3 possible treatments for patients with first CDI recurrence: oral vancomycin, fidaxomicin, or bezlotoxumab plus vancomycin. The model was performed from a payer's perspective with direct cost inputs and a timeline of 1 year. A systematic review of literature was performed to identify clinical, utility, and cost data. Quality-adjusted life years (QALY) and incremental cost-effectiveness ratios were calculated. The willingness-to-pay (WTP) threshold was set at $100,000 per QALY gained. The robustness of the model was tested using one-way sensitivity analyses and probabilistic sensitivity analysis.

RESULTS

Vancomycin had the lowest cost ($15,692) and was associated with a QALY gain of 0.8019 years. Bezlotoxumab plus vancomycin was a dominated strategy. Fidaxomicin led to a higher QALY compared to vancomycin, at an incremental cost of $500,975 per QALY gained. Based on our WTP threshold, vancomycin alone was the most cost-effective regimen for treating the first recurrence of CDI. Sensitivity analyses demonstrated the model's robustness.

CONCLUSIONS

Vancomycin alone appears to be the most cost-effective regimen for the treatment of first recurrence of CDI. Fidaxomicin alone led to the highest QALY gained, but at a cost beyond what is considered cost-effective.

Economic Modeling Considerations for Rare Diseases

OBJECTIVES

To identify challenges that affect the feasibility and rigor of economic models in rare diseases and strategies that manufacturers have employed in health technology assessment submissions to demonstrate the value of new orphan products that have limited study data.

METHODS

Targeted reviews of PubMed, the National Institute for Health and Care Excellence's (NICE's) Highly Specialised Technologies (HST), and the Scottish Medicines Consortium's (SMC's) ultra-orphan submissions were performed.

RESULTS

A total of 19 PubMed studies, 3 published NICE HSTs, and 11 ultra-orphan SMC submissions were eligible for inclusion. In rare diseases, a number of different factors may affect the model's ability to comply with good practice recommendations. Many products for the treatment of rare diseases have an incomplete efficacy and safety profile at product launch. In addition, there is often limited available natural history and epidemiology data. Information on the direct and indirect cost burden of an orphan disease also may be limited, making it difficult to estimate the potential economic benefit of treatment. These challenges can prevent accurate estimation of a new product's benefits in relation to costs. Approaches that can address such challenges include using patient and/or clinician feedback to inform model assumptions; data from disease analogues; epidemiological techniques, such as matching-adjusted indirect comparison; and long-term data collection.

CONCLUSIONS

Modeling in rare diseases is often challenging; however, a number of approaches are available to support the development of model structures and the collation of input parameters and to manage uncertainty.

Cost-effectiveness analyses of genetic and genomic diagnostic tests

Developments in next-generation sequencing technologies have driven the clinical application of diagnostic tests that interrogate the whole genome, which offer the chance to diagnose rare inherited diseases or inform the targeting of therapies. New genomic diagnostic tests compete with traditional approaches to diagnosis, including the genetic testing of single genes and other clinical strategies, for finite health-care budgets. In this context, decision analytic model-based cost-effectiveness analysis is a useful method to help evaluate the costs versus consequences of introducing new health-care interventions. This Perspective presents key methodological, technical, practical and organizational challenges that must be considered by decision-makers responsible for the allocation of health-care resources to obtain robust and timely information about the relative cost-effectiveness of the increasing numbers of emerging genomic tests.

Cost-Effectiveness of Olaratumab in Combination with Doxorubicin for Patients with Soft Tissue Sarcoma in the United States

BACKGROUND

Standard first-line treatments for advanced soft tissue sarcoma (STS) have changed little for 40 years, and outcomes have been poor. Recently, the United States (US) Food and Drug Administration conditionally approved olaratumab in combination with doxorubicin (Olara + Dox) based on a randomized phase II trial that reported a significant 11.8-month improvement in median survival versus single-agent doxorubicin (Dox). The present study investigated the cost-effectiveness of Olara + Dox compared with Dox and five other standard-of-care regimens from the US payer perspective.

