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

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].

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 ◽  
2020 ◽  
Vol 141 (Suppl_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.

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

2020 ◽  
Vol 20 (1) ◽  
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.

Abstract MP53: Associations of Dietary Patterns and Cardiovascular Disease Risk Do Not Differ by Diabetes Status

Circulation ◽  
2014 ◽  
Vol 129 (suppl_1) ◽  
Author(s):  
Keith E Pearson ◽  
Jenifer H Voeks ◽  
April P Carson ◽  
James S Shikany ◽  
Monika M Safford ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Racial Differences ◽  
Dietary Patterns ◽  
Dietary Pattern ◽  
Fasting Glucose ◽  
Inverse Association ◽  
Cvd Risk ◽  
Dietary Practices ◽  
Diabetes Status ◽  
Increased Risk

Introduction: Adults with diabetes have been shown to have differences in reported diet compared to adults without diabetes. While diet is associated with cardiovascular disease (CVD) risk, few studies have examined whether dietary patterns may differentially affect CVD risk in adults with and without diabetes. Objective: We examined whether the relationship between diet and CVD risk differed between adults with and without diabetes who were free of CVD at baseline in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Methods: REGARDS is a nation-wide, longitudinal study of 30, 239 black and white participants ages 45 and older. Previously, principal components analysis was utilized to derive dietary patterns for participants with usable Block98 food frequency questionnaire data (n=21,636). Diabetes was defined as self-reported medication use, fasting glucose ≥ 126 mg/dL, or non-fasting glucose ≥ 200 mg/dL. The final sample for this analysis included 2,701 participants with diabetes and 13,906 participants without diabetes. CVD events, including stroke and nonfatal or fatal myocardial infarction, were physician-adjudicated. Cox proportional hazards regression was used to assess the association of each dietary pattern (modeled in quintiles) with risk of CVD, stratified by diabetes status. Results: We observed 787 CVD events over an average follow up of 5.5 years. Greater adherence to the Southern dietary pattern (which loaded highly on fried foods, processed meats, and sugar-sweetened beverages) significantly increased risk of CVD in adults without diabetes (comparing Q5 to Q1: HR=1.54; 95% CI=1.16, 2.06) and the association trended similarly, though non-significant, in adults with diabetes (comparing Q5 to Q1: HR=1.32; 95% CI=0.76, 2.31). Adherence to the Plant-based pattern (which loaded heavily on fruits, vegetables, and legumes) showed a non-significant inverse association with CVD risk in both adults with diabetes (comparing Q5 to Q1: HR=0.77; 95% CI=0.49, 1.23) and adults without diabetes (comparing Q5 to Q1: HR=0.87; 95% CI=0.65, 1.17). After adjustment for age, race, gender, region, income, education, physical activity, smoking status, and total energy intake, there were no differences in the association of either dietary pattern and risk of CVD between adults with and without diabetes (p for interaction = 0.23 for Plant-based; p for interaction = 0.87 for Southern). Conclusions: While adults with and without diabetes may differ in reported dietary practices, our results suggest there are no differences in the associations of dietary patterns and CVD risk between the two groups - further demonstrating the importance of healthful dietary practices in the prevention of CVD regardless of diabetes status.

scholarly journals Tryptophan levels associate with incident cardiovascular disease in chronic kidney disease

2020 ◽  
Author(s):  
Vetalise C Konje ◽  
Thekkelnaycke M Rajendiran ◽  
Keith Bellovich ◽  
Crystal A Gadegbeku ◽  
Debbie S Gipson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Receiver Operating Curve ◽  
Cvd Risk ◽  
Diabetes Status ◽  
Ckd Stage ◽  
History Of

Abstract Background Non-traditional risk factors like inflammation and oxidative stress play an essential role in the increased cardiovascular disease (CVD) risk prevalent in chronic kidney disease (CKD). Tryptophan catabolism by the kynurenine pathway (KP) is linked to systemic inflammation and CVD in the general and dialysis population. However, the relationship of KP to incident CVD in the CKD population is unknown. Methods We measured tryptophan metabolites using targeted mass spectrometry in 92 patients with a history of CVD (old CVD); 46 patients with no history of CVD and new CVD during follow-up (no CVD); and 46 patients with no CVD history who developed CVD in the median follow-up period of 2 years (incident CVD). Results The three groups are well-matched in age, gender, race, diabetes status and CKD stage, and only differed in total cholesterol and proteinuria. Tryptophan and kynurenine levels significantly decreased in patients with ‘Incident CVD’ compared with the no CVD or old CVD groups (P = 5.2E–7; P = 0.003 respectively). Kynurenic acid, 3-hydroxykynurenine and kynurenine are all increased with worsening CKD stage (P &lt; 0.05). An increase in tryptophan levels at baseline was associated with 0.32-fold lower odds of incident CVD (P = 0.000014) compared with the no CVD group even after adjustment for classic CVD risk factors. Addition of tryptophan and kynurenine levels to the receiver operating curve constructed from discriminant analysis predicting incident CVD using baseline clinical variables increased the area under the curve from 0.76 to 0.82 (P = 0.04). Conclusions In summary, our study demonstrates that low tryptophan levels are associated with incident CVD in CKD.

