An assessment of the potential miscalibration of cardiovascular disease risk predictions caused by a secular trend in cardiovascular disease in England

Abstract Background A downwards secular trend in the incidence of cardiovascular disease (CVD) in England was identified through previous work and the literature. Risk prediction models for primary prevention of CVD do not model this secular trend, this could result in over prediction of risk for individuals in the present day. We evaluate the effects of modelling this secular trend, and also assess whether it is driven by an increase in statin use during follow up. Methods We derived a cohort of patients (1998–2015) eligible for cardiovascular risk prediction from the Clinical Practice Research Datalink with linked hospitalisation and mortality records (N = 3,855,660). Patients were split into development and validation cohort based on their cohort entry date (before/after 2010). The calibration of a CVD risk prediction model developed in the development cohort was tested in the validation cohort. The calibration was also assessed after modelling the secular trend. Finally, the presence of the secular trend was evaluated under a marginal structural model framework, where the effect of statin treatment during follow up is adjusted for. Results Substantial over prediction of risks in the validation cohort was found when not modelling the secular trend. This miscalibration could be minimised if one was to explicitly model the secular trend. The reduction in risk in the validation cohort when introducing the secular trend was 35.68 and 33.24% in the female and male cohorts respectively. Under the marginal structural model framework, the reductions were 33.31 and 32.67% respectively, indicating increasing statin use during follow up is not the only the cause of the secular trend. Conclusions Inclusion of the secular trend into the model substantially changed the CVD risk predictions. Models that are being used in clinical practice in the UK do not model secular trend and may thus overestimate the risks, possibly leading to patients being treated unnecessarily. Wider discussion around the modelling of secular trends in a risk prediction framework is needed.

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An assessment of the potential miscalibration of cardiovascular disease risk predictions caused by a secular trend in cardiovascular disease in England

10.21203/rs.3.rs-61533/v2 ◽

2020 ◽

Author(s):

Alexander Pate ◽

Tjeerd van Staa ◽

Richard Emsley

Keyword(s):

Cardiovascular Disease ◽

Risk Prediction ◽

Structural Model ◽

Validation Cohort ◽

Secular Trend ◽

Marginal Structural Model ◽

Cvd Risk ◽

Model Framework ◽

Statin Use

Abstract Background: A downwards secular trend in the incidence of cardiovascular disease (CVD) in England was identified through previous work and the literature. Risk prediction models for primary prevention of CVD do not model this secular trend, this could result in over prediction of risk for individuals in the present day. We evaluate the effects of modelling this secular trend, and also assess whether it is driven by an increase in statin use during follow up. Methods: We derived a cohort of patients (1998 – 2015) eligible for cardiovascular risk prediction from the Clinical Practice Research Datalink with linked hospitalisation and mortality records (N = 3,855,660). Patients were split into development and validation cohort based on their cohort entry date (before/after 2010). The calibration of a CVD risk prediction model developed in the development cohort was tested in the validation cohort. The calibration was also assessed after modelling the secular trend. Finally, the presence of the secular trend was evaluated under a marginal structural model framework, where the effect of statin treatment during follow up is adjusted for. Results: Substantial over prediction of risks in the validation cohort was found when not modelling the secular trend. This miscalibration could be minimised if one was to explicitly model the secular trend. The reduction in risk in the validation cohort when introducing the secular trend was 35.68% and 33.24% in the female and male cohorts respectively. Under the marginal structural model framework, the reductions were 33.31% and 32.67% respectively, indicating increasing statin use during follow up is not the only the cause of the secular trend. Conclusions: Inclusion of the secular trend into the model substantially changed the CVD risk predictions. Models that are being used in clinical practice in the UK do not model secular trend and may thus overestimate the risks, possibly leading to patients being treated unnecessarily. Wider discussion around the modelling of secular trends in a risk prediction framework is needed.

