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Network meta-analysis was used to derive estimates of the relative efficacy of inclisiran, evolocumab, alirocumab, bempedoic acid, and ezetimibe in patients with hypercholesterolemia and/or at increased cardiovascular risk due to elevated low-density lipoprotein cholesterol taking maximum tolerated dose statins. Clinical trials published through February 2021 comparing percent change from baseline in low-density lipoprotein cholesterol were identified via a systematic review. Bayesian network meta-analyses were performed for patients with atherosclerotic cardiovascular disease and/or high cardiovascular risk on maximally tolerated statins in the base case, which included 23 trials. Results from the base-case analyses demonstrated that inclisiran, evolocumab, and alirocumab provide superior efficacy over placebo, bempedoic acid, and ezetimibe in terms of reduction in low-density lipoprotein cholesterol. Inclisiran was also comparable to alirocumab (mean difference: 0.78% [95% CrI: −8.35, 9.88]) and evolocumab (8.16%, [95% CrI: −1.82, 18.49]). Findings of a scenario which also included trials conducted in patients with heterozygous familial hypercholesterolemia were consistent with the base case. There was evidence of statistical heterogeneity across the included trials, roughly equivalent to variation of 5–10% change in low-density lipoprotein cholesterol, suggesting that any differences between treatments that were greater than 5–10% are generalizable. This study provides insight regarding the comparative efficacy of drugs for which no head-to-head trials exist and suggests that inclisiran, alirocumab, and evolocumab are expected to provide similar clinically meaningful improvements in low-density lipoprotein cholesterol in patients with hypercholesterolemia on maximally tolerated statins who are at increased cardiovascular risk.

Critiques of cost-effectiveness modelling in type 1 diabetes mellitus (T1DM) are scarce and are often undertaken in combination with type 2 diabetes mellitus (T2DM) models. However, T1DM is a separate disease, and it is therefore important to appraise modelling methods in T1DM.This review identified published economic models in T1DM and provided an overview of the characteristics and capabilities of available models, thus enabling a discussion of best-practice modelling approaches in T1DM.A systematic review of Embase(®), MEDLINE(®), MEDLINE(®) In-Process, and NHS EED was conducted to identify available models in T1DM. Key conferences and health technology assessment (HTA) websites were also reviewed. The characteristics of each model (e.g. model structure, simulation method, handling of uncertainty, incorporation of treatment effect, data for risk equations, and validation procedures, based on information in the primary publication) were extracted, with a focus on model capabilities.We identified 13 unique models. Overall, the included studies varied greatly in scope as well as in the quality and quantity of information reported, but six of the models (Archimedes, CDM [Core Diabetes Model], CRC DES [Cardiff Research Consortium Discrete Event Simulation], DCCT [Diabetes Control and Complications Trial], Sheffield, and EAGLE [Economic Assessment of Glycaemic control and Long-term Effects of diabetes]) were the most rigorous and thoroughly reported. Most models were Markov based, and cohort and microsimulation methods were equally common. All of the more comprehensive models employed microsimulation methods. Model structure varied widely, with the more holistic models providing a comprehensive approach to microvascular and macrovascular events, as well as including adverse events. The majority of studies reported a lifetime horizon, used a payer perspective, and had the capability for sensitivity analysis.Several models have been developed that provide useful insight into T1DM modelling. Based on a review of the models identified in this study, we identified a set of 'best in class' methods for the different technical aspects of T1DM modelling.