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

OBJECTIVES: The cardiovascular outcomes challenge examined the predictive accuracy of 10 diabetes models in estimating hard outcomes in 2 recent cardiovascular outcomes trials (CVOTs) and whether recalibration can be used to improve replication. METHODS: Participating groups were asked to reproduce the results of the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients (EMPA-REG OUTCOME) and the Canagliflozin Cardiovascular Assessment Study (CANVAS) Program. Calibration was performed and additional analyses assessed model ability to replicate absolute event rates, hazard ratios (HRs), and the generalizability of calibration across CVOTs within a drug class. RESULTS: Ten groups submitted results. Models underestimated treatment effects (ie, HRs) using uncalibrated models for both trials. Calibration to the placebo arm of EMPA-REG OUTCOME greatly improved the prediction of event rates in the placebo, but less so in the active comparator arm. Calibrating to both arms of EMPA-REG OUTCOME individually enabled replication of the observed outcomes. Using EMPA-REG OUTCOME-calibrated models to predict CANVAS Program outcomes was an improvement over uncalibrated models but failed to capture treatment effects adequately. Applying canagliflozin HRs directly provided the best fit. CONCLUSIONS: The Ninth Mount Hood Diabetes Challenge demonstrated that commonly used risk equations were generally unable to capture recent CVOT treatment effects but that calibration of the risk equations can improve predictive accuracy. Although calibration serves as a practical approach to improve predictive accuracy for CVOT outcomes, it does not extrapolate generally to other settings, time horizons, and comparators. New methods and/or new risk equations for capturing these CV benefits are needed.

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

OBJECTIVES: The Eighth Mount Hood Challenge (held in St. Gallen, Switzerland, in September 2016) evaluated the transparency of model input documentation from two published health economics studies and developed guidelines for improving transparency in the reporting of input data underlying model-based economic analyses in diabetes. METHODS: Participating modeling groups were asked to reproduce the results of two published studies using the input data described in those articles. Gaps in input data were filled with assumptions reported by the modeling groups. Goodness of fit between the results reported in the target studies and the groups' replicated outputs was evaluated using the slope of linear regression line and the coefficient of determination (R2). After a general discussion of the results, a diabetes-specific checklist for the transparency of model input was developed. RESULTS: Seven groups participated in the transparency challenge. The reporting of key model input parameters in the two studies, including the baseline characteristics of simulated patients, treatment effect and treatment intensification threshold assumptions, treatment effect evolution, prediction of complications and costs data, was inadequately transparent (and often missing altogether). Not surprisingly, goodness of fit was better for the study that reported its input data with more transparency. To improve the transparency in diabetes modeling, the Diabetes Modeling Input Checklist listing the minimal input data required for reproducibility in most diabetes modeling applications was developed. CONCLUSIONS: Transparency of diabetes model inputs is important to the reproducibility and credibility of simulation results. In the Eighth Mount Hood Challenge, the Diabetes Modeling Input Checklist was developed with the goal of improving the transparency of input data reporting and reproducibility of diabetes simulation model results.

Multivariate Prediction Equations for HbA1c Lowering, Weight Change, and Hypoglycemic Events Associated with Insulin Rescue Medication in Type 2 Diabetes Mellitus: Informing Economic Modeling.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is chronic and progressive and the cost-effectiveness of new treatment interventions must be established over long time horizons. Given the limited durability of drugs, assumptions regarding downstream rescue medication can drive results. Especially for insulin, for which treatment effects and adverse events are known to depend on patient characteristics, this can be problematic for health economic evaluation involving modeling. OBJECTIVES: To estimate parsimonious multivariate equations of treatment effects and hypoglycemic event risks for use in parameterizing insulin rescue therapy in model-based cost-effectiveness analysis. METHODS: Clinical evidence for insulin use in T2DM was identified in PubMed and from published reviews and meta-analyses. Study and patient characteristics and treatment effects and adverse event rates were extracted and the data used to estimate parsimonious treatment effect and hypoglycemic event risk equations using multivariate regression analysis. RESULTS: Data from 91 studies featuring 171 usable study arms were identified, mostly for premix and basal insulin types. Multivariate prediction equations for glycated hemoglobin A1c lowering and weight change were estimated separately for insulin-naive and insulin-experienced patients. Goodness of fit (R2) for both outcomes were generally good, ranging from 0.44 to 0.84. Multivariate prediction equations for symptomatic, nocturnal, and severe hypoglycemic events were also estimated, though considerable heterogeneity in definitions limits their usefulness. CONCLUSIONS: Parsimonious and robust multivariate prediction equations were estimated for glycated hemoglobin A1c and weight change, separately for insulin-naive and insulin-experienced patients. Using these in economic simulation modeling in T2DM can improve realism and flexibility in modeling insulin rescue medication.

