Triglyceride Lowering with Pemafibrate to Reduce Cardiovascular Risk.

BACKGROUND: High triglyceride levels are associated with increased cardiovascular risk, but whether reductions in these levels would lower the incidence of cardiovascular events is uncertain. Pemafibrate, a selective peroxisome proliferator-activated receptor α modulator, reduces triglyceride levels and improves other lipid levels. METHODS: In a multinational, double-blind, randomized, controlled trial, we assigned patients with type 2 diabetes, mild-to-moderate hypertriglyceridemia (triglyceride level, 200 to 499 mg per deciliter), and high-density lipoprotein (HDL) cholesterol levels of 40 mg per deciliter or lower to receive pemafibrate (0.2-mg tablets twice daily) or matching placebo. Eligible patients were receiving guideline-directed lipid-lowering therapy or could not receive statin therapy without adverse effects and had low-density lipoprotein (LDL) cholesterol levels of 100 mg per deciliter or lower. The primary efficacy end point was a composite of nonfatal myocardial infarction, ischemic stroke, coronary revascularization, or death from cardiovascular causes. RESULTS: Among 10,497 patients (66.9% with previous cardiovascular disease), the median baseline fasting triglyceride level was 271 mg per deciliter, HDL cholesterol level 33 mg per deciliter, and LDL cholesterol level 78 mg per deciliter. The median follow-up was 3.4 years. As compared with placebo, the effects of pemafibrate on lipid levels at 4 months were -26.2% for triglycerides, -25.8% for very-low-density lipoprotein (VLDL) cholesterol, -25.6% for remnant cholesterol (cholesterol transported in triglyceride-rich lipoproteins after lipolysis and lipoprotein remodeling), -27.6% for apolipoprotein C-III, and 4.8% for apolipoprotein B. A primary end-point event occurred in 572 patients in the pemafibrate group and in 560 of those in the placebo group (hazard ratio, 1.03; 95% confidence interval, 0.91 to 1.15), with no apparent effect modification in any prespecified subgroup. The overall incidence of serious adverse events did not differ significantly between the groups, but pemafibrate was associated with a higher incidence of adverse renal events and venous thromboembolism and a lower incidence of nonalcoholic fatty liver disease. CONCLUSIONS: Among patients with type 2 diabetes, mild-to-moderate hypertriglyceridemia, and low HDL and LDL cholesterol levels, the incidence of cardiovascular events was not lower among those who received pemafibrate than among those who received placebo, although pemafibrate lowered triglyceride, VLDL cholesterol, remnant cholesterol, and apolipoprotein C-III levels. (Funded by the Kowa Research Institute; PROMINENT ClinicalTrials.gov number, NCT03071692.).

Differences in Metabolomic Profiles Between Black and White Women and Risk of Coronary Heart Disease: an Observational Study of Women From Four US Cohorts.

BACKGROUND: Racial differences in metabolomic profiles may reflect underlying differences in social determinants of health by self-reported race and may be related to racial disparities in coronary heart disease (CHD) among women in the United States. However, the magnitude of differences in metabolomic profiles between Black and White women in the United States has not been well-described. It also remains unknown whether such differences are related to differences in CHD risk. METHODS: Plasma metabolomic profiles were analyzed using liquid chromatography-tandem mass spectrometry in the WHI-OS (Women's Health Initiative-Observational Study; 138 Black and 696 White women), WHI-HT trials (WHI-Hormone Therapy; 156 Black and 1138 White women), MESA (Multi-Ethnic Study of Atherosclerosis; 114 Black and 219 White women), JHS (Jackson Heart Study; 1465 Black women with 107 incident CHD cases), and NHS (Nurses' Health Study; 2506 White women with 136 incident CHD cases). First, linear regression models were used to estimate associations between self-reported race and 472 metabolites in WHI-OS (discovery); findings were replicated in WHI-HT and validated in MESA. Second, we used elastic net regression to construct a racial difference metabolomic pattern (RDMP) representing differences in the metabolomic patterns between Black and White women in the WHI-OS; the RDMP was validated in the WHI-HT and MESA. Third, using conditional logistic regressions in the WHI (717 CHD cases and 719 matched controls), we examined associations of metabolites with large differences in levels by race and the RDMP with risk of CHD, and the results were replicated in Black women from the JHS and White women from the NHS. RESULTS: Of the 472 tested metabolites, levels of 259 (54.9%) metabolites, mostly lipid metabolites and amino acids, significantly differed between Black and White women in both WHI-OS and WHI-HT after adjusting for baseline characteristics, socioeconomic status, lifestyle factors, baseline health conditions, and medication use (false discovery rate <0.05); similar trends were observed in MESA. The RDMP, composed of 152 metabolites, was identified in the WHI-OS and showed significantly different distributions between Black and White women in the WHI-HT and MESA. Higher RDMP quartiles were associated with an increased risk of incident CHD (odds ratio=1.51 [0.97-2.37] for the highest quartile comparing to the lowest; Ptrend=0.02), independent of self-reported race and known CHD risk factors. In race-stratified analyses, the RDMP-CHD associations were more pronounced in White women. Similar patterns were observed in Black women from the JHS and White women from the NHS. CONCLUSIONS: Metabolomic profiles significantly and substantially differ between Black and White women and may be associated with CHD risk and racial disparities in US women.