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An assessment of the potential miscalibration of cardiovascular disease risk predictions caused by a secular trend in cardiovascular disease in England

10.21203/rs.3.rs-61533/v1 ◽

2020 ◽

Author(s):

Alexander Pate ◽

Tjeerd van Staa ◽

Richard Emsley

Keyword(s):

Cardiovascular Disease ◽

Risk Prediction ◽

Structural Model ◽

Validation Cohort ◽

Secular Trend ◽

Marginal Structural Model ◽

Cvd Risk ◽

Model Framework ◽

Statin Use

Abstract Background A downwards secular trend in the incidence of cardiovascular disease (CVD) in England was identified through previous work and the literature. Risk prediction models for primary prevention of CVD do not model this secular trend, this could result in over prediction of risk for individuals in the present day. We evaluate the effects of modelling this secular trend, and also assess whether it is driven by an increase in statin use during follow up. Methods We derived a cohort of patients (1998–2015) eligible for cardiovascular risk prediction from the Clinical Practice Research Datalink with linked hospitalisation and mortality records (N = 3,855,660). Patients were split into development and validation cohort based on their cohort entry date (before/after 2010). The calibration of a CVD risk prediction model developed in the development cohort was tested in the validation cohort. The calibration was also assessed after modelling the secular trend. Finally, the presence of the secular trend was evaluated under a marginal structural model framework, where the effect of statin treatment during follow up is adjusted for. Results Substantial over prediction of risks in the validation cohort was found when not modelling the secular trend. This miscalibration could be minimised if one was to explicitly model the secular trend. The secular trend was still present under the marginal structural model framework, indicating increasing statin use during follow up is not the cause. Conclusions Inclusion of the secular trend into the model substantially changed the CVD risk predictions. Models that are being used in clinical practice in the UK do not model secular trend and may thus overestimate the risks, possibly leading to patients being treated unnecessarily.

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Abstract 36: The Role of Sleep as a Cardiovascular Health Metric: Does It Improve Cardiovascular Disease Risk Prediction? Results From The Multi-Ethnic Study of Atherosclerosis

Circulation ◽

10.1161/circ.141.suppl_1.36 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Cited By ~ 1

Author(s):

Nour Makarem ◽

Cecilia Castro-Diehl ◽

Marie-Pierre St-Onge ◽

Susan Redline ◽

Steven Shea ◽

...

Keyword(s):

Cardiovascular Disease ◽

Sleep Duration ◽

Risk Prediction ◽

Cardiovascular Health ◽

Cvd Risk ◽

Sleep Study ◽

Lower Odds ◽

Wrist Actigraphy ◽

Incident Cases

Background: The AHA Life’s Simple 7 (LS7) is a measure of cardiovascular health (CVH). Sufficient and healthy sleep has been linked to higher LS7 scores and lower cardiovascular disease (CVD) risk, but sleep has not been included as a CVH metric. Hypothesis: A CVH score that includes the LS7 plus sleep metrics would be more strongly associated with CVD outcomes than the LS7 score. Methods: Participants were n=1920 diverse adults (mean age: 69.5 y) in the MESA Sleep Study who completed 7 days of wrist actigraphy, overnight in-home polysomnography, and sleep questionnaires. Logistic regression and Cox proportional hazards models were used to compare the LS7 score and 4 new CVH scores that incorporate aspects of sleep in relation to CVD prevalence and incidence (Table). There were 95 prevalent CVD events at the Sleep Exam and 93 incident cases during a mean follow up of 4.4y. Results: The mean LS7 score was 7.3, and the means of the alternate CVH scores ranged from 7.4 to 7.8. Overall, 63% of participants slept <7h, 10% had sleep efficiency <85%, 14% and 36% reported excess daytime sleepiness and insomnia, respectively, 47% had obstructive sleep apnea, and 39% and 25% had high night-to-night variability in sleep duration and sleep onset timing. The LS7 score was not significantly associated with CVD prevalence or incidence (Table). Those in the highest vs. lowest tertile of CVH score 1, that included sleep duration, and CVH score 2, that included sleep characteristics linked to CVD in the literature, had lower odds of prevalent CVD. Those in the highest vs. lowest tertile of CVH scores 3 and 4, which included sleep characteristics linked to cardiovascular risk in MESA, had lower odds of prevalent CVD and lower risk of developing CVD. Conclusions: CVH scores that include sleep were more strongly associated with CVD prevalence and incidence than the traditional LS7 score. The incorporation of sleep as a metric of CVH, akin to other health behaviors, may improve CVD risk prediction. Findings warrant confirmation in larger samples and over longer follow-up.