METHODS

An economic model was constructed to estimate costs and outcomes over patients' lifetimes from start of therapy. Progression-free and overall survival were based on survival analysis of patient-level data and a meta-analysis. Adverse-event rates were based on trials. Costs were from published sources.

RESULTS

Olara + Dox resulted in an estimated additional 1.27 life-years (LYs) compared with Dox, with an increase in total expected lifetime costs of $133,653. The incremental cost-effectiveness ratio (ICER) was estimated at $105,408 per LY gained; in a fully incremental analysis, all other regimens were dominated (higher costs and lower LYs or a higher ICER).

CONCLUSION

Olara + Dox is cost-effective for STS treatment compared with Dox and other standard-of-care regimens at willingness-to-pay thresholds of $150,000 per LY and above.

Economic evaluation of HIV pre-exposure prophylaxis strategies: protocol for a methodological systematic review and quantitative synthesis

BACKGROUND

Pre-exposure prophylaxis (PrEP) with antiretrovirals is an efficacious and effective intervention to decrease the risk of HIV (human immunodeficiency virus) acquisition. Yet drug and delivery costs prohibit access in many jurisdictions. In the absence of guidelines for the synthesis of economic evaluations, we developed a protocol for a systematic review of economic evaluation studies for PrEP by drawing on best practices in systematic reviews and the conduct and reporting of economic evaluations. We aim to estimate the incremental cost per health outcome of PrEP compared with placebo, no PrEP, or other HIV prevention strategies; assess the methodological variability in, and quality of, economic evaluations of PrEP; estimate the incremental cost per health outcome of different PrEP implementation strategies; and quantify the potential sources of heterogeneity in outcomes.

METHODS

We will systematically search electronic databases (MEDLINE, Embase) and the gray literature. We will include economic evaluation studies that assess both costs and health outcomes of PrEP in HIV-uninfected individuals, without restricting language or year of publication. Two reviewers will independently screen studies using predefined inclusion criteria, extract data, and assess methodological quality using the Philips checklist, Second Panel on the Cost-effectiveness of Health and Medicines, and the International Society for Pharmacoeconomics and Outcomes Research recommendations. Outcomes of interest include incremental costs and outcomes in natural units or utilities, cost-effectiveness ratios, and net monetary benefit. We will perform descriptive and quantitative syntheses using sensitivity analyses of outcomes by population subgroups, HIV epidemic settings, study designs, baseline intervention contexts, key parameter inputs and assumptions, type of outcomes, economic perspectives, and willingness to pay values.

DISCUSSION

Findings will guide future economic evaluation of PrEP strategies in terms of methodological and knowledge gaps, and will inform decisions on the efficient integration of PrEP into public health programs across epidemiologic and health system contexts.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42016038440 .

Cost-Effectiveness of Nivolumab-Ipilimumab Combination Therapy Compared with Monotherapy for First-Line Treatment of Metastatic Melanoma in the United States

BACKGROUND

The approval of new immunotherapies has dramatically changed the treatment landscape of metastatic melanoma. These survival gains come with trade-offs in side effects and costs, as well as important considerations for third-party payer systems, physicians, and patients.

OBJECTIVE

To develop a Markov model to determine the cost-effectiveness of nivolumab, ipilimumab, and nivolumab-ipilimumab combination as firstline therapy in metastatic melanoma, while accounting for differential effectiveness in programmed death-ligand 1 (PD-L1) positive and negative patients.

METHODS

A 3-state Markov model (PD-L1 positive stable disease, PD-L1 negative stable disease, and progression and/or death) was developed using a U.S. societal perspective with a lifetime time horizon of 14.5 years. Transition probabilities were calculated from progression-free (PF) survival data reported in the CheckMate-067 trial. Costs were expressed in 2015 U.S. dollars and were determined using national sources. Adverse event (AE) management was determined using immune-related AE (irAE) data from CheckMate-067, irAE management guides for nivolumab and ipilimumab, and treatment guidelines. Utilities were obtained from published literature, using melanoma-specific studies when available, and were weighted based on incidence and duration of irAEs. Base case, one-way sensitivity, and probabilistic sensitivity analyses were conducted.

