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

Andrew J Palmer, Lei Si, Michelle Tew, Xinyang Hua, Michael S Willis, Christian Asseburg, Phil McEwan, José Leal, Alastair Gray, Volker Foos, Mark Lamotte, Talitha Feenstra, Patrick J O'Connor, Michael Brändle, Harry J Smolen, James C Gahn, William J Valentine, Richard F Pollock, Penny Breeze, Alan Brennan, Daniel Pollard, Wen Ye, William H Herman, Deanna J Isaman, Shihchen Kuo, Neda Laiteerapong, An Tran-Duy & Philip M Clarke

abstract

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). 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.
   
citation Palmer A J, Si L, Tew M, Hua X, Willis M S, Asseburg C, McEwan P, Leal J, Gray A, Foos V, Lamotte M, Feenstra T, O'Connor P J, Brändle M, Smolen H J, Gahn J C, Valentine W J, Pollock R F, Breeze P, Brennan A, Pollard D, Ye W, Herman W H, Isaman D J, Kuo S, Laiteerapong N, Tran-Duy A, Clarke P M. Computer Modeling of Diabetes and Its Transparency: A Report on the Eighth Mount Hood Challenge. Value Health 2018; 21:724-731.
   
type journal paper/review (English)
date of publishing 09-04-2018
journal title Value Health (21/6)
ISSN electronic 1524-4733
pages 724-731
PubMed 29909878
DOI 10.1016/j.jval.2018.02.002