The cost-effectiveness of different chemotherapy strategies for patients with poor prognosis advanced colorectal cancer (MRC FOCUS).

OBJECTIVES: To assess the value for money of alternative chemotherapy strategies for managing advanced colorectal cancer using irinotecan or oxaliplatin, either in sequence or in combination with fluorouracil. METHODS: A cost-effectiveness model was developed using data from the U.K. fluorouracil, oxaliplatin, and CPT11 (irinotecan)--use and sequencing (FOCUS) trial. The analysis adopted the perspective of the U.K. National Health Service. Input parameters were derived using a system of risk equations (for probabilities), count data regression models (for resource use), and generalized linear models (for utilities). Parameter estimates were obtained using Markov chain Monte Carlo methods, propagating the simulation values through the state-transition model to characterize appropriately the joint distributions of expected cost, survival and quality-adjusted life years for each treatment strategy. An acceptability frontier was used to represent the probability that the optimal option is cost-effective at different values of the cost-effectiveness threshold. RESULTS: The base-case analysis used drug unit costs provided by a typical English hospital. First-line doublet therapy combination therapy fluorouracil (5FU) plus irinotecan was the most cost-effective strategy at standard thresholds, with an incremental cost-effectiveness ratio (ICER) of £14,877 (pound sterling) compared with first-line 5FU until treatment failure followed by single agent irinotecan. Other strategies were all subject to extended dominance. A sensitivity analysis using published drug (list) prices found the most cost-effective strategy would be first-line fluorouracil until failure followed by 5FU plus irinotecan (ICER: £19,753). CONCLUSIONS: The combination of 5FU and irinotecan (whether used first or second line) appears to be more cost-effective than the single agent sequential therapies used in the FOCUS trial, or 5FU plus oxaliplatin.

Cost-effectiveness of oral triptans for acute migraine: mixed treatment comparison.

BACKGROUND: The cost-effectiveness of triptans in the treatment of migraine has not been assessed since generic sumatriptan entered the Finnish market in 2008. METHODS: Using systematic review and mixed treatment comparison, the effectiveness of triptans was estimated with regard to 2-hour response, 2-hour pain-free, recurrence, and any adverse event, using published clinical data. Direct and indirect costs (2010 EUR, societal perspective) and quality-adjusted life-years (QALYs) were evaluated over one acute migraine attack using a decision-tree model. RESULTS: The meta-analysis combined data from fifty-six publications. The highest probability of achieving the primary outcome, "sustained pain-free, no adverse event" (SNAE), was estimated for eletriptan 40 mg (20.9 percent). Sumatriptan 100 mg was the treatment with lowest estimated costs (€20.86), and the incremental cost-effectiveness ratio of eletriptan 40 mg compared with sumatriptan 100 mg was €43.65 per SNAE gained (€19,659 per QALY gained). CONCLUSION: Depending on the decision-maker's willingness-to-pay threshold, either sumatriptan 100 mg or eletriptan 40 mg is likely to be cost-effective.

Advantages in Management and Remote Monitoring of Intravenous Therapy: Exploratory Survey and Economic Evaluation of Gravity-Based Infusions in Finland.