RESULTS

Nivolumab-ipilimumab combination therapy was not the cost-effective choice ($454,092 per PF quality-adjusted life-year [QALY]) compared with nivolumab monotherapy in a base case analysis at a willingness-to-pay threshold of $100,000 per PFQALY. Combination therapy and nivolumab monotherapy were cost-effective choices compared with ipilimumab monotherapy. PD-L1 positive status, utility of nivolumab and combination therapy, and medication costs contributed the most uncertainty to the model. In a population of 100% PD-L1 negative patients, nivolumab was still the optimal treatment, but combination therapy had an improved incremental cost-effectiveness ratio (ICER) of $295,903 per PFQALY. Combination therapy became dominated by nivolumab, when 68% of the sample was PD-L1 positive. In addition, the cost of ipilimumab would have to decrease to < $21,555 per dose for combination therapy to have an ICER < $100,000 per PFQALY and to < $19,151 (a 42% reduction) to be more cost-effective than nivolumab monotherapy.

CONCLUSIONS

Nivolumab-ipilimumab combination therapy was not cost-effective compared with nivolumab monotherapy, which was the most cost-effective option. Professionals in managed care settings should consider the pharmacoeconomic implications of these new immunotherapies as they make value-based formulary decisions, and future cost-effectiveness studies are completed.

DISCLOSURES

No funding supported this study. Merino was a contractor with EMD Serono at the time of this study but does not have any conflicts of interest and did not receive any funding related to this study. All other authors have no financial disclosures and no conflicts of interest. All the authors contributed to the study concept and design. Tran, McDowell, and Barcelon took the lead in data collection, along with Oh, Keyvani, and Merino. All authors except Merino contributed to data interpretation. The manuscript was written by Oh, Tran, McDowell, and Wilson and revised by Oh, Tran, McDowell, Wilson, and Keyvani. This analysis was presented at Academy of Managed Care Pharmacy Managed Care & Specialty Pharmacy Annual Meeting 2016, April 19-22, 2016, in San Francisco, California, and at the International Society for Pharmacoeconomics and Outcomes Research Annual International Meeting, May 21-25, 2016, in Washington DC.

Using Observational Data to Calibrate Simulation Models

BACKGROUND

Individual-level simulation models are valuable tools for comparing the impact of clinical or public health interventions on population health and cost outcomes over time. However, a key challenge is ensuring that outcome estimates correctly reflect real-world impacts. Calibration to targets obtained from randomized trials may be insufficient if trials do not exist for populations, time periods, or interventions of interest. Observational data can provide a wider range of calibration targets but requires methods to adjust for treatment-confounder feedback. We propose the use of the parametric g-formula to estimate calibration targets and present a case-study to demonstrate its application.

METHODS

We used the parametric g-formula applied to data from the HIV-CAUSAL Collaboration to estimate calibration targets for 7-y risks of AIDS and/or death (AIDS/death), as defined by the Center for Disease Control and Prevention under 3 treatment initiation strategies. We compared these targets to projections from the Cost-effectiveness of Preventing AIDS Complications (CEPAC) model for treatment-naïve individuals presenting to care in the following year ranges: 1996 to 1999, 2000 to 2002, or 2003 onwards.

RESULTS

The parametric g-formula estimated a decreased risk of AIDS/death over time and with earlier treatment. The uncalibrated CEPAC model successfully reproduced targets obtained via the g-formula for baseline 1996 to 1999, but over-estimated calibration targets in contemporary populations and failed to reproduce time trends in AIDS/death risk. Calibration to g-formula targets improved CEPAC model fit for contemporary populations.

CONCLUSION

Individual-level simulation models are developed based on best available information about disease processes in one or more populations of interest, but these processes can change over time or between populations. The parametric g-formula provides a method for using observational data to obtain valid calibration targets and enables updating of simulation model inputs when randomized trials are not available.

