Predictors of lack of glycemic control in persons with type 2 diabetes.

BACKGROUND: Professional guidelines recommend an HbA1c < 7% for most people with diabetes and < 8.5% for those with relaxed glycemic goals. However, many people with type 2 diabetes mellitus (T2DM) are unable to achieve the desired HbA1c goal. This study evaluated factors associated with lack of improvement in HbA1c over 3 years. METHODS: All patients with T2DM treated within a major academic healthcare system during 2015-2020, who had at least one HbA1c value > 8.5% within 3 years from their last HbA1c were included in analysis. Patients were grouped as improved glycemic control (last HbA1c ≤ 8.5%) or lack of improvement (last HbA1c > 8.5%). Multivariate logistic regression analysis was performed to assess independent predictors of lack of improvement in glycemic control. RESULTS: Out of 2,232 patients who met the inclusion criteria, 1,383 had an improvement in HbA1c while 849 did not. In the fully adjusted model, independent predictors of lack of improvement included: younger age (odds ratio, 0.89 per 1-SD [12 years]; 95% CI, 0.79-1.00), female gender (1.30, 1.08-1.56), presence of hypertension (1.29, 1.08-1.55), belonging to Black race (1.32, 1.04-1.68, White as reference), living in low income area (1.86,1.28-2.68, high income area as reference), and insurance coverage other than Medicare (1.32, 1.05-1.66). Presence of current smoking was associated with a paradoxical improvement in HbA1c (0.69, 0.47-0.99). In a subgroup analysis, comparing those with all subsequent HbA1c values > 8.5% (N = 444) to those with all subsequent HbA1c values < 8.5% (N = 341), similar factors were associated with lack of improvement, but smoking was no longer significant. CONCLUSION: We conclude that socioeconomic factors like race, type of insurance coverage and living in low-income areas are associated with lack of improvement in HbA1c over a period of 3-years in people with T2DM. Intervention strategies focused on low-income neighborhoods need to be designed to improve diabetes management.

Prognostic value of insulin resistance and hyperglycemia biomarkers for long-term risks of cardiometabolic outcomes.

We found that individuals in the top tertile of HOMA-IR and with HbA1c-defined prediabetes have elevated risk of cardiometabolic outcomes.

Insulin resistance probability score and incident cardiovascular disease.

BACKGROUND: Insulin resistance (IR) is associated with cardiovascular disease (CVD). However, insulin immunoassay variability and scarce research of the elderly have hindered the adoption of IR assessment for CVD prevention. We asked whether the probability of having IR [p(IR)]-derived from insulin and C-peptide mass-spectrometry assays-was associated with CVD in the elderly. METHODS: A random cohort was drawn from MPP, a population-based study of the elderly. After excluding those with missing data, CVD, or diabetes, 3645 participants (median age = 68) remained. RESULTS: During follow-up (13.3 years), 794 incident CVD events were observed. p(IR) > 80% (n = 152) compared with p(IR) ≤ 80% was associated with incident CVD (HR = 1.51, 95% CI 1.12-2.05, p = 0.007) and CVD or all-cause mortality (HR = 1.43, 95% CI 1.16-1.77, p = 0.0009) after adjusting for age, sex, hypertension, smoking, HDL-cholesterol, total cholesterol, triglycerides, BMI, and prediabetes. CONCLUSION: High p(IR) was associated with >50% greater risk of incident CVD. IR assessment in the elderly may be warranted.

The relationship between insulin resistance and ion mobility lipoprotein fractions.