Low-Dose Methotrexate for the Prevention of Atherosclerotic Events.

BACKGROUND: Inflammation is causally related to atherothrombosis. Treatment with canakinumab, a monoclonal antibody that inhibits inflammation by neutralizing interleukin-1ß, resulted in a lower rate of cardiovascular events than placebo in a previous randomized trial. We sought to determine whether an alternative approach to inflammation inhibition with low-dose methotrexate might provide similar benefit. METHODS: We conducted a randomized, double-blind trial of low-dose methotrexate (at a target dose of 15 to 20 mg weekly) or matching placebo in 4786 patients with previous myocardial infarction or multivessel coronary disease who additionally had either type 2 diabetes or the metabolic syndrome. All participants received 1 mg of folate daily. The primary end point at the onset of the trial was a composite of nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. Near the conclusion of the trial, but before unblinding, hospitalization for unstable angina that led to urgent revascularization was added to the primary end point. RESULTS: The trial was stopped after a median follow-up of 2.3 years. Methotrexate did not result in lower interleukin-1ß, interleukin-6, or C-reactive protein levels than placebo. The final primary end point occurred in 201 patients in the methotrexate group and in 207 in the placebo group (incidence rate, 4.13 vs. 4.31 per 100 person-years; hazard ratio, 0.96; 95% confidence interval [CI], 0.79 to 1.16). The original primary end point occurred in 170 patients in the methotrexate group and in 167 in the placebo group (incidence rate, 3.46 vs. 3.43 per 100 person-years; hazard ratio, 1.01; 95% CI, 0.82 to 1.25). Methotrexate was associated with elevations in liver-enzyme levels, reductions in leukocyte counts and hematocrit levels, and a higher incidence of non-basal-cell skin cancers than placebo. CONCLUSIONS: Among patients with stable atherosclerosis, low-dose methotrexate did not reduce levels of interleukin-1ß, interleukin-6, or C-reactive protein and did not result in fewer cardiovascular events than placebo. (Funded by the National Heart, Lung, and Blood Institute; CIRT ClinicalTrials.gov number, NCT01594333.).

Adverse effects related to methotrexate polyglutamate levels: adjudicated results from the cardiovascular inflammation reduction trial.

