Addressing practical issues of predictive models translation into everyday practice and public health management: a combined model to predict the risk of type 2 diabetes improves incidence prediction and reduces the prevalence of missing risk predictions

Predicting type 2 diabetes and testosterone effects in high-risk Australian men: development and external validation of a 2-year risk model

OBJECTIVE

We have shown that men aged 50 years+ at high risk of type 2 diabetes treated with testosterone together with a lifestyle program reduced the risk of type 2 diabetes at 2 years by 40% compared to a lifestyle program alone. To develop a personalized approach to treatment, we aimed to explore a prognostic model for incident type 2 diabetes at 2 years and investigate biomarkers predictive of the testosterone effect.

DESIGN

Model development in 783 men with impaired glucose tolerance but not type 2 diabetes from Testosterone for Prevention of Type 2 Diabetes; a multicenter, 2-year trial of Testosterone vs placebo. External validation performed in 236 men from the Examining Outcomes in Chronic Disease in the 45 and Up Study (EXTEND-45, n = 267 357).

METHODS

Type 2 diabetes at 2 years defined as 2-h fasting glucose by oral glucose tolerance test (OGTT) ≥11.1 mmol/L. Risk factors, including predictive biomarkers of testosterone treatment, were assessed using penalized logistic regression.

RESULTS

Baseline HbA1c and 2-h OGTT glucose were dominant predictors, together with testosterone, age, and an interaction between testosterone and HbA1c (P = .035, greater benefit with HbA1c ≥ 5.6%, 38 mmol/mol). The final model identified men who developed type 2 diabetes, with C-statistics 0.827 in development and 0.798 in validation. After recalibration, the model accurately predicted a participant's absolute risk of type 2 diabetes.

CONCLUSIONS

Baseline HbA1c and 2-h OGTT glucose predict incident type 2 diabetes at 2 years in high-risk men, with risk modified independently by testosterone treatment. Men with HbA1c ≥ 5.6% (38 mmol/mol) benefit most from testosterone treatment, beyond a lifestyle program.

A dynamic probabilistic model of the onset and interaction of cardio-metabolic comorbidities on an ageing adult population

Comorbidity is widespread in the ageing population, implying multiple and complex medical needs for individuals and a public health burden. Determining risk factors and predicting comorbidity development can help identify at-risk subjects and design prevention strategies. Using socio-demographic and clinical data from approximately 11,000 subjects monitored over 11 years in the English Longitudinal Study of Ageing, we develop a dynamic Bayesian network (DBN) to model the onset and interaction of three cardio-metabolic comorbidities, namely type 2 diabetes (T2D), hypertension, and heart problems. The DBN allows us to identify risk factors for developing each morbidity, simulate ageing progression over time, and stratify the population based on the risk of outcome occurrence. By applying hierarchical agglomerative clustering to the simulated, dynamic risk of experiencing morbidities, we identified patients with similar risk patterns and the variables contributing to their discrimination. The network reveals a direct joint effect of biomarkers and lifestyle on outcomes over time, such as the impact of fasting glucose, HbA1c, and BMI on T2D development. Mediated cross-relationships between comorbidities also emerge, showcasing the interconnected nature of these health issues. The model presents good calibration and discrimination ability, particularly in predicting the onset of T2D (iAUC-ROC = 0.828, iAUC-PR = 0.294) and survival (iAUC-ROC = 0.827, iAUC-PR = 0.311). Stratification analysis unveils two distinct clusters for all comorbidities, effectively discriminated by variables like HbA1c for T2D and age at baseline for heart problems. The developed DBN constitutes an effective, highly-explainable predictive risk tool for simulating and stratifying the dynamic risk of developing cardio-metabolic comorbidities. Its use could help identify the effects of risk factors and develop health policies that prevent the occurrence of comorbidities.

Pharmacological treatment of type 2 diabetes in elderly patients with heart failure: randomized trials and beyond

Heart failure (HF) and type 2 diabetes mellitus (T2DM) represent two important public health problems, and despite improvements in the management of both diseases, they are responsible for high rates of hospitalizations and mortality. T2DM accelerates physiological cardiac aging through hyperglycemia and hyperinsulinemia. Thus, HF and T2DM are chronic diseases widely represented in elderly people who often are affected by numerous comorbidities with important functional limitations making it difficult to apply the current guidelines. Several antidiabetic drugs should be used with caution in elderly individuals with T2DM. For instance, sulfonylureas should be avoided due to the risk of hypoglycemia associated with its use. Insulin should be used with caution because it is associated with higher risk of hypoglycemia, and may determine fluid retention which can lead to worsening of HF. Thiazolindinediones should be avoided due to the increased risk of fluid retention and HF. Biguanides may lead to a slightly increased risk of lactic acidosis in particular in elderly individuals with impaired renal function. Dipeptidyl peptidase 4 (DPP-4) inhibitors are safe having few side effects, minimal risk of hypoglycemia, and a neutral effect on cardiovascular (CV) outcome, even if it has been reported that saxagliptin treatment is associated with increased risk of hospitalizations for HF (hHF). Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have shown a CV protection without a significant reduction in hHF. On the other hand, sodium-glucose cotransporter 2 (SGLT2) inhibitors have shown a significant improvement in CV outcome, with a strong reduction of hHF and a positive impact on renal damage progression. However, it is necessary to consider the possible some side effects related to their use in elderly individuals including hypotension, bone fractures, and ketoacidosis.It is important to remark that elderly patients, in particular the very elderly, are not sufficiently represented in the trials; thus, the management and treatment of elderly diabetic patients with HF should be mainly based on the integration of scientific evidence with clinical judgment and patients' condition, with respect to the dignity and quality of life.