Objective: Insulin resistance (IR) increases risk of type 2 diabetes and atherosclerotic cardiovascular disease and is associated with lipid and lipoprotein abnormalities including high triglycerides (TG) and low high-density lipoprotein cholesterol (HDL-C). Lipoprotein size and lipoprotein subfractions (LS) have also been used to assist in identifying persons with IR. Associations of LS and IR have not been validated using both direct measures of IR and direct measures of LS. We assessed the usefulness of fasting lipoprotein subfractions (LS) by ion mobility to identify individuals with IR. Methods: Lipid panel, LS by ion mobility (LS-IM), and IR by steady-state plasma glucose (SSPG) concentration were assessed in 526 adult volunteers without diabetes. IR was defined as being in the highest tertile of SSPG concentration. LS-IM score was calculated by linear combination of regression coefficients from a stepwise regression analysis with SSPG concentration as the dependent variable. Improvement in prediction of IR was evaluated after combining LS-IM score with TG/HDL-C, TG/HDL-C and BMI as well as with TG/HDL-C, BMI, sex, race and ethnicity. IR prediction was evaluated by area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV) considering the highest 5% of scores as positive test. Results: Prediction of IR was similar by LS-IM score and TG/HDL-C (AUC=0.68; PPV=0.59 and AUC=0.70; PPV=0.59, respectively) and prediction was improved when LS-IM was combined with TG/HDL-C (AUC=0.73; PPV=0.70), TG/HDL-C and BMI (AUC=0.82; PPV=0.81) and with TG/HDL-C, BMI, sex, race and ethnicity (AUC=0.84; PPV=0.89). Conclusion: For identifying individuals with IR, LS-IM score and TG/HDL-C are comparable and their combination further improves IR prediction by TG/HDL-C alone. Among patients who have undergone IM testing, the LS-IM score may assist prioritization of subjects for further evaluation and interventions to reduce IR.

Intact Fasting Insulin Identifies Nonalcoholic Fatty Liver Disease in Patients Without Diabetes.

CONTEXT: Patients with nonalcoholic fatty liver disease (NAFLD) are characterized by insulin resistance and hyperinsulinism. However, insulin resistance measurements have not been shown to be good diagnostic tools to predict NAFLD in prior studies. OBJECTIVE: We aimed to assess a newly validated method to measure intact molecules of insulin by mass spectrometry to predict NAFLD. METHODS: Patients underwent a 2-hour oral glucose tolerance test (OGTT), a liver magnetic resonance spectroscopy (1H-MRS), and a percutaneous liver biopsy if they had a diagnosis of NAFLD. Mass spectrometry was used to measure intact molecules of insulin and C-peptide. RESULTS: A total of 180 patients were recruited (67% male; 52 ± 11 years of age; body mass index [BMI] 33.2 ± 5.7 kg/m2; 46% with diabetes and 65% with NAFLD). Intact fasting insulin was higher in patients with NAFLD, irrespective of diabetes status. Patients with NAFLD without diabetes showed ~4-fold increase in insulin secretion during the OGTT compared with all other subgroups (P = 0.008). Fasting intact insulin measurements predicted NAFLD in patients without diabetes (area under the receiver operating characteristic curve [AUC] of 0.90 [0.84-0.96]). This was significantly better than measuring insulin by radioimmunoassay (AUC 0.80 [0.71-0.89]; P = 0.007). Intact fasting insulin was better than other clinical variables (eg, aspartate transaminase, triglycerides, high-density lipoprotein, glucose, HbA1c, and BMI) to predict NAFLD. When combined with alanine transaminase (ALT) (intact insulin × ALT), it detected NAFLD with AUC 0.94 (0.89-0.99) and positive and negative predictive values of 93% and 88%, respectively. This newly described approach was significantly better than previously validated noninvasive scores such as NAFLD-LFS (P = 0.009), HSI (P < 0.001), and TyG index (P = 0.039). CONCLUSION: In patients without diabetes, accurate measurement of fasting intact insulin levels by mass spectrometry constitutes an easy and noninvasive strategy to predict presence of NAFLD.

Concordance of Cardiovascular Risk Factors and Behaviors in a Multiethnic US Nationwide Cohort of Married Couples and Domestic Partners.

