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.

The health economics of calcium and vitamin D3 for the prevention of osteoporotic hip fractures in Sweden.

OBJECTIVE: The objective of this study was to examine the economics of administering calcium and vitamin D3 to post-menopausal women in Sweden. We focus primarily on the cost-effectiveness of treating older women for whom clear evidence of efficacy is available. We supplement this information, however, with estimates of the cost-effectiveness of treating certain high-risk groups of younger women, while acknowledging the greater uncertainty involved. METHODS: We developed a Markov model for analyzing the occurrence and timing of hip fractures, based almost entirely on peer-reviewed data from Sweden. In a 3-year randomized clinical trial, the combination of calcium and vitamin D3 was shown to reduce the risk of hip fractures by 27%. Costs for treating hip fractures were based on 1,080 women who were hospitalized in Stockholm. RESULTS: Treatment of 70-year-old women was cost saving at efficacy as low as two-thirds that seen in the clinical trials, and upwards. Even at modest rates of efficacy, treatment of the high-risk 50- and 60-year-old cohorts was generally cost-effective and in some cases even cost saving. Particularly cost-effective was treatment of women with identified osteoporosis or a maternal family history of hip fracture. CONCLUSION: Simulation results suggest a role for lifetime treatment of older women with calcium and vitamin D3 in Sweden. While there is more uncertainty underlying the treatment of younger women, our simulation results suggest that treatment may also be cost saving or at least cost-effective for many cohorts of high-risk 50- and particularly 60-year-old women, in particular those with osteoporosis or a maternal family history of hip fracture.