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Nomogram to predict risk of incident chronic kidney disease in high-risk population of cardiovascular disease in China: community-based cohort study

BMJ Open ◽

10.1136/bmjopen-2020-047774 ◽

2021 ◽

Vol 11 (11) ◽

pp. e047774

Author(s):

Qiuxia Zhang ◽

Jingyi Zhang ◽

Li Lei ◽

Hongbin Liang ◽

Yun Li ◽

...

Keyword(s):

Cardiovascular Disease ◽

Chronic Kidney Disease ◽

Cohort Study ◽

Kidney Disease ◽

Cox Regression ◽

Validation Cohort ◽

High Risk Population ◽

Cvd Risk ◽

Incident Chronic Kidney Disease

AimsTo develop a nomogram for incident chronic kidney disease (CKD) risk evaluation among community residents with high cardiovascular disease (CVD) risk.MethodsIn this retrospective cohort study, 5730 non-CKD residents with high CVD risk participating the National Basic Public Health Service between January 2015 and December 2020 in Guangzhou were included. Endpoint was incident CKD defined as an estimated glomerular filtration rate (eGFR) less than 60 mL/min/1.73 m2 during the follow-up period. The entire cohorts were randomly (2:1) assigned to a development cohort and a validation cohort. Predictors of incident CKD were selected by multivariable Cox regression and stepwise approach. A nomogram based on these predictors was developed and evaluated with concordance index (C-index) and area under curve (AUC).ResultsDuring the median follow-up period of 4.22 years, the incidence of CKD was 19.09% (n=1094) in the entire cohort, 19.03% (727 patients) in the development cohort and 19.21% (367 patients) in the validation cohort. Age, body mass index, eGFR 60–89 mL/min/1.73 m2, diabetes and hypertension were selected as predictors. The nomogram demonstrated a good discriminative power with C-index of 0.778 and 0.785 in the development and validation cohort. The 3-year, 4-year and 5-year AUCs were 0.817, 0.814 and 0.834 in the development cohort, and 0.830, 0.847 and 0.839 in the validation cohort.ConclusionOur nomogram based on five readily available predictors is a reliable tool to identify high-CVD risk patients at risk of incident CKD. This prediction model may help improving the healthcare strategies in primary care.

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The gender-specific role of prediabetes on 10-year cardiovascular disease incidence: highlights from the ATTICA prospective (2002–2012) study

European Heart Journal ◽

10.1093/ehjci/ehaa946.3040 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

M Kouvari ◽

D.B Panagiotakos ◽

C Chrysohoou ◽

E.N Georgousopoulou ◽

C Pitsavos ◽

...

Keyword(s):