Importance: Married couples and domestic partners have been reported to share similar environmental exposures, adopt similar behavior patterns, and have similar transferable characteristics. However, the degree to which couples share similar levels of cardiovascular risk factors and behaviors is uncertain. Objective: To assess within-couple concordance of the American Heart Association-defined Life's Simple 7 (LS7). Design, Setting, and Participants: Cross-sectional study with a longitudinal substudy of employees and spouses (or domestic partners) who participated in an employer-sponsored health assessment program throughout the United States between October 2014 and December 2018. Data were analyzed from November 1, 2019, to August 4, 2020. Exposures: Having a spouse or domestic partner. Main Outcomes and Measures: The LS7 risk factors and behaviors (smoking status, body mass index, exercise, diet, total cholesterol, blood pressure, and fasting glucose) were assessed by questionnaires, examinations, and laboratory tests. LS7 categories were scored as 2 for ideal, 1 for intermediate, or 0 for poor and summed to generate a CV health score. Results: The study included 10 728 participants (5364 couples): 7% were African American, 11% Hispanic, 21% Asian, and 54% White (median [interquartile range] age, 50 [41-57] years for men and 47 [39-55] for women). For most couples, both members were in the ideal category or both were in a nonideal category. Concordance ranged from 53% (95% CI, 52%-54%) for cholesterol to 95% (95% CI, 94%-95%) for diet. For the CV health score, in 79% (95% CI, 78%-80%) of couples both members were in a nonideal category, which was associated mainly with unhealthy diet (94% [95% CI, 93%-94%] of couples) and inadequate exercise (53% [95% CI, 52%-55%] of couples). However, in most couples, both members were in the ideal category for smoking status (60% [95% CI, 59%-61%] of couples) and glucose (56% [95% CI, 55%-58%]). Except for total cholesterol, when 1 member of a couple was in the ideal category, the other member was likely also to be in the ideal category: the adjusted odds ratios for also being in the ideal category ranged from 1.3 (95% CI, 1.1-1.5; P ≤ .001) for blood pressure to 10.6 (95% CI, 7.4-15.3; P ≤ .001) for diet. Concordance differed by ethnicity, socioeconomic status, and geographic location. A 5-year longitudinal analysis of 2186 couples found modest changes in concordance of blood pressure (from 55% [95% CI, 53%-57%] to 59% [95% CI, 57%-61%]; P < .001 for trend) and fasting glucose (from 64% [95% CI, 62%-66%] to 59% [95% CI, 57%-61%]; P < .001 for trend) with no change in other factors. Conclusions and Relevance: In this study, high concordance of nonideal behaviors was found within couples; behavioral modification programs may benefit both the targeted and the nontargeted member of a couple.

Impact of a Digital Diabetes Prevention Program on Risk Factors for Chronic Disease in a Workforce Cohort.

OBJECTIVE: Evaluate the effect of a digital Diabetes Prevention Program (dDPP) on chronic disease risk factors in a workplace population. METHODS: dDPP participants were employees and spouses with BMI ≥ 24 kg/m and prediabetes or diabetes (n = 84). Annual change in risk factors before and after dDPP were assessed in the dDPP group and in a retrospectively identified matched control group drawn from those who participated in a dDPP after the conclusion of this study (n = 252). RESULTS: In the dDPP group, body weight, BMI, fasting glucose, triglycerides, total cholesterol and LDL-cholesterol decreased in the post-dDPP period compared with the pre-dDPP period (P < 0.05). In the control group, no difference between the annual change before and after dDPP was observed (P > 0.37). CONCLUSION: The dDPP was effective in reducing risk factors for chronic disease in a workplace setting.

Gaps in Dyslipidemia Care Among Working-Aged Individuals With Employer-Sponsored Health Care.

Background The American Heart Association and American College of Cardiology guidelines defined patient-management groups that would benefit from lowering of low-density lipoprotein cholesterol (LDL-C). We assessed gaps in dyslipidemia care among employees and spouses with health benefits. Methods and Results We studied 17 889 employees and spouses who were covered by an employer-sponsored health plan and participated in an annual health assessment. Using medical claims, laboratory tests, and risk assessment questionnaires, we found that 43% of participants were in one of 4 patient-management groups: secondary prevention, severe hypercholesterolemia (LDL-C ≥190 mg/dL at least once in the preceding 5 years), diabetes mellitus, or elevated 10-year risk of cardiovascular disease. To assess gaps in dyslipidemia care, we used LDL-C ≤70 mg/dL as the goal for both the secondary prevention group and those in the elevated 10-year risk group with >20% risk; LDL-C ≤100 mg/dL was used for the other groups. Among those in patient-management groups, 27.3% were in the secondary prevention group, 7.4% were in the severe hypercholesterolemia group, 29.9% were in the diabetes mellitus group, and 35.4% were in the elevated 10-year risk group. About 74% of those in patient-management groups had above-goal LDL-C levels, whereas only 31% had evidence of a lipid-lowering therapy in the past 6 months: 45% in the secondary prevention group, 31% in the severe hypercholesterolemia group, 36% in the diabetes mellitus group, and 17% in the elevated 10-year risk group. Conclusions The substantial gaps in LDL-C treatment and goal attainment among members of an employer-sponsored medical plan who were mostly aware of their LDL-C levels indicate the need for gap-closure initiatives.