INTRODUCTION: Intravenous infusion therapy is a common and challenging invasive treatment procedure in hospital wards. Administration mistakes can have serious, even life-threatening, consequences. The Monidor solution was developed to help nurses administer gravity-based infusions and monitor them remotely, to avoid complications and reduce workload. Its real-world effects and economic consequences were unknown. METHODS: An exploratory survey was carried out to estimate the potential impact of the Monidor solution on events and nurse time use. At the end of their shift, nurses estimated effects in terms of routine room visits avoided, prevention of complications, and impact on nurse time requirements. Linear regression was applied to estimate predictors of time freed. A health economic model was developed to evaluate economic consequences and to calculate the net return on investment for a hypothetical hospital ward. A 1-month time horizon was used, and discounting was not applied. RESULTS: A total of 216 responses were obtained from 6 Finnish hospitals, from a total of 15 wards, and 56.3% of nurses found that the Monidor solution freed nurse time, while < 3.5% experienced additional time requirements. Per nurse shift, the Monidor solution avoided on average 2.064 routine room visits, helped detect end of infusion 1.340 times, and led to 5.045 min of time freed. One routine visit avoided was associated with 2.453 min of time freed in the linear regression. In the conservative setting, the freed monthly capacity in the hypothetical ward amounted to €1270.90 per month (year 2021), yielding a return on investment of 2.63. Uncertainty of linear regression coefficient values was identified as a driver of uncertainty in sensitivity analysis, with return on investment ranging from 1.55 to 3.71. CONCLUSIONS: The study demonstrated that management and remote monitoring with the Monidor solution frees nurse time and reduces routine activities associated with gravity-based intravenous infusions. These findings could be confirmed in a comparative empirical study.

In hospitals, patients often receive fluids intravenously. These fluids enter the blood circulation directly, and their incorrect administration (too much or too little, too slow or too fast) can have serious and potentially life-threatening consequences. The Monidor solution aims to improve administration of intravenous fluids. It consists of two components: a mobile app for remote monitoring and a meter for bedside management. This study aimed to estimate the impact of the Monidor solution on administration of intravenous fluids and to assess how the Monidor solution would affect costs. Among the factors considered were the price of the devices, nurse time freed, and prevention of complications with the intravenous therapies. The data were collected via questionnaires from nurses from 15 wards in 6 Finnish hospitals. According to the responses and a health economic model designed for this study, the Monidor solution freed capacity with a value of €1270.90 per month. When considering the local cost of the Monidor solution, the return on investment was positive. In summary, the Monidor solution is cost-effective; routine room visits by nurses were avoided, problems with infusions were detected earlier, and nurse time was freed. These findings could be confirmed in a larger study.

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

BACKGROUND: Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models. METHODS: Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences. RESULTS: Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (-0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models (P = 0.049). CONCLUSIONS: Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions.HighlightsThe findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs).There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.

Cost-effectiveness of infliximab for the treatment of active and progressive psoriatic arthritis.

BACKGROUND: Despite its proven efficacy, infliximab is often considered to be an expensive treatment for patients with psoriatic arthritis. OBJECTIVES: To estimate the cost-effectiveness of infliximab among patients with active and progressive psoriatic arthritis. METHODS: A decision analytic model was constructed to simulate disease progression in hypothetical cohorts of patients with psoriatic arthritis receiving infliximab maintenance treatment. The primary response measure was change in Health Assessment Questionnaire score from a baseline estimated from mixed treatment models drawn from published clinical trials. Palliative care, comprising nonbiologic disease-modifying antirheumatic drugs, was used as a comparator. The primary outcome was quality-adjusted life years. The dose of infliximab was estimated for a range of 60 to 80 kg per patient body weight. The costs and outcomes were discounted at 3.5% for a period of 40 years. Uncertainty around the results was explored with probabilistic sensitivity analysis. RESULTS: The mixed treatment comparison showed a significant reduction in Health Assessment Questionnaire score across all patients. The tumor necrosis factor α inhibitors were significantly superior to palliative care but comparable with one another. The incremental cost-effectiveness ratios for etanercept, adalimumab, and infliximab relative to palliative care were £17,327; £19,246; and £16,942 to £23,022, respectively, across all patients with psoriatic arthritis and £16,613; £18,170; and £15,788 to £21,736, respectively, in the subgroup with significant psoriasis. CONCLUSION: Infliximab represents a cost-effective treatment option well within the National Institute for Health and Clinical Excellence threshold relative to palliative care. In light of equivalent outcomes with other tumor necrosis factor α inhibitors, its position in the treatment pathway is likely to be governed by treatment costs.

Short-course adjuvant trastuzumab therapy in early stage breast cancer in Finland: cost-effectiveness and value of information analysis based on the 5-year follow-up results of the FinHer Trial.