Cardiovascular Disease ◽

Risk Prediction ◽

Fasting Glucose ◽

Disease Incidence ◽

Fasting Blood Glucose ◽

Total Sample ◽

Funding Source ◽

Cvd Risk ◽

Diabetes Status

Abstract Background/Introduction Prediabetes in terms of impaired fasting glucose (IFG) or impaired glucose tolerance (IGT) are highly discussed for their aggravating effect on cardiac health and their potential inclusion in risk prediction to achieve earlier prevention. Purpose The aim of the present work was to evaluate the association between prediabetes and 10-year first fatal/non fatal cardiovascular disease (CVD) incidence in a sample without prevalent CVD, taking into account the stability of this condition or the transition to type II diabetes. Methods A prospective study was conducted during 2001–2012 studying n=1,514 males and n=1,528 females (aged >18 years old) free of CVD. According to American Diabetes Association Diagnosis, prediabetes in terms of IFG was defined as fasting glucose levels 100–125 mg/dl while type 2 diabetes as fasting blood glucose >125 mg/dl or the use of antidiabetic medication. Ten-year follow-up was performed in n=2,020 participants (n=317 CVD cases); the working sample here was n=1,485 (n=249 CVD cases) (without baseline diabetes and with available data on diabetes status at follow-up). Results Of the 1,485 participants, n=279 had IFG, at baseline. Ten-year CVD incidence was 19.3% in IFG subgroup and 12.3% in normoglycemic subgroup (p<0.001); the IFG-to-normoglycemic CVD incidence ratio in men was 1.22 while in women 1.60. Multi-adjusted analysis revealed that IFG was an independent predictor of CVD within the decade (Hazard ratio (HR)=1.39, 95% Confidence Interval (95% CI) (1.00, 1.95)). Significant interacting effect of gender on the examined association was revealed (p for interaction=0.001); in stratified analysis, IFG was independently associated with increased CVD risk only in women (HR=1.47, 95% CI (1.10, 2.68)). Within the decade, transition to diabetes status was observed in about one out of four participants with prediabetes (25.1%) while the respective rate in normoglycemic participants was 10% (n=191 diabetes cases, in total). Interestingly, sensitivity analysis revealed that when this category (with diabetes onset within the decade) was excluded from the analysis prediabetes retained its independent aggravating –even weaker– effect on 10-year CVD risk in total sample (HR=1.18, 95% CI (1.01, 1.91)) as well as in women (HR=1.25, 95% CI (1.03, 2.97)). Conclusion Here, it was suggested that IFG independently predicted long-term CVD onset, even without transition to a more serious cardiometabolic condition (i.e. diabetes) with more evident outcomes in case of women. Considering the increasing interest for early CVD risk prediction, prediabetes condition in terms of IFG may be a useful predictor towards this perspective. Funding Acknowledgement Type of funding source: Other. Main funding source(s): This work was supported by a research grant from Hellenic Atherosclerosis Society. The ATTICA study is supported by research grants from the Hellenic Cardiology Society [HCS2002] and the Hellenic Atherosclerosis Society [HAS2003].

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Abstract P346: Cohort Identification to Harness the Electronic Health Record for Cardiovascular Disease Prediction

Circulation ◽

10.1161/circ.141.suppl_1.p346 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Author(s):

Sheila M Manemann ◽

Jennifer St Sauver ◽

Janet E Olson ◽

Nicholas B Larson ◽

Paul Y Takahashi ◽

...

Keyword(s):

Blood Pressure ◽

Cardiovascular Disease ◽

Heart Rate ◽

Electronic Health Record ◽

Risk Prediction ◽

Health Record ◽

Next Generation ◽

Cvd Risk ◽

Electronic Health

Background: Current cardiovascular disease (CVD) risk scores are derived from research cohorts and are particularly inaccurate in women, older adults, and those with missing data. To overcome these limitations, we aimed to develop a cohort to capitalize on the depth and breadth of clinical data within electronic health record (EHR) systems in order to develop next-generation sex-specific risk prediction scores for incident CVD. Methods: All individuals 30 years of age or older residing in Olmsted County, Minnesota on 1/1/2006 were identified. We developed and validated algorithms to define a variety of risk factors, thus building a comprehensive risk profile for each patient. Outcomes including myocardial infarction (MI), percutaneous intervention (PCI), coronary artery bypass graft (CABG), and CVD death were ascertained through 9/30/2017. Results: We identified 73,069 individuals without CVD (Table). We retrieved a total of 14,962,762 lab results; 14,534,466 diagnoses; 17,062,601 services/procedures; 1,236,998 outpatient prescriptions; 1,079,065 heart rate measurements; and 1,320,115 blood pressure measurements. The median number of blood pressure and heart rate measurements ascertained per individuals were 11 and 9, respectively. The five most prevalent conditions were: hypertension, hyperlipidemia, arthritis, depression, and cardiac arrhythmias. During follow-up 1,455 MIs, 1,581 PCI, 652 CABG, and 2,161 CVD-related deaths occurred. Conclusions: We developed a cohort with comprehensive risk profiles and follow-up for each patient. Using sophisticated machine learning approaches, this electronic cohort will be utilized to develop next-generation sex-specific CVD risk prediction scores. These approaches will allow us to address several challenges with use of EHR data including the ability to 1) deal with missing values, 2) assess and utilize a large number of variables without over-fitting, 3) allow non-linear relationships, and 4) use time-to-event data.

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Prediction of Cardiovascular Disease Risk Accounting for Future Initiation of Statin Treatment

American Journal of Epidemiology ◽

10.1093/aje/kwab031 ◽

2021 ◽

Author(s):

Zhe Xu ◽

Matthew Arnold ◽

David Stevens ◽

Stephen Kaptoge ◽

Lisa Pennells ◽

...