Performance of Plasma Biomarkers and Diagnostic Panels for Nonalcoholic Steatohepatitis and Advanced Fibrosis in Patients With Type 2 Diabetes.

OBJECTIVE: The 2019 Standards of Medical Care in Diabetes suggested that patients with nonalcoholic fatty liver disease (NAFLD) should be evaluated for liver fibrosis. However, the performance of noninvasive clinical models/scores and plasma biomarkers for the diagnosis of nonalcoholic steatohepatitis (NASH) and advanced fibrosis has not been carefully assessed in patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: In this cross-sectional study, patients (n = 213) had a liver MRS, and those with a diagnosis of NAFLD underwent a percutaneous liver biopsy. Several noninvasive clinical models/scores and plasma biomarkers were measured to identify NASH and advanced fibrosis (NASH: ALT, cytokeratin-18, NashTest 2, HAIR, BARD, and OWLiver; advanced fibrosis: AST, fragments of propeptide of type III procollagen [PRO-C3], FIB-4, APRI, NAFLD fibrosis score, and FibroTest). RESULTS: None of the noninvasive tools assessed for the diagnosis of NASH in patients with T2DM had an optimum performance (all areas under the curve [AUCs] <0.80). Of note, none of the panels or biomarkers was able to outperform plasma ALT (AUC 0.78 [95% CI 0.71-0.84]). Performance was better to diagnose advanced fibrosis, in which plasma PRO-C3, AST, and APRI showed better results than the other approaches (AUC 0.90 [0.85-0.95], 0.85 [0.80-0.91], and 0.86 [0.80-0.91], respectively). Again, none of the approaches did significantly better than plasma AST. Sequential use of plasma AST and other noninvasive tests may help in limiting the number of liver biopsies required to identify patients with advanced fibrosis. CONCLUSIONS: Performance of noninvasive clinical models/scores and plasma biomarkers for the diagnosis of NASH or advanced fibrosis was suboptimal in patients with T2DM. Combination of multiple tests may provide an alternative to minimize the need for liver biopsies to detect fibrosis in these patients.

Population health screenings for the prevention of chronic disease progression.

OBJECTIVES: Early detection of disease enables prompt treatment that can prevent disease progression and costly health outcomes. We report incidence of previously unrecognized disease and investigate the expected effect of early detection and care on health outcomes. STUDY DESIGN: Population health study based on laboratory evidence. METHODS: Laboratory evidence of prediabetes, diabetes, chronic kidney disease, and colorectal cancer was evaluated in an employee and spouse population (65% women; mean [SD] age = 46 [12] years). Expected disease progression was assessed. RESULTS: Annual screening found laboratory evidence for 1185 previously unrecognized cases of prediabetes, 287 cases of diabetes, 73 cases of chronic kidney disease, and 669 positive colorectal screens per 10,000 people. CONCLUSIONS: Early identification and appropriate medical care may delay 34 cases of end-stage kidney disease and prevent diabetes-related complications, 210 cases of diabetes, and 3 cases of late-stage colorectal cancer over 5 years per 1000 cases identified.

Association of cardiovascular events and lipoprotein particle size: Development of a risk score based on functional data analysis.