Collaborative Modeling: Experience of the U.S. Preventive Services Task Force

Models can be valuable tools to address uncertainty, trade-offs, and preferences when trying to understand the effects of interventions. Availability of results from two or more independently developed models that examine the same question (comparative modeling) allows systematic exploration of differences between models and the effect of these differences on model findings. Guideline groups sometimes commission comparative modeling to support their recommendation process. In this commissioned collaborative modeling, modelers work with the people who are developing a recommendation or policy not only to define the questions to be addressed but ideally, work side-by-side with each other and with systematic reviewers to standardize selected inputs and incorporate selected common assumptions. This paper describes the use of commissioned collaborative modeling by the U.S. Preventive Services Task Force (USPSTF), highlighting the general challenges and opportunities encountered and specific challenges for some topics. It delineates other approaches to use modeling to support evidence-based recommendations and the many strengths of collaborative modeling compared with other approaches. Unlike systematic reviews prepared for the USPSTF, the commissioned collaborative modeling reports used by the USPSTF in making recommendations about screening have not been required to follow a common format, sometimes making it challenging to understand key model features. This paper presents a checklist developed to critically appraise commissioned collaborative modeling reports about cancer screening topics prepared for the USPSTF.

Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models

Background

Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes.

Methods

Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study.

Results

Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes.

Conclusions

Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.

Electronic supplementary material

The online version of this article (doi: 10.1186/s12874-017-0437-y) contains supplementary material, which is available to authorized users.

ISPOR Code of Ethics 2017 (4th Edition)

As the leading health economics and outcomes research (HEOR) professional society, ISPOR has a responsibility to establish a uniform, harmonized international code for ethical conduct. ISPOR has updated its 2008 Code of Ethics to reflect the current research environment. This code addresses what is acceptable and unacceptable in research, from inception to the dissemination of its results. There are nine chapters: 1 - Introduction; 2 - Ethical Principles respect, beneficence and justice with reference to a non-exhaustive compilation of international, regional, and country-specific guidelines and standards; 3 - Scope HEOR definitions and how HEOR and the Code relate to other research fields; 4 - Research Design Considerations primary and secondary data related issues, e.g., participant recruitment, population and research setting, sample size/site selection, incentive/honorarium, administration databases, registration of retrospective observational studies and modeling studies; 5 - Data Considerations privacy and data protection, combining, verification and transparency of research data, scientific misconduct, etc.; 6 - Sponsorship and Relationships with Others (roles of researchers, sponsors, key opinion leaders and advisory board members, research participants and institutional review boards (IRBs) / independent ethics committees (IECs) approval and responsibilities); 7 - Patient Centricity and Patient Engagement new addition, with explanation and guidance; 8 - Publication and Dissemination; and 9 - Conclusion and Limitations.

Methodological Issues in Economic Evaluations Submitted to the Pan-Canadian Oncology Drug Review (pCODR)

BACKGROUND

Public drug plans are faced with increasingly difficult funding decisions. In Canada, the pan-Canadian Oncology Drug Review (pCODR) makes funding recommendations to the provincial and territorial drug plans responsible for cancer drugs. Assessments of the economic models submitted by pharmaceutical manufacturers are publicly reported.

OBJECTIVES

The main objective of this research was to identify recurring methodological issues in economic models submitted to pCODR for funding reviews. The secondary objective was to explore whether there exists any observed relationships between reported methodological issues and funding recommendations made by pCODR's expert review committee.

METHODS

Publicly available Economic Guidance Reports from July 2011 (inception) until June 2014 for drug reviews with a final funding recommendation (N = 34) were independently examined by two authors. Major methodological issues from each review were abstracted and grouped into nine main categories. Each issue was also categorized based on perception of the reviewer's actions to manage it.

RESULTS

The most commonly reported issues involved costing (59% of reviews), time horizon (56%), and model structure (36%). Several types of issues were identified that usually could not be resolved, such as quality of clinical data or uncertainty with indirect comparisons. Issues with costing or choice of utility estimates could usually be addressed or explored by reviewers. No statistically significant relationship was found between any methodological issue and funding recommendations from the expert review committee.

CONCLUSIONS

The findings provide insights that can be used by parties who submit or review economic evidence for continuous improvement and consistency in economic modeling, reporting, and decision making.

