Executive summary 2020 will go down in history as the year when the global community was
awakened to the fragility of human health and the interdependence of the ecosystem …

Many childhood cancer survivors carry a significant risk for late morbidity and mortality, a
consequence of the numerous therapeutic exposures that contribute to their cure. Focused …

State-transition modeling (STM) is an intuitive, flexible, and transparent approach of
computer-based decision-analytic modeling, including both Markov model cohort simulation …

Development and progression of nephropathy in type 2 diabetes: The United Kingdom
Prospective Diabetes Study (UKPDS 64). Background The progression of nephropathy from …

Markov models are often employed to represent stochastic processes, that is, random
processes that evolve over time. In a healthcare context, Markov models are particularly …

Meta-analysis, decision analysis, and cost-effectiveness analysis are the cornerstones of
evidence-based medicine. These related quantitative methods have become essential tools …

The use of modelling in economic evaluation is widespread, and it most often involves
synthesising data from a number of sources. However, even when economic evaluations are …

Background Non‐alcoholic fatty liver disease (NAFLD) and non‐alcoholic steatohepatitis
(NASH) account for an increasing proportion of liver disease in the Asia‐Pacific region …

Abstract Models for the economic evaluation of health technologies provide valuable
information to decision makers. The choice of model structure is rarely discussed in …

Objectives: We have developed an Internet-based, interactive computer model to determine
the longterm health outcomes and economic consequences of implementing different …