Cardiorenal diseases in type 2 diabetes mellitus: clinical trials and real-world practice

Abstract Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D. 

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis

Cardiometabolic diseases are the leading preventable causes of death in most geographies. The causes, clinical presentations, and pathogenesis of cardiometabolic diseases vary greatly worldwide, as do the resources and strategies needed to prevent and treat them. Therefore, there is no single solution and health care should be optimised, if not to the individual (ie, personalised health care), then at least to population subgroups (ie, precision medicine). This optimisation should involve tailoring health care to individual disease characteristics according to ethnicity, biology, behaviour, environment, and subjective person-level characteristics. The capacity and availability of local resources and infrastructures should also be considered. Evidence needed for equitable precision medicine cannot be generated without adequate data from all target populations, and the idea that research done in high-income countries will transfer adequately to low-income and middle-income countries (LMICs) is problematic, as many migration studies and transethnic comparisons have shown. However, most data for precision medicine research are derived from people of European ancestry living in high-income countries. In this Series paper, we discuss the case for precision medicine for cardiometabolic diseases in LMICs, the barriers and enablers, and key considerations for implementation. We focus on three propositions: first, failure to explore and implement precision medicine for cardiometabolic disease in LMICs will enhance global health disparities. Second, some LMICs might already be placed to implement cardiometabolic precision medicine under appropriate circumstances, owing to progress made in treating infectious diseases. Third, improvements in population health from precision medicine are most probably asymptotic; the greatest gains are more likely to be obtained in countries where health-care systems are less developed. We outline key recommendations for implementation of precision medicine approaches in LMICs. 

The case for precision medicine in the prevention, diagnosis, and treatment of cardiometabolic diseases in low-income and middle-income countries.

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that could improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination on internal validation, with lower performance on external validation. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

/pdf/precision-prognostics-for-cardiovascular-disease-in-type-2-4dwi8ss4.pdf

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis

Abstract Evidence‐based guidelines provide the premise for the delivery of quality care to preserve health and prevent disabilities and premature death. The systematic gathering of observational, mechanistic and experimental data contributes to the hierarchy of evidence used to guide clinical practice. In the field of diabetes, metformin was discovered more than 100 years ago, and with 60 years of clinical use, it has stood the test of time regarding its value in the prevention and management of type 2 diabetes. Although some guidelines have challenged the role of metformin as the first‐line glucose‐lowering drug, it is important to point out that the cardiovascular‐renal protective effects of sodium‐glucose co‐transporter‐2 inhibitors and glucagon‐like peptide‐1 receptor agonists were gathered from patients with type 2 diabetes, the majority of whom were treated with metformin. Most national, regional and international guidelines recommend metformin as a foundation therapy with emphasis on avoidance of therapeutic inertia and early attainment of multiple treatment goals. Moreover, real‐world evidence has confirmed the glucose‐lowering and cardiovascular‐renal benefits of metformin accompanied by an extremely low risk of lactic acidosis. In patients with type 2 diabetes and advanced chronic kidney disease (estimated glomerular filtration rate 15‐30 mL/min/1.73m 2 ), metformin discontinuation was associated with an increased risk of cardiovascular‐renal events compared with metformin persistence. Meanwhile, it is understood that microbiota, nutrients and metformin can interact through the gut‐brain‐kidney axis to modulate homeostasis of bioactive molecules, systemic inflammation and energy metabolism. While these biological changes contribute to the multisystem effects of metformin, they may also explain the gastrointestinal side effects and vitamin B12 deficiency associated with metformin intolerance. By understanding the interactions between metformin, foods and microbiota, healthcare professionals are in a better position to optimize the use of metformin and mitigate potential side effects. The United Kingdom Prospective Diabetes Study and the Da Qing Diabetes Prevention Program commenced 40 years ago provided the first evidence that type 2 diabetes is preventable and treatable. To drive real‐world impact from this evidence, payors, practitioners and planners need to co‐design and implement an integrated, data‐driven, metformin‐based programme to detect people with undiagnosed diabetes and prediabetes (intermediate hyperglycaemia), notably impaired glucose tolerance, for early intervention. The systematic data collection will create real‐world evidence to bring out the best of metformin and make healthcare sustainable, affordable and accessible. 