Comparison of Timed Automata with Discrete Event Simulation for Modeling of Biomarker-Based Treatment Decisions: An Illustration for Metastatic Castration-Resistant Prostate Cancer

BACKGROUND

With the advent of personalized medicine, the field of health economic modeling is being challenged and the use of patient-level dynamic modeling techniques might be required.

OBJECTIVES

To illustrate the usability of two such techniques, timed automata (TA) and discrete event simulation (DES), for modeling personalized treatment decisions.

METHODS

An early health technology assessment on the use of circulating tumor cells, compared with prostate-specific antigen and bone scintigraphy, to inform treatment decisions in metastatic castration-resistant prostate cancer was performed. Both modeling techniques were assessed quantitatively, in terms of intermediate outcomes (e.g., overtreatment) and health economic outcomes (e.g., net monetary benefit). Qualitatively, among others, model structure, agent interactions, data management (i.e., importing and exporting data), and model transparency were assessed.

RESULTS

Both models yielded realistic and similar intermediate and health economic outcomes. Overtreatment was reduced by 6.99 and 7.02 weeks by applying circulating tumor cell as a response marker at a net monetary benefit of -€1033 and -€1104 for the TA model and the DES model, respectively. Software-specific differences were observed regarding data management features and the support for statistical distributions, which were considered better for the DES software. Regarding method-specific differences, interactions were modeled more straightforward using TA, benefiting from its compositional model structure.

CONCLUSIONS

Both techniques prove suitable for modeling personalized treatment decisions, although DES would be preferred given the current software-specific limitations of TA. When these limitations are resolved, TA would be an interesting modeling alternative if interactions are key or its compositional structure is useful to manage multi-agent complex problems.

Can Economic Model Transparency Improve Provider Interpretation of Cost-effectiveness Analysis? Evaluating Tradeoffs Presented by the Second Panel on Cost-effectiveness in Health and Medicine

The Second Panel on Cost-Effectiveness in Health and Medicine convened on December 7, 2016 at the National Academy of Medicine to disseminate their recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses (CEAs). Following its summary, panel proceedings included lengthy discussions including the field's struggle to disseminate findings efficiently through peer-reviewed literature to target audiences. With editors of several medical and outcomes research journals in attendance, there was consensus that findings of cost-effectiveness analyses do not effectively reach other researchers or health care providers. The audience members suggested several solutions including providing additional training to clinicians in cost-effectiveness research and requiring that cost-effectiveness models are made publicly available. However, there remains the questions of whether making economic modelers' work open-access through journals is fair under the defense that these models remain one's own intellectual property, or whether journals can properly manage the peer-review process specifically for cost-effectiveness analyses. In this article, we elaborate on these issues and provide some suggested solutions that may increase the dissemination and application of cost-effectiveness literature to reach its intended audiences and ultimately benefit the patient. Ultimately, it is our combined view as economic modelers and clinicians that cost-effectiveness results need to reach the clinician to improve the efficiency of medical practice, but that open-access models do not improve clinician access or interpretation of the economics of medicine.

Cost-effectiveness of methods in personalized medicine. Results of a decision-analytic model in patients with acute myeloid leukemia with normal karyotype

BACKGROUND

During the last years, molecular genetic data are increasingly used as prognostic and predictive factors in acute myeloid leukemia (AML). The molecular genetic profile permits a rapid risk categorization and beyond that a prediction of differential treatment efficacy of post-remission chemotherapy versus an allogeneic hematopoietic cell transplantation (HCT) in specific subgroups.

METHODS

The aim of this study was to evaluate cost-effectiveness of two different strategies of risk categorization (conventional cytogenetic diagnostics (CCD) versus molecular genetic diagnostics (MGD)) in patients with AML, using a decision-analytic state-transition model. The model is run as (Monte Carlo) microsimulation in which individuals pass through in cycles with a cycle length of one month and a time horizon of ten years.

FINDINGS

Results show that on average, individuals within the MGD group generated about US$ 32,000 higher costs but survived about seven months longer than individuals within the CCD group. This leads to an Incremental Cost-Effectiveness Ratio (ICER) of about US$ 4928 per survived month.