scholarly journals Lipoprotein (a) and 10-year Cardiovascular Disease Incidence in Apparently Healthy Individuals: A Sex-based Sensitivity Analysis from ATTICA Cohort Study

Angiology ◽  
2019 ◽  
Vol 70 (9) ◽  
pp. 819-829 ◽  
Author(s):  
Matina Kouvari ◽  
Demosthenes B. Panagiotakos ◽  
Christina Chrysohoou ◽  
Ekavi N. Georgousopoulou ◽  
Mary Yannakoulia ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Disease Incidence ◽  
Density Lipoprotein ◽  
Patient Characteristics ◽  
Apolipoprotein A1 ◽  
Sensitivity Analyses ◽  
Cvd Risk ◽  
Lipoprotein A ◽  
Apparently Healthy

The association between lipoprotein (a) (Lp(a)) and 10-year first fatal/nonfatal cardiovascular disease (CVD) risk in apparently healthy men and women was evaluated. The ATTICA prospective study was conducted during 2001-2012 and included n = 1514 men and n = 1528 women (age >18 years) from the greater Athens area, Greece. Follow-up CVD assessment (2011-2012) was achieved in n = 2020 participants (n = 317 cases); baseline Lp(a) was measured in n = 1890 participants. The recommended threshold of 50 mg/dL was used to define abnormal Lp(a) status. Ten-year CVD-event rate was 14% and 24% in participants with Lp(a) <50 and Lp(a) ≥50 mg/dL, respectively. Multivariate analysis revealed that participants with Lp(a) ≥50 mg/dL versus Lp(a) <50 mg/dL had about 2 times higher CVD risk (hazard ratio (HR) = 2.18, 95% confidence interval (CI) 1.11, 4.28). The sex-based analysis revealed that the independent Lp(a) effect was retained only in men (HR = 2.00, 95% CI 1.19, 2.56); in women, significance was lost after adjusting for lipid markers. Sensitivity analyses revealed that Lp(a) increased CVD risk only in case of abnormal high-density lipoprotein cholesterol, apolipoprotein A1, and triglycerides as well as low adherence to Mediterranean diet. Certain patient characteristics may be relevant when considering Lp(a) as a therapeutic or risk-prediction target.

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

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.

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

Circulation ◽  
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.

Abstract 19269: Relations and Predictive Value of Post-load and Fasting Glucose for Incident Cardiovascular Disease and Mortality in Older Adults: the Cardiovascular Health Study

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Erika Brutsaert ◽  
Sanyog Shitole ◽  
Mary Lou Biggs ◽  
Kenneth Mukamal ◽  
Ian De Boer ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Older Adults ◽  
Old Age ◽  
Risk Prediction ◽  
Cardiovascular Health ◽  
Fasting Glucose ◽  
Community Dwelling ◽  
Health Study ◽  
Cardiovascular Health Study

Introduction: Elders have a high prevalence of post-load hyperglycemia, which may go undetected with standard screening. Post-load glucose has shown more robust associations with cardiovascular disease (CVD) and death than fasting glucose, but data in advanced old age are sparse. Whether post-load glucose improves risk prediction for CVD and death after accounting for fasting glucose has not been examined. Methods: Fasting and 2-hour post-load glucose were measured at baseline (1989) and follow-up (1996) visits in a prospective study of community-dwelling adults initially ≥65 years old (Cardiovascular Health Study). To evaluate if previously reported associations of fasting and post-load glucose with incident CVD from the baseline visit persist later in life, and apply to mortality, we focused on the 1996 visit (n=2394). To determine the incremental value of post-load glucose for risk prediction, we examined whether it could significantly reclassify baseline (1989) participants (≤75 years) into cholesterol treatment categories based on recent guidelines (n=2542). Results: Among participants in the 1996 visit (mean age 77), there were 543 incident CVD events and 1698 deaths during median follow-up of 11.2 years. In fully adjusted models, both fasting and 2-hour glucose were associated with CVD (HR per SD, 1.13 [1.03-1.25] and 1.17 [1.07-1.28], respectively) and mortality (HR per SD, 1.12 [1.07-1.18] and 1.14 [1.08-1.20]). After mutual adjustment, however, the associations for fasting glucose with either outcome were abolished, but those for post-load glucose remained unchanged. Among subjects ≤75 years old in 1989, there were 416 CVD events and 740 deaths at 10-year follow-up. Post-load glucose did not enhance reclassification using the 7.5% 10-year risk threshold, nor did it improve the C-statistic. Conclusion: In adults surviving to advanced old age, post-load glucose was associated with CVD and mortality independently of fasting glucose, but not vice versa, although there was no associated improvement in risk prediction. These findings affirm the robust association of post-load glucose with CVD and death late in life, but do not support the value of routine oral glucose tolerance testing for prediction of these outcomes in older adults.

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

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.

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

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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