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Aim To estimate the cost‐effectiveness of sequential addition of empagliflozin versus sitagliptin after metformin in patients with type 2 diabetes (T2D) with or without cardiovascular disease (CVD) from the perspective of the US healthcare payer. Methods An individual simulation model predicted lifetime diabetes‐related complications, using UKPDS‐OM2 equations in patients without CVD, and EMPA‐REG OUTCOME equations in patients with CVD. Additional US‐based sources informed inputs for population characteristics, adverse events, non‐CV death, treatment escalation, quality of life and costs. Costs and quality‐adjusted life‐years (QALYs) were discounted 3.0% annually. Results The incremental cost‐effectiveness ratio (ICER) for second‐line empagliflozin versus sitagliptin in the overall T2D population was $6967/QALY. Empagliflozin led to longer CVD‐free survival (0.07 years) and an 11% reduction in CV death in patients with CVD compared with sitagliptin. Empagliflozin resulted in greater benefits with greater costs in patients with versus without baseline CVD, yielding ICERs of $3589/QALY versus $12 577/QALY, respectively. Results were consistent across a range of deterministic and probabilistic sensitivity analyses and scenarios. Conclusion Compared with sitagliptin, empagliflozin was cost‐effective (at $50 000/QALY US threshold) as a second‐line treatment to metformin for T2D patients with or without CVD in the United States. Our findings lend additional support for more widespread adoption of guidelines by healthcare decision‐makers for T2D treatment.

Aims Heart failure (HF) and type 2 diabetes (T2D), common co‐morbidities, translate into worse patient prognoses and higher direct costs than for either condition alone. Empagliflozin has been shown to markedly reduce cardiovascular (CV) deaths and HF hospitalizations (HHF) in HF patients with T2D. This study evaluated the lifetime cost‐effectiveness of supplementing standard of care (SoC) with empagliflozin, relative to SoC alone, in HF patients with T2D from the UK payer perspective. Methods and results An existing discrete‐event simulation model was adapted for the economic evaluation. Risk equations developed from time‐dependent parametric survival analyses using patient‐level HF subpopulation data from the EMPA‐REG OUTCOME trial were employed to predict CV and renal events. Non‐CV death, utility weights, and costs were drawn from UK sources. Quality‐adjusted life years (QALYs) and costs were discounted at 3.5% per annum. Relative to SoC, empagliflozin with SoC yielded fewer first HHF, recurrent HHF, CV death, and non‐fatal myocardial infarction but more non‐fatal stroke events. Empagliflozin with SoC vs. SoC alone was associated with increased average life expectancy (10.80 vs. 9.59 LYs) and quality of life (6.27 vs. 5.62 QALYs), though at higher lifetime cost (£18 197 vs. £16 829) per person, resulting in an incremental cost‐effectiveness ratio of £2093 per QALY. The probability of empagliflozin being cost‐effective in the HF subpopulation at a £20 000 per QALY willingness‐to‐pay threshold was 91%. Conclusions This analysis suggests that adding empagliflozin to SoC in HF patients with T2D constitutes a cost‐effective use of UK healthcare resources and may provide long‐term health benefits to patients.

INTRODUCTION: The EMPA-REG OUTCOME trial demonstrated the efficacy of empagliflozin in the treatment of type 2 diabetes (T2D) with a previous history of cardiovascular (CV) disease. The drug is currently reimbursed for T2D Italian patients, but the reduction of CV mortality and morbidity shown in the trial opens a new treatment perspective in those patients with associated high CV risk.OBJECTIVE: Cost-effectiveness analysis of empagliflozin for the treatment of T2D patients with a previous history of CV disease, from the Italian National Health Service (NHS) perspective.METHODS: The analysis was performed with an individual simulation model, which can predict the time to CV events or death through a set of time-dependent regressions estimated on the patient-level data of the EMPA-REG OUTCOME trial. This design allows the direct simulation of long-term outcomes and costs without the need for surrogate endpoints.The model was adapted to the Italian setting, considering local epidemiological data, baseline quality of life (QoL) utility, background mortality and unit costs from current prices and tariffs. The cost perspective was that of the Italian NHS and the horizon of the simulation was lifetime. Costs and benefits were discounted at a 3.5% rate.RESULTS: Base case results were estimated on a cohort of 5,000 patients, which ensured the convergence of the simulation. Patients treated with empagliflozin in add-on to the standard of care (SoC) lived on the average 13.8 undiscounted years as compared to 11.8 years of patients on SoC alone. The gain in discounted quality-adjusted life years (QALYs) was 1.0, due to improved survival and QoL linked to the reduced incidence of CV events and CV mortality. The incremental cost-effectiveness ratio (ICER) was 4,811 €/QALY, well below the commonly applied threshold of 30,000-50,000 €/QALY.CONCLUSION: Empagliflozin in add-on to the SoC is a highly cost-effective strategy for the treatment of T2D patients with known CV disease in the Italian setting.

Objectives Treatment landscape in prostate cancer has changed dramatically with the emergence of new medicines in the past few years. The traditional survival partition model (SPM) cannot accurately predict long-term clinical outcomes because it is limited by its ability to capture the key consequences associated with this changing treatment paradigm. The objective of this study was to introduce and validate a discrete-event simulation (DES) model for prostate cancer. Methods A DES model was developed to simulate overall survival (OS) and other clinical outcomes based on patient characteristics, treatment received, and disease progression history. We tested and validated this model with clinical trial data from the abiraterone acetate phase III trial (COU-AA-302). The model was constructed with interim data (55% death) and validated with the final data (96% death). Predicted OS values were also compared with those from the SPM. Results The DES model's predicted time to chemotherapy and OS are highly consistent with the final observed data. The model accurately predicts the OS hazard ratio from the final data cut (predicted: 0.74; 95% confidence interval [CI] 0.64–0.85 and final actual: 0.74; 95% CI 0.6–0.88). The log-rank test to compare the observed and predicted OS curves indicated no statistically significant difference between observed and predicted curves. However, the predictions from the SPM based on interim data deviated significantly from the final data. Conclusions Our study showed that a DES model with properly developed risk equations presents considerable improvements to the more traditional SPM in flexibility and predictive accuracy of long-term outcomes.