Current type 2 diabetes guidelines: Individualized treatment and how to make the most of metformin

Importance Many health care systems lack the efficiency, preparedness, or resources needed to address the increasing number of patients with type 2 diabetes, especially in low- and middle-income countries. Objective To examine the effects of a quality improvement intervention comprising information and communications technology and contact with nonphysician personnel on the care and cardiometabolic risk factors of patients with type 2 diabetes in 8 Asia-Pacific countries. Design, Setting, and Participants This 12-month multinational open-label randomized clinical trial was conducted from June 28, 2012, to April 28, 2016, at 50 primary care or hospital-based diabetes centers in 8 Asia-Pacific countries (India, Indonesia, Malaysia, the Philippines, Singapore, Taiwan, Thailand, and Vietnam). Six countries were low and middle income, and 2 countries were high income. The study was conducted in 2 phases; phase 1 enrolled 7537 participants, and phase 2 enrolled 13 297 participants. Participants in both phases were randomized on a 1:1 ratio to intervention or control groups. Data were analyzed by intention to treat and per protocol from July 3, 2019, to July 21, 2020. Interventions In both phases, the intervention group received 3 care components: a nurse-led Joint Asia Diabetes Evaluation (JADE) technology-guided structured evaluation, automated personalized reports to encourage patient empowerment, and 2 or more telephone or face-to-face contacts by nurses to increase patient engagement. In phase 1, the control group received the JADE technology-guided structured evaluation and automated personalized reports. In phase 2, the control group received the JADE technology-guided structured evaluation only. Main Outcomes and Measures The primary outcome was the incidence of a composite of diabetes-associated end points, including cardiovascular disease, chronic kidney disease, visual impairment or eye surgery, lower extremity amputation or foot ulcers requiring hospitalization, all-site cancers, and death. The secondary outcomes were the attainment of 2 or more primary diabetes-associated targets (glycated hemoglobin A1c <7.0%, blood pressure <130/80 mm Hg, and low-density lipoprotein cholesterol <100 mg/dL) and/or 2 or more key performance indices (reduction in glycated hemoglobin A1c≥0.5%, reduction in systolic blood pressure ≥5 mm Hg, reduction in low-density lipoprotein cholesterol ≥19 mg/dL, and reduction in body weight ≥3.0%). Results A total of 20 834 patients with type 2 diabetes were randomized in phases 1 and 2. In phase 1, 7537 participants (mean [SD] age, 60.0 [11.3] years; 3914 men [51.9%]; 4855 patients [64.4%] from low- and middle-income countries) were randomized, with 3732 patients allocated to the intervention group and 3805 patients allocated to the control group. In phase 2, 13 297 participants (mean [SD] age, 54.0 [11.1] years; 7754 men [58.3%]; 13 297 patients [100%] from low- and middle-income countries) were randomized, with 6645 patients allocated to the intervention group and 6652 patients allocated to the control group. In phase 1, compared with the control group, the intervention group had a similar risk of experiencing any of the primary outcomes (odds ratio [OR], 0.94; 95% CI, 0.74-1.21) but had an increased likelihood of attaining 2 or more primary targets (OR, 1.34; 95% CI, 1.21-1.49) and 2 or more key performance indices (OR, 1.18; 95% CI, 1.04-1.34). In phase 2, the intervention group also had a similar risk of experiencing any of the primary outcomes (OR, 1.02; 95% CI, 0.83-1.25) and had a greater likelihood of attaining 2 or more primary targets (OR, 1.25; 95% CI, 1.14-1.37) and 2 or more key performance indices (OR, 1.50; 95% CI, 1.33-1.68) compared with the control group. For attainment of 2 or more primary targets, larger effects were observed among patients in low- and middle-income countries (OR, 1.50; 95% CI, 1.29-1.74) compared with high-income countries (OR, 1.20; 95% CI, 1.03-1.39) (P = .04). Conclusions and Relevance In this 12-month clinical trial, the use of information and communications technology and nurses to empower and engage patients did not change the number of clinical events but did reduce cardiometabolic risk factors among patients with type 2 diabetes, especially those in low- and middle-income countries in the Asia-Pacific region. Trial Registration ClinicalTrials.gov Identifier: NCT01631084.

/pdf/effects-of-a-technology-assisted-integrated-diabetes-care-4gxg3cvkb1.pdf

Effects of a Technology-Assisted Integrated Diabetes Care Program on Cardiometabolic Risk Factors Among Patients With Type 2 Diabetes in the Asia-Pacific Region: The JADE Program Randomized Clinical Trial.

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Effects of a Technology-Assisted Integrated Diabetes Care Program on Cardiometabolic Risk Factors Among Patients With Type 2 Diabetes in the Asia-Pacific Region: The JADE Program Randomized Clinical Trial.