Decision models in type 2 diabetes mellitus: A systematic review

Area of Science:

• Health economics
• Epidemiology
• Biostatistics

Background:

• Type 2 diabetes (T2DM) poses a significant global health burden.
• Disease decision models are crucial tools for informing T2DM management strategies.
• A comprehensive assessment of existing T2DM decision models is lacking.

Purpose of the Study:

• To provide an overview of the characteristics and capabilities of published T2DM decision models.
• To assess the suitability of different models for various research needs.
• To guide the selection and development of T2DM decision models.

Main Methods:

• Systematic literature search of four databases (PubMed, Web of Science, Embase, Cochrane Library) up to August 2020.
• Inclusion of studies using keywords related to T2DM, cost-utility, quality-of-life, and decision models.
• Independent screening and data extraction by two reviewers, focusing on model characteristics, methodologies, inputs, outcomes, validation, and uncertainty.

Main Results:

• Fourteen unique T2DM decision models were identified, employing diverse methodologies like Markov chains and risk equations.
• Most models used annual cycles and flexible time horizons, with 10 focusing on complications and 11 on patient-level simulations.
• Eleven models simulated annual risk factor changes, and most addressed model uncertainty and validation.

Conclusions:

• T2DM decision models exhibit significant heterogeneity in health state classification detail.
• Balancing model complexity with transparency is essential for effective T2DM decision model development.
• Further research should focus on standardizing or clearly defining model structures for improved comparability.