External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement-a protocol for a systematic review

A Systematic Review of Methodologies Used in Models of the Treatment of Diabetes Mellitus

BACKGROUND

Diabetes mellitus is a chronic and complex disease, increasing in prevalence and consequent health expenditure. Cost-effectiveness models with long time horizons are commonly used to perform economic evaluations of diabetes' treatments. As such, prediction accuracy and structural uncertainty are important features in cost-effectiveness models of chronic conditions.

OBJECTIVES

The aim of this systematic review is to identify and review published cost-effectiveness models of diabetes treatments developed between 2011 and 2022 regarding their methodological characteristics. Further, it also appraises the quality of the methods used, and discusses opportunities for further methodological research.

METHODS

A systematic literature review was conducted in MEDLINE and Embase to identify peer-reviewed papers reporting cost-effectiveness models of diabetes treatments, with time horizons of more than 5 years, published in English between 1 January 2011 and 31 of December 2022. Screening, full-text inclusion, data extraction, quality assessment and data synthesis using narrative synthesis were performed. The Philips checklist was used for quality assessment of the included studies. The study was registered in PROSPERO (CRD42021248999).

RESULTS

The literature search identified 30 studies presenting 29 unique cost-effectiveness models of type 1 and/or type 2 diabetes treatments. The review identified 26 type 2 diabetes mellitus (T2DM) models, 3 type 1 DM (T1DM) models and one model for both types of diabetes. Fifteen models were patient-level models, whereas 14 were at cohort level. Parameter uncertainty was assessed thoroughly in most of the models, whereas structural uncertainty was seldom addressed. All the models where validation was conducted performed well. The methodological quality of the models with respect to structure was high, whereas with respect to data modelling it was moderate.

CONCLUSIONS

Models developed in the past 12 years for health economic evaluations of diabetes treatments are of high-quality and make use of advanced methods. However, further developments are needed to improve the statistical modelling component of cost-effectiveness models and to provide better assessment of structural uncertainty.

Interactions among moderate/severe periodontitis, ADIPOQ-rs1501299, and LEPR-rs1137100 polymorphisms on the risk of type 2 diabetes in a Chinese population

OBJECTIVE

Type 2 diabetes mellitus (T2DM) is a complex disease influenced by genes and the environment. Periodontitis a demonstrated risk factor of T2DM. Previous studies related to gene-environment interactions on the risk of T2DM mainly focused on gene-obesity interactions. However, the impact of gene-periodontitis interaction on the risk of T2DM has not yet been investigated. This study aimed to investigate gene-environment interactions among moderate/severe periodontitis, polymorphisms of adiponectin (ADIPOQ)-rs1501299, and leptin receptor (LEPR)-rs1137100 on T2DM risk in Chinese subjects.

DESIGN

A case-control study was conducted in 239 Chinese participants from Beijing Hypertension Association Institute (BHAL). After full-mouth periodontal examinations, the participants underwent bilateral buccal swabs for DNA testing. ADIPOQ-rs1501299 and LEPR-rs1137100 were used for genotyping. Generalised multifactor dimensionality reduction (GMDR) and logistic regression were used to examine the interactions among single nucleotide polymorphisms (SNPs) and moderate/severe periodontitis on the risk of T2DM.

RESULTS

The risk of T2DM was higher in moderate/severe periodontitis [adjusted odds ratio (AOR) = 3.67, 95% confidence interval (95%CI): 1.26-10.71] in ADIPOQ-rs1501299 GG genotype (AOR = 3.42, 95%CI: 1.81-6.46) and LEPR-rs1137100 GG genotype (AOR = 3.16, 95%CI: 1.56-6.39). The GMDR model indicated that there was a significant three-factor model (p = 0.001) involving rs1501299, rs1137100, and moderate/severe periodontitis, demonstrating a potential gene-environment interaction among periodontitis, polymorphisms of rs1501299, and rs1137100 influencing the risk of T2DM. Moderate/severe periodontitis patients with rs1501299-GG and rs1137100-GG have the highest T2DM risk after adjusting for age, gender, BMI, WHR, smoking status, alcohol consumption, economic status, and hypertension (AOR = 20.39, 95%CI: 2.64-157.26).

CONCLUSIONS

Interactions among moderate/severe periodontitis, rs1501299-GG, and rs1137100-GG were associated with an increased risk of T2DM. This study may provide a new insight into the effect of gene-environment interactions on T2DM.