BACKGROUND: Trastuzumab is a standard treatment of HER2-positive early breast cancer in many countries, and it is usually given as a one year adjuvant treatment. However, its cost-effectiveness has not been assessed in Finland. The Finland Herceptin (FinHer) trial has compared a shorter 9-week treatment protocol against no trastuzumab with promising results. The aim of this study was to assess the potential cost-effectiveness of the 9-week treatment based on the recently published five-year follow-up results of the FinHer trial. METHODS: An evaluation model of breast cancer treatment was constructed using fitted survival estimates and a long-term Markov model. The cost-effectiveness of 9-week adjuvant treatment was assessed in a Finnish setting, compared to treatment without trastuzumab. The analysis was performed from a societal perspective, and a 3% discount rate was applied for future costs and outcomes. Value of information analysis was performed to estimate the potential value of further research. RESULTS: According to the probabilistic analysis, the incremental cost-effectiveness ratio was €12 000 per quality adjusted life year (QALY), and €9300 per life year gained (LYG), when comparing adjuvant trastuzumab therapy to standard treatment without trastuzumab. The modelled incremental outcomes for trastuzumab treatment were 0.66 QALY and 0.85 LYG for a lifetime perspective. Value of information analysis showed that additional research on treatment effects would be most valuable for reducing uncertainty in the adoption decision. CONCLUSIONS: Adjuvant 9-week trastuzumab is likely to be a cost-effective treatment in the Finnish setting. Results from an ongoing trial comparing adjuvant 9-week treatment with the 12-month treatment will play a key role in addressing the uncertainty related to the treatment effect and potential cost-effectiveness of these two treatment protocols.

[Indirect comparison and network meta-analyses--new tools for the assessment of evidence on the relative efficacy of drugs]. / Epäsuora vertailu ja verkostometa-analyysit --uudet työkalut lääkkeiden suhteellisen tehon ja vaikuttavuuden arviointiin.

Meta-analysis allows the quantitative combination of results of multiple studies that address similar research questions. Traditional meta-analysis of studies involving a direct comparison of two treatment alternatives can be applied to estimate the overall relative efficacy of these two treatment alternatives. All treatment options relevant to practical treatment decisions are, however, not always compared directly against each other in clinical studies, but indirect comparison via a common comparator may be possible. To use all relevant evidence from both direct and indirect comparisons of treatment options, advanced methods of meta-analysis have been developed. These so-called network meta-analyses extend the traditional meta-analysis to cases where a network of studies enables different pair-wise direct and indirect comparisons between multiple treatment alternatives, thereby forming a network of relevant evidence.

Macrovascular Risk Equations Based on the CANVAS Program.

BACKGROUND: Widely used risk equations for cardiovascular outcomes for individuals with type 2 diabetes mellitus (T2DM) have been incapable of predicting cardioprotective effects observed in recent cardiovascular outcomes trials (CVOTs) involving individuals with T2DM at high risk for or with established cardiovascular disease (CVD). OBJECTIVE: We developed cardiovascular and mortality risk equations using patient-level data from the CANVAS (CANagliflozin cardioVascular Assessment Study) Program to address this shortcoming. METHODS: Data from 10,142 patients with T2DM at high risk for or with established CVD, randomized to canagliflozin + standard of care (SoC) or SoC alone and followed for a mean duration of 3.6 years in the CANVAS Program were used to derive parametric risk equations for myocardial infarction (MI), stroke, hospitalization for heart failure (HHF), and death. Accumulated knowledge from the widely used UKPDS-OM2 (United Kingdom Prospective Diabetes Study Outcomes Model 2) was leveraged, and any departures in parameterization were limited to those necessary to provide adequate goodness of fit. Candidate explanatory covariates were selected using only the placebo arm to minimize confounding effects. Internal validation was performed separately by study treatment arm. RESULTS: UKPDS-OM2 predicted CANVAS Program outcomes poorly. Recalibrating UKPDS-OM2 intercepts improved calibration in some cases. Refitting the coefficients but otherwise preserving the UKPDS-OM2 structure improved the fit substantially, which was sufficient for stroke and death. For MI, reselecting UKPDS-OM2 covariates and functional form proved sufficient. For HHF, selection from a broad set of candidate covariates and inclusion of a canagliflozin indicator was required. CONCLUSION: These risk equations address some of the limitations of widely used risk equations, such as the UKPDS-OM2, for modeling cardioprotective treatments for individuals with T2DM and high cardiovascular risk, including derivation from overly healthy patients treated with agents that lack cardioprotection and have been described as reflecting a different therapeutic era. Future work is needed to examine external validity.

Cost-Effectiveness of Apixaban versus Other Direct Oral Anticoagulants and Warfarin in the Prevention of Thromboembolic Complications Among Finnish Patients with Non-Valvular Atrial Fibrillation.