OBJECTIVES: Methotrexate is widely used at low dosages (LD-MTX) for non-oncologic indications and is associated with a variety of adverse effects (AEs). We sought to determine whether concentrations of the active metabolite, MTX polyglutamates (MTX-PGs) 1-5, correlate with AEs. METHOD: We examined data from the LD-MTX arm of the randomized double-blind Cardiovascular Inflammation Reduction Trial (CIRT). All AEs were blindly adjudicated and monitoring laboratories were tested centrally. The MTX-PGs 1-5 were assessed in one reference laboratory using liquid chromatography-tandem mass spectrometry. Based on prior literature, MTX-PGs 3-5 were chosen as the exposure of interest and quartiles of MTX-PGs 3-5 were assessed for their relationship with all AEs and each pre-specified category of AE using adjusted Cox proportional hazards regression. RESULTS: Of the 2391 subjects randomized to LD-MTX, MTX-PG levels were available for 1319 subjects (median dosage 16.1 mg/week) from the 8 month visit. We followed these subjects for a median of 2.2 years [interquartile range (IQR) 1.5-2.9]. Higher MTX-PG3-5 levels were related to an increased risk of anaemia [compared with quartile 1 (Q1); hazard ratio (HR) for Q4 1.27 (95% CI 0.98, 1.65), P for trend = 0.05] and a decreased risk of thrombocytopenia [HR for Q4 0.52 (95% CI 0.32, 0.84), P for trend = 0.05]. MTX-PG3-5 levels >134 nmol/l were associated with an increased risk of liver abnormalities [HR 1.36 (95% CI 1.08, 1.72)]. CONCLUSIONS: Higher MTX- PG3-5 levels were modestly associated with LD-MTX AEs, including anaemia and liver function abnormalities, but a reduced risk of thrombocytopenia and haemorrhage. CLINICAL TRIAL REGISTRATION: NCT01594333.

Adverse Effects of Low-Dose Methotrexate: A Randomized Trial.

Background: Low-dose methotrexate (LD-MTX) is the most commonly used drug for systemic rheumatic diseases worldwide and is the recommended first-line agent for rheumatoid arthritis. Despite extensive clinical use for more than 30 years, few data on adverse event (AE) rates derive from randomized, placebo-controlled trials, where both causality and magnitude of risk can be inferred. Objective: To investigate AE rates, risk, and risk differences comparing LD-MTX versus placebo. Design: Prespecified secondary analyses of a double-blind, placebo-controlled, randomized trial. (ClinicalTrials.gov: NCT01594333). Setting: North America. Participants: Adults with known cardiovascular disease and diabetes or metabolic syndrome. Intervention: Random allocation to LD-MTX (≤20 mg/wk) or placebo. All participants received folic acid, 1 mg/d, 6 days per week. Measurements: Risks for specific AEs of interest, as well as for all AEs, were compared across treatment groups after blinded adjudication. Results: After an active run-in period, 6158 patients were enrolled and 4786 randomly assigned to a group; median follow-up was 23 months and median dosage 15 mg/wk. Among the randomly assigned participants, 81.2% were male, median age was 65.7 years, and median body mass index was 31.5 kg/m2. Of 2391 participants assigned to LD-MTX, 2080 (87.0%) had an AE of interest, compared with 1951 of 2395 (81.5%) assigned to placebo (hazard ratio [HR], 1.17 [95% CI, 1.10 to 1.25]). The relative hazards of gastrointestinal (HR, 1.91 [CI, 1.75 to 2.10]), pulmonary (HR, 1.52 [CI, 1.16 to 1.98]), infectious (HR, 1.15 [CI, 1.01 to 1.30]), and hematologic (HR, 1.15 [CI, 1.07 to 1.23]) AEs were elevated for LD-MTX versus placebo. With the exception of increased risk for skin cancer (HR, 2.05 [CI, 1.28 to 3.28]), the treatment groups did not differ in risk for other cancer or mucocutaneous, neuropsychiatric, or musculoskeletal AEs. Renal AEs were reduced in the LD-MTX group (HR, 0.85 [CI, 0.78 to 0.93]). Limitation: The trial was done in patients without rheumatic disease who tolerated LD-MTX during an active run-in period. Conclusion: Use of LD-MTX was associated with small to moderate elevations in risks for skin cancer and gastrointestinal, infectious, pulmonary, and hematologic AEs, whereas renal AEs were decreased. Primary Funding Source: National Institutes of Health.

Metabolic Predictors of Incident Coronary Heart Disease in Women.