BACKGROUND: Functional data is data represented by functions (curves or surfaces of a low-dimensional index). Functional data often arise when measurements are collected over time or across locations. In the field of medicine, plasma lipoprotein particles can be quantified according to particle diameter by ion mobility. GOAL: We wanted to evaluate the utility of functional analysis for assessing the association of plasma lipoprotein size distribution with cardiovascular disease after adjustment for established risk factors including standard lipids. METHODS: We developed a model to predict risk of cardiovascular disease among participants in a case-cohort study of the Malmö Prevention Project. We used a linear model with 311 coefficients, corresponding to measures of lipoprotein mass at each of 311 diameters, and assumed these coefficients varied smoothly along the diameter index. The smooth function was represented as an expansion of natural cubic splines where the smoothness parameter was chosen by assessment of a series of nested splines. Cox proportional hazards models of time to a first cardiovascular disease event were used to estimate the smooth coefficient function among a training set consisting of one half of the participants. The resulting model was used to calculate a functional risk score for the remaining half of the participants (test set) and its association with events was assessed in Cox models that adjusted for traditional cardiovascular risk factors. RESULTS: In the test set, participants with a functional risk score in the highest quartile were found to be at increased risk of cardiovascular events compared with the lowest quartile (Hazard ratio = 1.34; 95% Confidence Interval: 1.05 to 1.70) after adjustment for established risk factors. CONCLUSION: In an independent test set of Malmö Prevention Project participants, the functional risk score was found to be associated with cardiovascular events after adjustment for traditional risk factors including standard lipids.

Insulin Resistance Probability Scores for Apparently Healthy Individuals.

CONTEXT: Insulin resistance (IR) can progress to type 2 diabetes. Therefore, timely identification of IR could facilitate disease prevention efforts. However, direct measurement of IR is not feasible in a clinical setting. OBJECTIVE: Develop a clinically practical probability score to assess IR in apparently healthy individuals based on levels of insulin, C-peptide, and other risk factors. DESIGN: Cross-sectional study. PARTICIPANTS: Apparently healthy individuals who volunteered to participate in studies of IR. MAIN OUTCOME MEASURE: IR, defined as the top tertile of steady-state plasma glucose during an insulin-suppression test. RESULTS: In a study of 535 participants, insulin, C-peptide, creatinine, body mass index (BMI), and triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL-C) were independently associated with IR (all P < 0.05) in a model that included age, sex, ethnicity, BMI, blood pressure, insulin, C-peptide, fasting glucose, low-density lipoprotein cholesterol, TG/HDL-C, alanine aminotransferase, and creatinine. For an IR probability score based on a model that included insulin, C-peptide, creatinine, TG/HDL-C, and BMI, the odds ratio was 26.7 (95% CI 14.0 to 50.8) for those with scores >66% compared with those with scores <33%. When only insulin and C-peptide were included in the model, the odds ratio was 15.6 (95% CI 7.5 to 32.4) for those with scores >66% compared with those with scores <33%. CONCLUSIONS: An IR probability score based on insulin, C-peptide, creatinine, TG/HDL-C, and BMI or a score based on only insulin and C-peptide may help assess IR in apparently healthy individuals.

Validation of a genetic risk score for atrial fibrillation: A prospective multicenter cohort study.

BACKGROUND: Atrial fibrillation (AF) is the most commonly encountered arrhythmia and is associated with an elevated risk of stroke. Improving the identification of patients with the highest risk for AF to enable appropriate surveillance and treatment, if necessary, is critical to reducing AF-associated morbidity and mortality. Multiple common single nucleotide polymorphisms (SNPs) are unequivocally associated with the lifetime risk of AF. In the current study we aimed to prospectively validate an AF genetic risk score (GRS) in previously undiagnosed patients at risk for AF. METHODS AND FINDINGS: Individuals 40 years of age or older with 1 clinical risk factor for AF, presenting with symptoms of AF, or with a first diagnosis of AF, were enrolled for genetic testing and ambulatory cardiac rhythm monitoring with an adhesive patch monitor or a long-term Holter monitor (mean wear time 10 days 21 hours and 13 days 18 hours, respectively). An AF event was the first diagnosis of AF by ECG, patch monitor, or long-term Holter monitor. The AF GRS was determined for each participant based on the weighted contribution of 12 genetic risk loci. Of 904 participants, 85 manifested AF. Their mean age was 66.2 (SD 11.8) years; 38% of participants were male. Participants in the highest quintile of AF GRS were more likely (odds ratio 3.11; 95% CI 1.27-7.58; p = 0.01) to have had an AF event than participants in the lowest quintile after adjusting for age, sex, smoking status, BMI, hypertension, diabetes mellitus, heart failure, and prior myocardial infarction. Study limitations included an ethnically homogenous population, a restricted rhythm monitoring period, and the evolving discovery of SNPs associated with AF. CONCLUSIONS: Prospective assessment of a GRS for AF identified participants with elevated risk of AF beyond established clinical criteria. Accordingly, a GRS for AF could be incorporated into overall risk assessment to better identify patients at the highest risk of developing AF, although further testing in larger populations is needed to confirm these findings. TRIAL REGISTRATION: ClinicalTrials.gov NCT01970969.

