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Transparency in health economic decision modelling is important for engendering confidence in the models and in the reliability of model-based cost-effectiveness analyses. The Mount Hood Diabetes Challenge Network has taken a lead in promoting transparency through validation with biennial conferences in which diabetes modelling groups meet to compare simulated outcomes of pre-specified scenarios often based on the results of pivotal clinical trials. Model registration is a potential method for promoting transparency, while also reducing the duplication of effort. An important network initiative is the ongoing construction of a diabetes model registry (https://www.mthooddiabeteschallenge.com). Following the 2012 International Society for Pharmacoeconomics and Outcomes Research and the Society of Medical Decision Making (ISPOR-SMDM) guidelines, we recommend that modelling groups provide technical and non-technical documentation sufficient to enable model reproduction, but not necessarily provide the model code. We also request that modelling groups upload documentation on the methods and outcomes of validation efforts, and run reference case simulations so that model outcomes can be compared. In this paper, we discuss conflicting definitions of transparency in health economic modelling, and describe the ongoing development of a registry of economic models for diabetes through the Mount Hood Diabetes Challenge Network, its objectives and potential further developments, and highlight the challenges in its construction and maintenance. The support of key stakeholders such as decision-making bodies and journals is key to ensuring the success of this and other registries. In the absence of public funding, the development of a network of modellers is of huge value in enhancing transparency, whether through registries or other means.

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 (R 2 ). 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., (Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.)

Many studies have demonstrated the metabolic efficacy of continuous subcutaneous insulin infusion (CSII) and particularly a reduction of glycaemic fluctuations in type 1 diabetic patients. Despite this benefit, many patients decide to discontinue the use of CSII. To determine the factors related to discontinuation of CSII we analyzed clinical data from a group of 70 patients who had been consecutively started on this treatment from April 2000 to April 2002. Patients were followed for up to 2 years. Eighteen (25.7%) patients decided to terminate CSII during the study after an average of 235 days (range 21-293). The reasons for stopping CSII were decision of the patients (10), end of pregnancy (4), needle site infections (3) and lack of compliance (1). No significant difference was found between patients who had continued and those who had discontinued CSII for age, duration of diabetes, reasons for starting CSII, marital status, prepump concentration of HbA1c and prepump frequency of hypoglycaemia. There tend to be more discontinuations for pregnant women, patients attending hospital visits versus liberal practitioner and patients with lower educational level (below or over baccalaureat) although none of these differences was statistically significant. In conclusion we could not identify any predictive factor of CSII discontinuation.

Background: Corticosteroids are generally contraindicated in diabetic patients due to the risk of disrupting glucose control leading to acute decompensation. In some cases however, corticosteroid therapy can be beneficial if given early with a well-controlled regimen. Glucose disequilibrium after withdrawal can be anticipated with proper knowledge of the pharmacokinetics of the glucocorticoid used., For Patients With Type I Diabetes: Ketose acidosis is a real risk in these patients. Insulin dose must be increased and the administration scheme optimized., For Patients With Type Ii Diabetes: Whether oral drugs should be continued is a question of debate, excepting cases where the underlying disease might cause acute decompensation requiring insulin. Outside this situation, oral drugs can be continued at a higher dose if the fasting serum glucose is below 2 g/L. Finally, it is important to recognized steroid-induced diabetes in order to initiate proper antidiabetic measures., For All Patients: The glucose curve is reproducible. Basically, the postprandial level rises, warranting repeated insulin injections. Rapid-release analogs and alpha-glucosidase inhibitors appear to be promising; biguanides affect insulin resistance.