BACKGROUND: Although metabolomic profiling offers promise for the prediction of coronary heart disease (CHD), and metabolic risk factors are more strongly associated with CHD in women than men, limited data are available for women. METHODS: We applied a liquid chromatography-tandem mass spectrometry metabolomics platform to measure 371 metabolites in a discovery set of postmenopausal women (472 incident CHD cases, 472 controls) with validation in an independent set of postmenopausal women (312 incident CHD cases, 315 controls). RESULTS: Eight metabolites, primarily oxidized lipids, were significantly dysregulated in cases after the adjustment for matching and CHD risk factors in both the discovery and validation data sets. One oxidized phospholipid, C34:2 hydroxy-phosphatidylcholine, remained associated with CHD after further adjustment for other validated metabolites. Subjects with C34:2 hydroxy-phosphatidylcholine levels in the highest quartile had a 4.7-fold increase in CHD odds in comparison with the lowest quartile; C34:2 hydroxy-phosphatidylcholine also significantly improved the area under the curve (P<0.01) for CHD. The C34:2 hydroxy-phosphatidylcholine findings were replicated in a third replication data set of 980 men and women (230 cardiovascular events) with a stronger association observed in women. CONCLUSIONS: These data replicate known metabolite predictors, identify novel markers, and support the relationship between lipid oxidation and subsequent CHD.

Estimating the receiver operating characteristic curve in matched case control studies.

The matched case-control design is frequently used in the study of complex disorders and can result in significant gains in efficiency, especially in the context of measuring biomarkers; however, risk prediction in this setting is not straightforward. We propose an inverse-probability weighting approach to estimate the predictive ability associated with a set of covariates. In particular, we propose an algorithm for estimating the summary index, area under the curve corresponding to the Receiver Operating Characteristic curve associated with a set of pre-defined covariates for predicting a binary outcome. By combining data from the parent cohort with that generated in a matched case control study, we describe methods for estimation of the population parameters of interest and the corresponding area under the curve. We evaluate the bias associated with the proposed methods in simulations by considering a range of parameter settings. We illustrate the methods in two data applications: (1) a prospective cohort study of cardiovascular disease in women, the Women's Health Study, and (2) a matched case-control study nested within the Nurses' Health Study aimed at risk prediction of invasive breast cancer.

Rationale and design of the Pemafibrate to Reduce Cardiovascular Outcomes by Reducing Triglycerides in Patients with Diabetes (PROMINENT) study.

Observational, genetic, and experimental data indicate that triglyceride rich lipoproteins (TRLs) likely participate causally in atherothrombosis. Yet, robust clinical trial evidence that triglyceride (TG) lowering therapy reduces cardiovascular events remains elusive. The selective peroxisome proliferator-activated receptor alpha modulator (SPPARM-α), pemafibrate, will be used to target residual cardiovascular risk remaining after treatment to reduce low-density lipoprotein cholesterol (LDL-C) in individuals with the dyslipidemia of type 2 diabetes mellitus (T2). The PROMINENT study will randomly allocate approximately 10,000 participants with T2D, mild-to-moderate hypertriglyceridemia (TG: 200-499 mg/dl; 2.26-5.64 mmol/l) and low high-density lipoprotein cholesterol levels (HDL-C: ≤40 mg/dl; 1.03 mmol/l) to either pemafibrate (0.2 mg twice daily) or matching placebo with an average expected follow-up period of 3.75 years (total treatment phase 5 years; 24 countries). At study entry, participants must be receiving either moderate-to-high intensity statin therapy or meet specified LDL-C criteria. The study population will be one-third primary and two-thirds secondary prevention (established cardiovascular disease). The primary endpoint is a composite of nonfatal myocardial infarction, nonfatal ischemic stroke, hospitalization for unstable angina requiring urgent coronary revascularization, and cardiovascular death. This event-driven study will complete when 1092 adjudicated primary endpoints have accrued with at least 200 occurring in women. Statistical power is at least 90% to detect an 18% reduction in the primary endpoint. Pre-specified secondary and tertiary endpoints include all-cause mortality, hospitalization for heart failure, new or worsening peripheral artery disease, new or worsening diabetic retinopathy and nephropathy, and change in biomarkers including select lipid and non-lipid biomarkers, inflammatory and glycemic parameters.

Are Genetic Tests for Atherosclerosis Ready for Routine Clinical Use?