Prediction of Type 2 Diabetes by Hemoglobin A1c in Two Community-Based Cohorts.

OBJECTIVE: Hemoglobin A1c (HbA1c) can be used to assess type 2 diabetes (T2D) risk. We asked whether HbA1c was associated with T2D risk in four scenarios of clinical information availability: 1) HbA1c alone, 2) fasting laboratory tests, 3) clinic data, and 4) fasting laboratory tests and clinic data. RESEARCH DESIGN AND METHODS: We studied a prospective cohort of white (N = 11,244) and black (N = 2,294) middle-aged participants without diabetes in the Framingham Heart Study and Atherosclerosis Risk in Communities study. Association of HbA1c with incident T2D (defined by medication use or fasting glucose [FG] ≥126 mg/dL) was evaluated in regression models adjusted for 1) age and sex (demographics); 2) demographics, FG, HDL, and triglycerides; 3) demographics, BMI, blood pressure, and T2D family history; or 4) all preceding covariates. We combined results from cohort and race analyses by random-effects meta-analyses. Subsidiary analyses tested the association of HbA1c with developing T2D within 8 years or only after 8 years. RESULTS: Over 20 years, 3,315 individuals developed T2D. With adjustment for demographics, the odds of T2D increased fourfold for each percentage-unit increase in HbA1c. The odds ratio (OR) was 4.00 (95% CI 3.14, 5.10) for blacks and 4.73 (3.10, 7.21) for whites, resulting in a combined OR of 4.50 (3.35, 6.03). After adjustment for fasting laboratory tests and clinic data, the combined OR was 2.68 (2.15, 3.34) over 20 years, 5.79 (2.51, 13.36) within 8 years, and 2.23 (1.94, 2.57) after 8 years. CONCLUSIONS: HbA1c predicts T2D in different common scenarios and is useful for identifying individuals with elevated T2D risk in both the short- and long-term.

LDL subfractions are associated with incident cardiovascular disease in the Malmö Prevention Project Study.

BACKGROUND AND AIMS: After assessing the risk for cardiovascular disease (CVD) based on traditional risk factors, decisions concerning lipid lowering therapy might remain uncertain. To investigate whether lipoprotein subfraction levels could aid these decisions, we assessed the association between lipoprotein subfractions and CVD, after adjustment for traditional risk factors including standard lipids. METHODS: Using a case-cohort design, participants were randomly drawn from the Malmö Prevention Project (MPP), a population-based prospective study of 18,240 participants, and supplemented with additional incident CVD events (5764 participants, 1784 CVD events). RESULTS: Low density lipoprotein particle number (LDL-P) and individual subfractions ranging in size from very-small to large were associated with CVD (continuous p value (pcont) < 0.001) while adjusting for age, sex, hypertension, smoking, and diabetes. After further adjustment for LDL-C, HDL-C, and triglycerides, very small LDL subfraction (b) (LDL-VS (b)) remained associated with CVD (HR = 1.23, 95% CI, 1.06 to 1.43 for top vs. bottom quartile, pcont = 0.03). Among participants with low/intermediate risk [without diabetes and with LDL-C <3.36 mmol/L (<130 mg/dL)], the fully adjusted HR for LDL-small (top vs. bottom quartile) was 1.48 (95% CI 1.02 to 2.17, pcont = 0.03). Among those with very-high risk (>20% 10-year risk of CVD), LDL-VS(a) and LDL-VS(b) were associated with CVD in fully adjusted models (HR = 1.37, 95% CI 1.12 to 1.67 and HR = 1.28, 95% CI 1.07 to 1.53, respectively, pcont≤0.03). CONCLUSIONS: Smaller LDL particles are associated with incident CVD independently of traditional risk factors, including standard lipids, in participants with low/intermediate and very-high risk, who might benefit from improved risk assessment.