PURPOSE: Direct oral anticoagulant (DOAC) use for the prevention of thromboembolic complications in patients with non-valvular atrial fibrillation (AF) has increased steadily in Finland. DOACs have been shown to be cost-effective in comparison to warfarin, but published evidence of relative cost-effectiveness between DOACs is still scarce and mostly based on indirect comparisons of clinical trial evidence. The aim of this study was to compare the cost-effectiveness of apixaban to dabigatran, rivaroxaban and warfarin in a Finnish setting using real-life evidence where available. PATIENTS AND METHODS: A lifetime Markov simulation model used previously in a published Finnish assessment comparing apixaban and warfarin was modified and updated with the relative effectiveness and safety data available from the real-world NAXOS-study and representative Finnish input data for patient characteristics, event risks, mortality, resource use, costs, and quality of life. Apixaban's cost-effectiveness was assessed from health care payer perspective (using 3% per year discount rate) based on incremental cost-effectiveness ratio (ICER, cost per quality-adjusted life year [QALY] gained), probability of cost-effectiveness (at willingness-to-pay [WTP] of 35,000 euros/QALY), and net monetary benefit (NMB). RESULTS: Apixaban increased the average modelled quality-adjusted life-expectancy and reduced the average total health care costs of AF patients when compared to warfarin (+0.14 QALYs, -3691 euros), dabigatran (+0.11 QALYs, -404 euros), and rivaroxaban (+0.03 QALYs, -43 euros). The resulting NMB of apixaban versus warfarin, dabigatran and rivaroxaban was 8723, 4168, and 1129 euros, respectively. The respective probabilities of apixaban being cost-effective against each comparator were 100%, 92.7%, and 64.0%. CONCLUSION: In this modelling study, apixaban dominated other anticoagulants in the Finnish real-life setting.

Development and Internal Validation of a Discrete Event Simulation Model of Diabetic Kidney Disease Using CREDENCE Trial Data.

INTRODUCTION: The Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) study showed that compared with placebo, canagliflozin 100 mg significantly reduced the risk of major cardiovascular events and adverse renal outcomes in patients with diabetic kidney disease (DKD). We developed a simulation model that can be used to estimate the long-term health and economic consequences of DKD treatment interventions for patients matching the CREDENCE study population. METHODS: The CREDENCE Economic Model of DKD (CREDEM-DKD) was developed using patient-level data from CREDENCE (which recruited patients with estimated glomerular filtration rate 30 to < 90 mL/min/1.73 m2, urinary albumin to creatinine ratio > 300-5000 mg/g, and taking the maximum tolerated dose of a renin-angiotensin-aldosterone system inhibitor). Risk prediction equations were fit for start of maintenance dialysis, doubling of serum creatinine, hospitalization for heart failure, nonfatal myocardial infarction, nonfatal stroke, and all-cause mortality. A micro-simulation model was constructed using these risk equations combined with user-definable kidney transplant event risks. Internal validation was performed by loading the model to replicate the CREDENCE study and comparing predictions with trial Kaplan-Meier estimate curves. External validation was performed by loading the model to replicate a subgroup of the CANagliflozin cardioVascular Assessment Study (CANVAS) Program with patient characteristics that would have qualified for inclusion in CREDENCE. RESULTS: Risk prediction equations generally fit well and exhibited good concordance, especially for the placebo arm. In the canagliflozin arm, modest underprediction was observed for myocardial infarction, along with overprediction of dialysis, doubling of serum creatinine, and all-cause mortality. Discrimination was strong (0.85) for the renal outcomes, but weaker for the macrovascular outcomes and all-cause mortality (0.60-0.68). The model performed well in internal and external validation exercises. CONCLUSION: CREDEM-DKD is an important new tool in the evaluation of treatment interventions in the DKD population. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02065791.

Conducting and interpreting results of network meta-analyses in type 2 diabetes mellitus: A review of network meta-analyses that include sodium glucose co-transporter 2 inhibitors.