Keyword(s):

Cardiovascular Disease ◽

High Risk ◽

Risk Prediction ◽

Prediction Models ◽

Predictive Performance ◽

Statin Treatment ◽

Clinical Practice Research Datalink ◽

Cvd Risk ◽

Risk Prediction Models

Abstract Cardiovascular disease (CVD) risk prediction models are used to identify high-risk individuals and guide statin-initiation. However, these models are usually derived from individuals who may initiate statins during follow-up. We present a simple approach to address statin-initiation to predict “statin-naïve” CVD risk. We analyzed primary care data (2004-2017) from the UK Clinical Practice Research Datalink for 1,678,727 individuals (40-85 years) without CVD or statin treatment history at study entry. We derived age- and sex-specific prediction models including conventional risk factors and a time-dependent effect of statin-initiation constrained to 25% risk reduction (from trial results). We compared predictive performance and measures of public-health impact (e.g., numbers-needed-to-screen to prevent one case) against models ignoring statin-initiation. During a median follow-up of 8.9 years, 103,163 individuals developed CVD. In models accounting for versus ignoring statin initiation, 10-year CVD risk predictions were slightly higher; predictive performance was moderately improved. However, few individuals were reclassified to a high-risk threshold, resulting in negligible improvements in numbers-needed-to-screen to prevent one case. In conclusion, incorporating statin effects from trial results into risk prediction models enables statin-naïve CVD risk estimation, provides moderate gains in predictive ability, but had a limited impact on treatment decision-making under current guidelines in this population.

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Association between Soy Food and Dietary Soy Isoflavone Intake and the Risk of Cardiovascular Disease in Women: A Prospective Cohort Study in Korea

Nutrients ◽

10.3390/nu13051407 ◽

2021 ◽

Vol 13 (5) ◽

pp. 1407

Author(s):

Jihyun Im ◽

Kyong Park

Keyword(s):

Cardiovascular Disease ◽

Postmenopausal Women ◽

Premenopausal Women ◽

Soy Isoflavones ◽

Korean Women ◽

Cvd Risk ◽

Soy Isoflavone ◽

Soy Foods ◽

Cardiovascular Disease In Women

The association between soy food and soy isoflavone intake and cardiovascular disease (CVD) risk is uncertain, especially in women. We aimed to investigate this association in Korean women. We analyzed data from the Korean Genome and Epidemiology Study, including 4713 Korean women aged 40–69 years with no CVD or cancer at baseline. Dietary information was obtained using a validated semi-quantitative food frequency questionnaire, and the incidence of CVD was assessed using biennial self-reported questionnaires on medical history. The mean follow-up time was 7.4 years, during which 82 premenopausal and 200 postmenopausal women reported CVD incidence. The highest tofu, total soy foods, and dietary soy isoflavone intake groups were significantly associated with a decreased CVD risk in premenopausal women (tofu: hazard ratio (HR) 0.39; 95% confidence interval (CI), 0.19–0.80; total soy food: HR 0.36; 95% CI, 0.18–0.70; dietary soy isoflavones: HR 0.44; 95% CI, 0.22–0.89), whereas no association was observed in postmenopausal women. Other soy foods showed no association with CVD incidence. Dietary soy isoflavones and total soy foods are associated with a decreased CVD risk in premenopausal women. Among soy foods, only tofu showed significant health benefits.

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Multi-trajectories of lipid indices with incident cardiovascular disease, heart failure, and all-cause mortality: 23 years follow-up of two US cohort studies

Journal of Translational Medicine ◽

10.1186/s12967-021-02966-4 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Fatemeh Koohi ◽

Davood Khalili ◽

Mohammad Ali Mansournia ◽

Farzad Hadaegh ◽

Hamid Soori

Keyword(s):