INTERPRETATION

With a GDP (Gross Domestic Product) of US$ 26,467 (€ 33,630) per capita in Germany in 2012, the base-case ICER of US$ 4928 per survived month projected to US$ 59,136 per survived year is in between the simple GDP and the three times GDP per capita.

A systematic review of health economic evaluation in adjuvant breast radiotherapy: Quality counted by numbers

BACKGROUND

Evolving practice in adjuvant breast radiotherapy inevitably impacts healthcare budgets. This is reflected in a rise of health economic evaluations (HEE) in this domain. The available HEE literature was analysed qualitatively and quantitatively, using available instruments.

METHODS

HEEs published between 1/1/2000 and 31/10/2016 were retrieved through a systematic search in Medline, Cochrane and Embase. A quality-assessment using CHEERS (Consolidated Health Economic Evaluation Reporting Standards) was translated into a quantitative score and compared with Tufts Medical Centre CEA registry and Quality of Health Economic Studies (QHES) results.

RESULTS

Twenty cost-effectiveness analyses (CEA) and thirteen cost comparisons (CC) were analysed. In qualitative evaluation, valuation or justification of data sources, population heterogeneity and discussion on generalizability, in addition to declaration on funding, were often absent or incomplete. After quantification, the average CHEERS-scores were 74% (CI 66.9-81.1%) and 75.6% (CI 70.7-80.5%) for CEAs and CCs respectively. CEA-scores did not differ significantly from Tufts and QHES-scores.

CONCLUSION

Quantitative CHEERS evaluation is feasible and yields comparable results to validated instruments. HEE in adjuvant breast radiotherapy is of acceptable quality, however, further efforts are needed to improve comprehensive reporting of all data, indispensable for assessing relevance, reliability and generalizability of results.

Cost-Utility of Partially Implantable Active Middle Ear Implants for Sensorineural Hearing Loss: A Decision Analysis

BACKGROUND

Partially implantable active middle ear implants (aMEIs) offer a solution for individuals who have mild to severe sensorineural hearing loss and an outer ear medical condition that precludes the use of hearing aids. When otherwise left untreated, individuals report a lower quality of life, which may further decrease with increasing disability. In the lack of cost-effectiveness studies and long-term data, there is a need for decision modeling.

OBJECTIVE

To explore individual-level variance in resource utilization patterns following aMEI implantation.

METHODS

A Markov model was developed and analyzed as microsimulation to estimate the incremental cost utility ratio (ICUR) of partially implantable aMEIs compared with no (surgical) intervention in individuals with sensorineural hearing loss and an outer ear medical condition in Australia. Cost data were derived mostly from the Medicare Benefit Schedule and effectiveness data from published literature. A third-party payer perspective was adopted, and a 5% discount rate was applied over a 10-year time horizon.

RESULTS

Compared with baseline strategy, aMEIs yielded an incremental cost of Australian dollars (AUD) 13,339.18, incremental quality-adjusted life-year (QALY) of 1.35, and an ICUR of AUD 9,913.72/QALY. Of the respective number of simulated patients who visited each health state, 75.73% never had a minor adverse event, 99.82% did not experience device failure, and 97.75% did not cease to use their aMEIs. Probabilistic sensitivity analyses showed the ICUR to differ by only 0.95%.

CONCLUSIONS

In the Australian setting, partially implantable aMEIs offer a safe and cost-effective solution compared with no intervention and are also well accepted by users.

Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies

In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An expert consultation hosted by WHO, a survey of modellers and users of modelling studies, and literature reviews informed the development of recommendations on when and how to incorporate the results of modelling studies into WHO guidelines. In this article, we argue that modelling studies should routinely be considered in the process of developing WHO guidelines, but particularly in the evaluation of public health programmes, long-term effectiveness or comparative effectiveness.  There should be a systematic and transparent approach to identifying relevant published models, and to commissioning new models.  We believe that the inclusion of evidence from modelling studies into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process is possible and desirable, with relatively few adaptations.  No single "one-size-fits-all" approach is appropriate to assess the quality of modelling studies. The concept of the 'credibility' of the model, which takes the conceptualization of the problem, model structure, input data, different dimensions of uncertainty, as well as transparency and validation into account, is more appropriate than 'risk of bias'.