In this review, we lay out 3 areas currently being evaluated for incorporation of genetic information into clinical practice related to atherosclerosis. The first, familial hypercholesterolemia, is the clearest case for utility of genetic testing in diagnosis and potentially guiding treatment. Already in use for confirmatory testing of familial hypercholesterolemia and for cascade screening of relatives, genetic testing is likely to expand to help establish diagnoses and facilitate research related to most effective therapies, including new agents, such as PCSK9 inhibitors. The second area, adding genetic information to cardiovascular risk prediction for primary prevention, is not currently recommended. Although identification of additional variants may add substantially to prediction in the future, combining known variants has not yet demonstrated sufficient improvement in prediction for incorporation into commonly used risk scores. The third area, pharmacogenetics, has utility for some therapies today. Future utility for pharmacogenetics will wax or wane depending on the nature of available drugs and therapeutic strategies.

Clinical risk reclassification at 10 years.

Three papers in this issue focus on the role of calibration in model fit statistics, including the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). This commentary reviews the development of such reclassification statistics along with more recent advances in our understanding of these measures. We show how the two-category NRI and the IDI are affected by changes in the event rate in theory and in an applied example. We also describe the role of calibration and how it may be assessed. Finally, we discuss the relevance of the event rate NRI for clinical use. Copyright © 2017 John Wiley & Sons, Ltd.

Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption.

Coffee, a major dietary source of caffeine, is among the most widely consumed beverages in the world and has received considerable attention regarding health risks and benefits. We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91,462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log10Bayes factor (BF)>5.64) with per-allele effect sizes of 0.03-0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P<5 × 10(-8)).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.

Comparison of lifestyle-based and traditional cardiovascular disease prediction in a multiethnic cohort of nonsmoking women.

BACKGROUND: Healthy levels of lifestyle factors can reduce the risk of cardiovascular disease. However, except for smoking status, often considered a traditional risk factor, their effect on cardiovascular risk prediction is unclear. METHODS AND RESULTS: We used a case-cohort design of postmenopausal nonsmokers in the multiethnic Women's Health Initiative Observational Study (1587 cases and 1808 subcohort participants) with a median follow-up of 10 years in noncases. Compared with nonsmokers with no other healthy lifestyle factors (healthy diet, recreational physical activity, moderate alcohol use, and low adiposity), the risk of cardiovascular disease was lower for each additional factor (hazard ratio for trend, 0.82; 95% confidence interval, 0.76-0.89), with a 45% reduction in risk with all factors (95% confidence interval, 0.36-0.84). When lifestyle factors were added to traditional risk factor models (variables from the Pooled Cohort and Reynolds risk scores), only recreational physical activity remained independently associated with the risk of cardiovascular disease. The addition of detailed lifestyle measures to traditional models showed a change in the integrated discrimination improvement and continuous net reclassification improvement (P<0.01 for both) but had little impact on more clinically relevant risk stratification measures. CONCLUSIONS: Although lifestyle factors have important effects on cardiovascular disease risk factors and subsequent risk, their addition to established cardiovascular disease risk models does not result in clear improvement in overall prediction.

Novel locus including FGF21 is associated with dietary macronutrient intake.

Dietary intake of macronutrients (carbohydrate, protein, and fat) has been associated with risk of chronic conditions such as obesity and diabetes. Family studies have reported a moderate contribution of genetics to variation in macronutrient intake. In a genome-wide meta-analysis of a population-based discovery cohort (n = 33 533), rs838133 in FGF21 (19q13.33), rs197273 near TRAF family member-associated NF-kappa-B activator (TANK) (2p24.2), and rs10163409 in FTO (16q12.2) were among the top associations (P < 10(-5)) for percentage of total caloric intake from protein and carbohydrate. rs838133 was replicated in silico in an independent sample from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE) Nutrition Working Group (n = 38 360) and attained genome-wide significance in combined analysis (Pjoint = 7.9 × 10(-9)). A cytokine involved in cellular metabolism, FGF21 is a potential susceptibility gene for obesity and type 2 diabetes. Our results highlight the potential of genetic variation for determining dietary macronutrient intake.