Heart Failure ◽

Cardiovascular Disease ◽

Cohort Studies ◽

Significant Risk ◽

Density Lipoprotein ◽

Lipid Levels ◽

Cvd Risk ◽

All Cause Mortality ◽

Over Time

Abstract Background Understanding the distinct patterns (trajectories) of variation in blood lipid levels before diagnosing cardiovascular disease (CVD) might carry important implications for improving disease prevention or treatment. Methods We investigated 14,373 participants (45.5% men) aged 45–84 from two large US prospective cohort studies with a median of 23 years follow-up. First, we jointly estimated developmental trajectories of lipid indices, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) concentrations using group-based multi-trajectory modeling. Then, the association of identified multi-trajectories with incident CVD, heart failure, and all-cause mortality were examined using Cox proportional hazard model. Results Seven distinct multi-trajectories were identified. The majority of participants (approximately 80%) exhibited decreasing LDL-C but rising TG levels and relatively stable HDL-C levels. Compared to the individuals with healthy and stable LDL-C, HDL-C, and TG levels, those in other groups were at significant risk of incident CVD after adjusting for other conventional risk factors. Individuals with the highest but decreasing LDL-C and borderline high and rising TG levels over time were at the highest risk than those in other groups with a 2.22-fold risk of CVD. Also, those with the highest and increased triglyceride levels over time, over optimal and decreasing LDL-C levels, and the lowest HDL-C profile had a nearly 1.84 times CVD risk. Even individuals in the multi-trajectory group with the highest HDL-C, optimal LDL-C, and optimal TG levels had a significant risk (HR, 1.45; 95% CI 1.02–2.08). Furthermore, only those with the highest HDL-C profile increased the risk of heart failure by 1.5-fold (95% CI 1.07–2.06). Conclusions The trajectories and risk of CVD identified in this study demonstrated that despite a decline in LDL-C over time, a significant amount of residual risk for CVD remains. These findings suggest the impact of the increasing trend of TG on CVD risk and emphasize the importance of assessing the lipid levels at each visit and undertaking potential interventions that lower triglyceride concentrations to reduce the residual risk of CVD, even among those with the optimal LDL-C level.

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Physical activity less than the recommended amount may prevent the onset of major biological risk factors for cardiovascular disease: a cohort study of 198 919 adults

British Journal of Sports Medicine ◽

10.1136/bjsports-2018-099740 ◽

2018 ◽

Vol 54 (4) ◽

pp. 238-244 ◽

Cited By ~ 1

Author(s):

David Martinez-Gomez ◽

Irene Esteban-Cornejo ◽

Esther Lopez-Garcia ◽

Esther García-Esquinas ◽

Kabir P Sadarangani ◽

...

Keyword(s):

Physical Activity ◽

Risk Factors ◽

Type 2 Diabetes ◽

Cardiovascular Disease ◽

Cvd Risk Factors ◽

Cvd Risk ◽

Highly Active ◽

Atherogenic Dyslipidaemia

ObjectivesWe examined the dose–response relationship between physical activity (PA) and incidence of cardiovascular disease (CVD) risk factors in adults in Taiwan.MethodsThis study included 1 98 919 participants, aged 18–97 years, free of CVD, cancer and diabetes at baseline (1997–2013), who were followed until 2016. At baseline, participants were classified into five PA levels: inactive’ (0 metabolic equivalent of task (MET)-h/week), ‘lower insufficiently active’ (0.1–3.75 MET-h/week), ‘upper insufficiently active’ (3.75–7.49 MET-h/week), ‘active’ (7.5–14.99 MET-h/week) and ‘highly active’ (≥15 MET-h/week]. CVD risk factors were assessed at baseline and at follow-up by physical examination and laboratory tests. Analyses were performed with Cox regression and adjusted for the main confounders.ResultsDuring a mean follow-up of 6.0±4.5 years (range 0.5–19 years), 20 447 individuals developed obesity, 19 619 hypertension, 21 592 hypercholesterolaemia, 14 164 atherogenic dyslipidaemia, 24 275 metabolic syndrome and 8548 type 2 diabetes. Compared with inactive participants, those in the upper insufficiently active (but not active) category had a lower risk of obesity (HR 0.92; 95% CI 0.88 to 0.95), atherogenic dyslipidaemia (0.96; 0.90 to 0.99), metabolic syndrome (0.95; 0.92 to 0.99) and type 2 diabetes (0.91; 0.86 to 0.97). Only highly active individuals showed a lower incidence of CVD risk factors than their upper insufficiently active counterparts.ConclusionCompared with being inactive, doing half the recommended amount of PA is associated with a lower incidence of several common biological CVD risk factors. Given these benefits, half the recommended amount of PA is an evidence based target for inactive adults.

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