AIMS: Network meta-analyses (NMAs) are valuable ways to generate comparative effectiveness data for therapies available to treat type 2 diabetes mellitus (T2DM). This review assesses NMAs that evaluate sodium glucose co-transporter 2 (SGLT2) inhibitors for treatment of T2DM and discusses potential issues in conducting and interpreting NMAs. METHODS: A systematic literature search was conducted on September 13, 2018 using the search terms "network meta-analysis," "SGLT2," variations of these terms, and individual SGLT2 inhibitor names. Extracted data included NMA objectives, methods, target populations, treatments, study endpoints, length of follow-up, and funding. Differences between NMAs were investigated. RESULTS: Thirty-five full-length publications met criteria for inclusion. In most NMAs, the target population was defined by therapeutic regimen (e.g., combination with metformin). Follow-up intervals permitted in NMAs varied considerably (range, 4-208 weeks). Twenty-nine NMAs included dapagliflozin, 28 evaluated canagliflozin, and 27 evaluated empagliflozin. Nine NMAs used frequentist methods; 16 used Bayesian methods. Six NMAs were funded by pharmaceutical manufacturers. Heterogeneity across NMAs was seen in scope, time frame, and other aspects of analytic design. CONCLUSIONS: Although this review indicates that methodological guidelines for reporting NMAs were generally followed, it also emphasizes the need for T2DM-specific guidance requiring clear reporting of NMA scope and objectives to aid appropriate interpretation and use of NMA results.

Challenges and Opportunities Associated with Incorporating New Evidence of Drug-Mediated Cardioprotection in the Economic Modeling of Type 2 Diabetes: A Literature Review.

INTRODUCTION: Cardiovascular disease is a leading cause of mortality in people with type 2 diabetes mellitus (T2DM). Beginning in 2015, long-term cardiovascular outcomes trials (CVOTs) have reported cardioprotective benefits for two classes of diabetes drugs. In addition to improving the lives of patients, these health benefits affect relative value (i.e., cost-effectiveness) of these agents compared with each other and especially compared with other agents. While long-term CVOT data on hard outcomes are a great asset, economic modeling of the value of this cardioprotection faces many new empirical challenges. The aim of this study was to identify different approaches used to incorporate drug-mediated cardioprotection into T2DM economic models, to identify pros and cons of these approaches, and to highlight additional considerations. METHODS: A review of T2DM modeling applications (manuscript or conference abstracts) that included direct cardioprotective effects was conducted from January 2015 to September 2018. Model applications were classified on the basis of the mechanism used to model cardioprotection [i.e., directly via hazard ratios (HRs) for cardiovascular outcomes or indirectly via biomarker mediation]. Details were extracted and the studies were evaluated. RESULTS: Five full-length articles and 16 conference abstracts (of which 11 posters were found) qualified for study inclusion. While the approaches used were diverse, the five full-length publications and all but two of the abstracts modeled cardioprotection used direct HRs from the relevant CVOT. The remaining two posters modeled cardioprotection using CVOT HRs in combination with treatment effects mediated through known risk factors. CONCLUSION: The classification of empirical methods in cardioprotection was intended to facilitate a better understanding of the pros and cons of different methodologies. A substantial diversity was observed, though most used trial HRs directly. Given the differences observed, we believe that diabetes modelers and other stakeholders can benefit from a formal discussion and evolving consensus. FUNDING: Janssen Global Services, LLC (Raritan, NJ, USA).

Sensitivity to assumptions in models of generalist predation on a cyclic prey.

Ecological theory predicts that generalist predators should damp or suppress long-term periodic fluctuations (cycles) in their prey populations and depress their average densities. However, the magnitude of these impacts is likely to vary depending on the availability of alternative prey species and the nature of ecological mechanisms driving the prey cycles. These multispecies effects can be modeled explicitly if parameterized functions relating prey consumption to prey abundance, and realistic population dynamical models for the prey, are available. These requirements are met by the interaction between the Hen Harrier (Circus cyaneus) and three of its prey species in the United Kingdom, the Meadow Pipit (Anthus pratensis), the field vole (Microtus agrestis), and the Red Grouse (Lagopus lagopus scoticus). We used this system to investigate how the availability of alternative prey and the way in which prey dynamics are modeled might affect the behavior of simple trophic networks. We generated cycles in one of the prey species (Red Grouse) in three different ways: through (1) the interaction between grouse density and macroparasites, (2) the interaction between grouse density and male grouse aggressiveness, and (3) a generic, delayed density-dependent mechanism. Our results confirm that generalist predation can damp or suppress grouse cycles, but only when the densities of alternative prey are low. They also demonstrate that diametrically opposite indirect effects between pairs of prey species can occur together in simple systems. In this case, pipits and grouse are apparent competitors, whereas voles and grouse are apparent facilitators. Finally, we found that the quantitative impacts of the predator on prey density differed among the three models of prey dynamics, and these differences were robust to uncertainty in parameter estimation and environmental stochasticity.

Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM).

BACKGROUND: The Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM) was developed to address study questions pertaining to the cost-effectiveness of treatment alternatives in the care of patients with type 2 diabetes mellitus (T2DM). Naturally, the usefulness of a model is determined by the accuracy of its predictions. A previous version of ECHO-T2DM was validated against actual trial outcomes and the model predictions were generally accurate. However, there have been recent upgrades to the model, which modify model predictions and necessitate an update of the validation exercises. OBJECTIVES: The objectives of this study were to extend the methods available for evaluating model validity, to conduct a formal model validation of ECHO-T2DM (version 2.3.0) in accordance with the principles espoused by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), and secondarily to evaluate the relative accuracy of four sets of macrovascular risk equations included in ECHO-T2DM. METHODS: We followed the ISPOR/SMDM guidelines on model validation, evaluating face validity, verification, cross-validation, and external validation. Model verification involved 297 'stress tests', in which specific model inputs were modified systematically to ascertain correct model implementation. Cross-validation consisted of a comparison between ECHO-T2DM predictions and those of the seminal National Institutes of Health model. In external validation, study characteristics were entered into ECHO-T2DM to replicate the clinical results of 12 studies (including 17 patient populations), and model predictions were compared to observed values using established statistical techniques as well as measures of average prediction error, separately for the four sets of macrovascular risk equations supported in ECHO-T2DM. Sub-group analyses were conducted for dependent vs. independent outcomes and for microvascular vs. macrovascular vs. mortality endpoints. RESULTS: All stress tests were passed. ECHO-T2DM replicated the National Institutes of Health cost-effectiveness application with numerically similar results. In external validation of ECHO-T2DM, model predictions agreed well with observed clinical outcomes. For all sets of macrovascular risk equations, the results were close to the intercept and slope coefficients corresponding to a perfect match, resulting in high R 2 and failure to reject concordance using an F test. The results were similar for sub-groups of dependent and independent validation, with some degree of under-prediction of macrovascular events. CONCLUSION: ECHO-T2DM continues to match health outcomes in clinical trials in T2DM, with prediction accuracy similar to other leading models of T2DM.

Modeled Health Economic Impact of a Hypothetical Certolizumab Pegol Risk-Sharing Scheme for Patients with Moderate-to-Severe Rheumatoid Arthritis in Finland.

PURPOSE: To model the American College of Rheumatology (ACR) outcomes, cost-effectiveness, and budget impact of certolizumab pegol (CZP) (with and without a hypothetical risk-sharing scheme at treatment initiation for biologic-naïve patients) versus the current mix of reimbursed biologics for treatment of moderate-to-severe rheumatoid arthritis (RA) in Finland. METHODS: A probabilistic model with 12-week cycles and a societal approach was developed for the years 2015-2019, accounting for differences in ACR responses (meta-analysis), mortality, and persistence. The risk-sharing scheme included a treatment switch and refund of the costs associated with CZP acquisition if patients failed to achieve ACR20 response at week 12. For the current treatment mix, ACR20 at week 24 determined treatment continuation. Quality-adjusted life years were derived on the basis of the Health Utilities Index. RESULTS: In the Finnish target population, CZP treatment with a risk-sharing scheme led to a estimated annual net expenditure decrease ranging from 1.7% in 2015 to 5.6% in 2019 compared with the current treatment mix. Per patient over the 5 years, CZP risk sharing was estimated to decrease the time without ACR response by 5%-units, decrease work absenteeism by 24 days, and increase the time with ACR20, ACR50, and ACR70 responses by 5%-, 6%-, and 1%-units, respectively, with a gain of 0.03 quality-adjusted life years. The modeled risk-sharing scheme showed reduced costs of €7866 per patient, with a more than 95% probability of cost-effectiveness when compared with the current treatment mix. CONCLUSION: The present analysis estimated that CZP, with or without the risk-sharing scheme, is a cost-effective alternative treatment for RA patients in Finland. The surplus provided by the CZP risk-sharing scheme could fund treatment for 6% more Finnish RA patients. FUNDING: UCB Pharma.

Warfarin treatment among Finnish patients with atrial fibrillation: retrospective registry study based on primary healthcare data.