Tests of calibration and goodness-of-fit in the survival setting.

To access the calibration of a predictive model in a survival analysis setting, several authors have extended the Hosmer-Lemeshow goodness-of-fit test to survival data. Grønnesby and Borgan developed a test under the proportional hazards assumption, and Nam and D'Agostino developed a nonparametric test that is applicable in a more general survival setting for data with limited censoring. We analyze the performance of the two tests and show that the Grønnesby-Borgan test attains appropriate size in a variety of settings, whereas the Nam-D'Agostino method has a higher than nominal Type 1 error when there is more than trivial censoring. Both tests are sensitive to small cell sizes. We develop a modification of the Nam-D'Agostino test to allow for higher censoring rates. We show that this modified Nam-D'Agostino test has appropriate control of Type 1 error and comparable power to the Grønnesby-Borgan test and is applicable to settings other than proportional hazards. We also discuss the application to small cell sizes.

Cardiovascular disease risk prediction in women: is there a role for novel biomarkers?

BACKGROUND: Risk prediction is an integral part of the current US guidelines for cardiovascular disease in women. Although current risk prediction algorithms exist to identify women at increased 10-year risk of cardiovascular disease (CVD), clinicians and researchers have been interested in developing novel biomarkers that might improve predictive accuracy further. These biomarkers have led to important insights into the pathophysiology of CVD, but results for their ability to improve prediction or guide preventive therapy have been mixed. The incidence of CVD is lower in women than men, and the effects of a number of traditional biomarkers on CVD risk differ in women compared to men. Both of these factors influence the ability to accurately predict CVD risk. CONTENT: We review the distinctive aspects of CVD risk prediction in women, discuss the statistical challenges to improved risk prediction, and discuss a number of biomarkers in varying stages of development with a range of performance in prediction. SUMMARY: A variety of biomarkers from different pathophysiologic pathways have been evaluated for improving CVD risk. While many have been incompletely studied or have not been shown to improve risk prediction in women, others, such as high-sensitivity troponin T, have shown promise in improving risk prediction. Increasing inclusion of women in CVD studies will be crucial to providing opportunities to evaluate future biomarkers.

Genome-wide meta-analysis identifies regions on 7p21 (AHR) and 15q24 (CYP1A2) as determinants of habitual caffeine consumption.

We report the first genome-wide association study of habitual caffeine intake. We included 47,341 individuals of European descent based on five population-based studies within the United States. In a meta-analysis adjusted for age, sex, smoking, and eigenvectors of population variation, two loci achieved genome-wide significance: 7p21 (P = 2.4 × 10(-19)), near AHR, and 15q24 (P = 5.2 × 10(-14)), between CYP1A1 and CYP1A2. Both the AHR and CYP1A2 genes are biologically plausible candidates as CYP1A2 metabolizes caffeine and AHR regulates CYP1A2.

Tailoring Risk Prediction Models to Local Populations.