Metabolic Mediators of the Effects of Family History and Genetic Risk Score on Coronary Heart Disease-Findings From the Malmö Diet and Cancer Study.

BACKGROUND: Family history of coronary heart disease (CHD) as well as genetic predisposition to CHD assessed by a genetic risk score (GRS) are predictors of CHD risk. It is, however, uncertain to what extent these risk predictors are mediated by major metabolic pathways. METHODS AND RESULTS: Total effects of self-reported family history and a 50-variant GRS (GRS50), as well as effects mediated by apolipoprotein B and A-I (apoB, apoA-I), blood pressure, and diabetes mellitus, on incidence of CHD were estimated in 23 595 participants of the Malmö Diet and Cancer study (a prospective, population-based study). During a median follow-up of 14.4 years, 2213 participants experienced a first CHD event. Family history of CHD and GRS50 (highest versus other quintiles) were associated with incident CHD, with hazard ratios of 1.52 (95% CI: 1.39-1.65) and 1.53 (95% CI: 1.39-1.68), respectively, after adjusting for age, sex, and smoking status. Small proportions of the family history effect were mediated by metabolic risk factors: 8.3% (95% CI: 5.8-11.7%) by the apoB pathway, 1.7% (95% CI: 0.2-3.4%) by apoA-I, 8.5% (95% CI: 5.9-12.0%) by blood pressure, and 1.5% (95% CI: -0.8% to 3.8%) by diabetes mellitus. Similarly, small proportions of GRS50 were mediated: 8.1% (95% CI: 5.5-11.8%) by apoB, 1.2% (95% CI: 0.5-3.0%) by apoA-I, 4.2% (95% CI: 1.3-7.5%) by blood pressure, and -0.9% (95% CI: -3.7% to 1.6%) by diabetes mellitus. CONCLUSIONS: A fraction of the CHD risk associated with family history or with GRS50 is mediated through elevated blood lipids and hypertension, but not through diabetes mellitus. However, a major part (≥80%) of the genetic effect operates independently of established metabolic risk factor pathways.

Use of low density lipoprotein particle number levels as an aid in statin treatment decisions for intermediate risk patients: a cost-effectiveness analysis.

BACKGROUND: The 2013 ACC/AHA guideline recommended either no statin therapy or moderate-intensity statin therapy (MST) for intermediate risk patients-those with 5-7.5% 10-year risk and without cardiovascular disease (CVD), hypercholesterolemia or diabetes. The guideline further suggested that the therapy choice be based on patient-clinician discussions of risks and benefits. Since low-density lipoprotein particle (LDL-P) levels were reported to be associated with CVD independently of traditional risk factors in intermediate and low risk patients, we investigated the cost-effectiveness of using LDL-P levels to identify intermediate risk patients likely to benefit from initiating or intensifying statin therapy. METHODS: We evaluated 5 care strategies for intermediate risk patients. These included the strategies suggested by the guideline: no-statin therapy and MST. We compared each of these strategies to a related strategy that incorporated LDL-P testing. No-statin therapy was compared with the strategy of MST for those with high LDL-P levels and no statin therapy for all other patients (test-and-MST). MST was compared with the strategy of high-intensity statin therapy (HST) for those with high LDL-P levels and MST for all other patients (test-and-HST). We also evaluated the strategy of HST for all. Costs (payer perspective) and utilities were assessed over a 5-year time horizon in a Markov model of 100,000 hypothetical intermediate risk patients. RESULTS: HST dominated all other strategies, costing less and-despite causing 739 more cases of diabetes than did MST-resulting in more quality adjusted life-years (QALYs). For patient-clinician discussions that would otherwise lead to the MST strategy, we found the test-and-HST strategy reduced costs by $4.67 MM and resulted in 134 fewer CVD events and 115 additional QALYs. For patient-clinician discussions that would otherwise lead to no statin therapy, we found that the test-and-MST strategy reduced costs by $3.25 MM, resulted in 97 fewer CVD events and 44 additional QALYs. CONCLUSIONS: The HST strategy was cost saving and improved outcomes in intermediate risk patients. For patient and clinicians concerned about the adverse events associated with HST, using LDL-P levels to target intensified statin therapy could improve outcomes and reduce costs.