OBJECTIVE: To assess the frequency of warfarin use, the achieved international normalised ratio (INR) balance among warfarin users and the primary healthcare outpatient costs of patients with atrial fibrillation (AF). DESIGN: Retrospective, non-interventional registry study. SETTING: Primary healthcare. PARTICIPANTS: All patients with AF (n=2746) treated in one Finnish health centre between October 2010 and March 2012. METHODS: Data on healthcare resource use, warfarin use, individually defined target INR range and INR test results were collected from the primary healthcare database for patients with AF diagnosis. The analysed dataset consisted of a 1-year follow-up. Warfarin treatment balance was estimated with the proportion of time spent in the therapeutic INR range (TTR). The cost of used healthcare resources was valued separately with national and service provider unit costs to estimate the total outpatient treatment costs. The factors potentially impacting the treatment costs were assessed with a generalised linear regression model. RESULTS: Approximately 50% of the patients with AF with CHADS-VASc ≥1 used warfarin. The average TTR was 65.2% but increased to 74.5% among patients using warfarin continuously (ie, without gaps exceeding 56 days between successive INR tests) during follow-up. One-third of the patients had a TTR of below 60%. The average outpatient costs in the patient cohort were €314.44 with the national unit costs and €560.26 with the service provider unit costs. The costs among warfarin users were, on average, €524.11 or €939.54 higher compared with the costs among non-users, depending on the used unit costs. A higher TTR was associated with lower outpatient costs. CONCLUSIONS: The patients in the study centre using warfarin were, on average, well controlled on warfarin, yet one-third of patients had a TTR of below 60%.

Validation of economic and health outcomes simulation model of type 2 diabetes mellitus (ECHO-T2DM).

OBJECTIVE: This study constructed the Economic and Health Outcomes Model for type 2 diabetes mellitus (ECHO-T2DM), a long-term stochastic microsimulation model, to predict the costs and health outcomes in patients with T2DM. Naturally, the usefulness of the model depends upon its predictive accuracy. The objective of this work is to present results of a formal validation exercise of ECHO-T2DM. METHODS: The validity of ECHO-T2DM was assessed using criteria recommended by the International Society for Pharmacoeconomics and Outcomes Research/Society for Medical Decision Making (ISPOR/SMDM). Specifically, the results of a number of clinical trials were predicted and compared with observed study end-points using a scatterplot and regression approach. An F-test of the best-fitting regression was added to assess whether it differs statistically from the identity (45°) line defining perfect predictions. In addition to testing the full model using all of the validation study data, tests were also performed of microvascular, macrovascular, and survival outcomes separately. The validation tests were also performed separately by type of data (used vs not used to construct the model, economic simulations, and treatment effects). RESULTS: The intercept and slope coefficients of the best-fitting regression line between the predicted outcomes and corresponding trial end-points in the main analysis were -0.0011 and 1.067, respectively, and the R(2) was 0.95. A formal F-test of no difference between the fitted line and the identity line could not be rejected (p = 0.16). The high R(2) confirms that the data points are closely (and linearly) associated with the fitted regression line. Additional analyses identified that disagreement was highest for macrovascular end-points, for which the intercept and slope coefficients were 0.0095 and 1.225, respectively. The R(2) was 0.95 and the estimated intercept and slope coefficients were 0.017 and 1.048, respectively, for mortality, and the F-test was narrowly rejected (p = 0.04). The sub-set of microvascular end-points showed some tendency to over-predict (the slope coefficient was 1.095), although concordance between predictions and observed values could not be rejected (p = 0.16). LIMITATIONS: Important study limitations include: (1) data availability limited one to tests based on end-of-study outcomes rather than time-varying outcomes during the studies analyzed; (2) complex inclusion and exclusion criteria in two studies were difficult to replicate; (3) some of the studies were older and reflect outdated treatment patterns; and (4) the authors were unable to identify published data on resource use and costs of T2DM suitable for testing the validity of the economic calculations. CONCLUSIONS: Using conventional methods, ECHO-T2DM simulated the treatment, progression, and patient outcomes observed in important clinical trials with an accuracy consistent with other well-accepted models. Macrovascular outcomes were over-predicted, which is common in health-economic models of diabetes (and may be related to a general over-prediction of event rates in the United Kingdom Prospective Diabetes Study [UKPDS] Outcomes Model). Work is underway in ECHO-T2DM to incorporate new risk equations to improve model prediction.