Importance: Risk estimation is an integral part of cardiovascular care. Local recalibration of guideline-recommended models could address the limitations of existing tools. Objective: To provide a machine learning (ML) approach to augment the performance of the American Heart Association's Predicting Risk of Cardiovascular Disease Events (AHA-PREVENT) equations when applied to a local population while preserving clinical interpretability. Design, Setting, and Participants: This cohort study used a New England-based electronic health record cohort of patients without prior atherosclerotic cardiovascular disease (ASCVD) who had the data necessary to calculate the AHA-PREVENT 10-year risk of developing ASCVD in the event period (2007-2016). Patients with prior ASCVD events, death prior to 2007, or age 79 years or older in 2007 were subsequently excluded. The final study population of 95 326 patients was split into 3 nonoverlapping subsets for training, testing, and validation. The AHA-PREVENT model was adapted to this local population using the open-source ML model (MLM) Extreme Gradient Boosting model (XGBoost) with minimal predictor variables, including age, sex, and AHA-PREVENT. The MLM was monotonically constrained to preserve known associations between risk factors and ASCVD risk. Along with sex, race and ethnicity data from the electronic health record were collected to validate the performance of ASCVD risk prediction in subgroups. Data were analyzed from August 2021 to February 2024. Main Outcomes and Measures: Consistent with the AHA-PREVENT model, ASCVD events were defined as the first occurrence of either nonfatal myocardial infarction, coronary artery disease, ischemic stroke, or cardiovascular death. Cardiovascular death was coded via government registries. Discrimination, calibration, and risk reclassification were assessed using the Harrell C index, a modified Hosmer-Lemeshow goodness-of-fit test and calibration curves, and reclassification tables, respectively. Results: In the test set of 38 137 patients (mean [SD] age, 64.8 [6.9] years, 22 708 [59.5]% women and 15 429 [40.5%] men; 935 [2.5%] Asian, 2153 [5.6%] Black, 1414 [3.7%] Hispanic, 31 400 [82.3%] White, and 2235 [5.9%] other, including American Indian, multiple races, unspecified, and unrecorded, consolidated owing to small numbers), MLM-PREVENT had improved calibration (modified Hosmer-Lemeshow P > .05) compared to the AHA-PREVENT model across risk categories in the overall cohort (χ23 = 2.2; P = .53 vs χ23 > 16.3; P < .001) and sex subgroups (men: χ23 = 2.1; P = .55 vs χ23 > 16.3; P < .001; women: χ23 = 6.5; P = .09 vs. χ23 > 16.3; P < .001), while also surpassing a traditional recalibration approach. MLM-PREVENT maintained or improved AHA-PREVENT's calibration in Asian, Black, and White individuals. Both MLM-PREVENT and AHA-PREVENT performed equally well in discriminating risk (approximate ΔC index, ±0.01). Using a clinically significant 7.5% risk threshold, MLM-PREVENT reclassified a total of 11.5% of patients. We visualize the recalibration through MLM-PREVENT ASCVD risk charts that highlight preserved risk associations of the original AHA-PREVENT model. Conclusions and Relevance: The interpretable ML approach presented in this article enhanced the accuracy of the AHA-PREVENT model when applied to a local population while still preserving the risk associations found by the original model. This method has the potential to recalibrate other established risk tools and is implementable in electronic health record systems for improved cardiovascular risk assessment.

Comparison of the Framingham and Reynolds Risk scores for global cardiovascular risk prediction in the multiethnic Women's Health Initiative.

BACKGROUND: Framingham-based and Reynolds Risk scores for cardiovascular disease (CVD) prediction have not been directly compared in an independent validation cohort. METHODS AND RESULTS: We selected a case-cohort sample of the multiethnic Women's Health Initiative Observational Cohort, comprising 1722 cases of major CVD (752 myocardial infarctions, 754 ischemic strokes, and 216 other CVD deaths) and a random subcohort of 1994 women without prior CVD. We estimated risk using the Adult Treatment Panel III (ATP-III) score, the Reynolds Risk Score, and the Framingham CVD model, reweighting to reflect cohort frequencies. Predicted 10-year risk varied widely between models, with ≥10% risk in 6%, 10%, and 41% of women with the ATP-III, Reynolds, and Framingham CVD models, respectively. Calibration was adequate for the Reynolds model, but the ATP-III and Framingham CVD models overestimated risk for coronary heart disease and major CVD, respectively. After recalibration, the Reynolds model demonstrated improved discrimination over the ATP-III model through a higher c statistic (0.765 versus 0.757; P=0.03), positive net reclassification improvement (NRI; 4.9%; P=0.02), and positive integrated discrimination improvement (4.1%; P<0.0001) overall, excluding diabetics (NRI=4.2%; P=0.01), and in white (NRI=4.3%; P=0.04) and black (NRI=11.4%; P=0.13) women. The Reynolds (NRI=12.9%; P<0.0001) and ATP-III (NRI=5.9%; P=0.0001) models demonstrated better discrimination than the Framingham CVD model. CONCLUSIONS: The Reynolds Risk Score was better calibrated than the Framingham-based models in this large external validation cohort. The Reynolds score also showed improved discrimination overall and in black and white women. Large differences in risk estimates exist between models, with clinical implications for statin therapy.