Developing WHO guidelines: Time to formally include evidence from mathematical modelling studies

In recent years, the number of mathematical modelling studies has increased steeply. Many of the questions addressed in these studies are relevant to the development of World Health Organization (WHO) guidelines, but modelling studies are rarely formally included as part of the body of evidence. An expert consultation hosted by WHO, a survey of modellers and users of modelling studies, and literature reviews informed the development of recommendations on when and how to incorporate the results of modelling studies into WHO guidelines. In this article, we argue that modelling studies should routinely be considered in the process of developing WHO guidelines, but particularly in the evaluation of public health programmes, long-term effectiveness or comparative effectiveness.  There should be a systematic and transparent approach to identifying relevant published models, and to commissioning new models.  We believe that the inclusion of evidence from modelling studies into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) process is possible and desirable, with relatively few adaptations.  No single "one-size-fits-all" approach is appropriate to assess the quality of modelling studies. The concept of the 'credibility' of the model, which takes the conceptualization of the problem, model structure, input data, different dimensions of uncertainty, as well as transparency and validation into account, is more appropriate than 'risk of bias'.

Cost-Effectiveness of Different Population Screening Strategies for Hereditary Haemochromatosis in Australia

INTRODUCTION

Amongst populations of northern European ancestry, HFE-associated haemochromatosis is a common genetic disorder characterised by iron overload. In the absence of treatment, excess iron is stored in parenchymal tissues, causing morbidity and mortality. Population screening programmes may increase early diagnosis and reduce associated disease. No contemporary health economic evaluation has been published for Australia. The objective of this study was to identify cost-effective screening strategies for haemochromatosis in the Australian setting.

METHODS

A Markov model using probabilistic decision analysis was developed comparing four adult screening strategies: the status quo (cascade and incidental screening), genotyping with blood and buccal samples and transferrin saturation followed by genotyping (TfS). Target populations were males (30 years) and females (45 years) of northern European ancestry. Cost-effectiveness was estimated from the government perspective over a lifetime horizon.

RESULTS

All strategies for males were cost-effective compared to the status quo. The incremental costs (standard deviation) associated with genotyping (blood) were AUD7 (56), TfS AUD15 (45) and genotyping (buccal) AUD63 (56), producing ICERs of AUD1673, 4103 and 15,233/quality-adjusted life-year (QALY) gained, respectively. For females, only the TfS strategy was cost-effective, producing an ICER of AUD10,195/QALY gained. Approximately 3% of C282Y homozygotes were estimated to be identified with the status quo approach, compared with 40% with the proposed screening strategies.

CONCLUSION

This model estimated that genotyping and TfS strategies are likely to be more cost-effective screening strategies than the status quo.

A Comparison of Agent-Based Models and the Parametric G-Formula for Causal Inference

Decision-making requires choosing from treatments on the basis of correctly estimated outcome distributions under each treatment. In the absence of randomized trials, 2 possible approaches are the parametric g-formula and agent-based models (ABMs). The g-formula has been used exclusively to estimate effects in the population from which data were collected, whereas ABMs are commonly used to estimate effects in multiple populations, necessitating stronger assumptions. Here, we describe potential biases that arise when ABM assumptions do not hold. To do so, we estimated 12-month mortality risk in simulated populations differing in prevalence of an unknown common cause of mortality and a time-varying confounder. The ABM and g-formula correctly estimated mortality and causal effects when all inputs were from the target population. However, whenever any inputs came from another population, the ABM gave biased estimates of mortality-and often of causal effects even when the true effect was null. In the absence of unmeasured confounding and model misspecification, both methods produce valid causal inferences for a given population when all inputs are from that population. However, ABMs may result in bias when extrapolated to populations that differ on the distribution of unmeasured outcome determinants, even when the causal network linking variables is identical.