Treatment drop-in in a contemporary cohort used to derive cardiovascular risk prediction equations.

BACKGROUND: No routinely recommended cardiovascular disease (CVD) risk prediction equations have adjusted for CVD preventive medications initiated during follow-up (treatment drop-in) in their derivation cohorts. This will lead to underestimation of risk when equations are applied in clinical practice if treatment drop-in is common. We aimed to quantify the treatment drop-in in a large contemporary national cohort to determine whether equations are likely to require adjustment. METHODS: Eight de-identified individual-level national health administrative datasets in Aotearoa New Zealand were linked to establish a cohort of almost all New Zealanders without CVD and aged 30-74 years in 2006. Individuals dispensing blood-pressure-lowering and/or lipid-lowering medications between 1 July 2006 and 31 December 2006 (baseline dispensing), and in each 6-month period during 12 years' follow-up to 31 December 2018 (follow-up dispensing), were identified. Person-years of treatment drop-in were determined. RESULTS: A total of 1 399 348 (80%) out of the 1 746 695 individuals in the cohort were not dispensed CVD medications at baseline. Blood-pressure-lowering and/or lipid-lowering treatment drop-in accounted for 14% of follow-up time in the group untreated at baseline and increased significantly with increasing predicted baseline 5-year CVD risk (12%, 31%, 34% and 37% in <5%, 5-9%, 10-14% and ≥15% risk groups, respectively) and with increasing age (8% in 30-44 year-olds to 30% in 60-74 year-olds). CONCLUSIONS: CVD preventive treatment drop-in accounted for approximately one-third of follow-up time among participants typically eligible for preventive treatment (≥5% 5-year predicted risk). Equations derived from cohorts with long-term follow-up that do not adjust for treatment drop-in effect will underestimate CVD risk in higher risk individuals and lead to undertreatment. Future CVD risk prediction studies need to address this potential flaw.

Development and validation of cardiovascular risk prediction equations in 76 000 people with known cardiovascular disease.

AIMS: Multiple health administrative databases can be individually linked in Aotearoa New Zealand, using encrypted identifiers. These databases were used to develop cardiovascular risk prediction equations for patients with known cardiovascular disease (CVD). METHODS AND RESULTS: Administrative health databases were linked to identify all people aged 18-84 years with known CVD, living in Auckland and Northland, Aotearoa New Zealand, on 1 January 2014. The cohort was followed until study outcome, death, or 5 years. The study outcome was death or hospitalization due to ischaemic heart disease, stroke, heart failure, or peripheral vascular disease. Sex-specific 5-year CVD risk prediction equations were developed using multivariable Fine and Gray models. A total of 43 862 men {median age: 67 years [interquartile range (IQR): 59-75]} and 32 724 women [median age: 70 years (IQR: 60-77)] had 14 252 and 9551 cardiovascular events, respectively. Equations were well calibrated with good discrimination. Increasing age and deprivation, recent cardiovascular hospitalization, Mori ethnicity, smoking history, heart failure, diabetes, chronic renal disease, atrial fibrillation, use of blood pressure lowering and anti-thrombotic drugs, haemoglobin A1c, total cholesterol/HDL cholesterol, and creatinine were statistically significant independent predictors of the study outcome. Fourteen per cent of men and 23% of women had predicted 5-year cardiovascular risk <15%, while 28 and 24% had ≥40% risk. CONCLUSION: Robust cardiovascular risk prediction equations were developed from linked routine health databases, a currently underutilized resource worldwide. The marked heterogeneity demonstrated in predicted risk suggests that preventive therapy in people with known CVD would be better informed by risk stratification beyond a one-size-fits-all high-risk categorization.

Using regionwide New Zealand health databases, methods of predicting hospitalization risk in patients with existing heart disease were developed. Using only data from health databases, it was possible to predict the risk accurately.Among patients with existing heart disease, the predicted risk varied markedly which could help improve preventive strategies.

Cardiovascular disease preventive medication dispensing for almost every New Zealander 65 years and over: a preventive treatment paradox?

OBJECTIVE: To describe the dispensing of cardiovascular disease (CVD) preventive medications among older New Zealanders with and without prior CVD or diabetes. METHODS: New Zealanders aged ≥65 years in 2013 were identified using anonymised linkage of national administrative health databases. Dispensing of blood pressure lowering (BPL), lipid lowering (LL) or antithrombotic (AT) medications, was documented, stratified by age and by history of CVD, diabetes, or neither. RESULTS: Of the 593,549 people identified, 32% had prior CVD, 14% had diabetes (of whom half also had prior CVD) and 61% had neither diagnosis. For those with prior CVD, between 79-87% were dispensed BPL and 73-79% were dispensed AT medications, across all age groups. In contrast, LL dispensing was lower than either BPL or AT in every age group, falling from 75% at age 65-69 years to 43% at 85+ years. For people with diabetes, BPL and LL dispensing was similar to those with prior CVD, but AT dispensing was approximately 20% lower. Among people without prior CVD or diabetes, both BPL and AT dispensing increased with age (from 39% and 17% at age 65-69 years to 56% and 35% at 85+ years respectively), whereas LL dispensing was 26-31% across the 65-84 year age groups, falling to 17% at 85+ years. CONCLUSION: The much higher dispensing of BPL and AT compared to LL medications with increasing age suggests a preventive treatment paradox for older people, with the medications most likely to cause adverse effects being dispensed most often.

Association between gout and cardiovascular outcomes in adults with no history of cardiovascular disease: large data linkage study in New Zealand.

Objective: To examine the association of gout with cardiovascular outcomes using linked administrative health data in Aotearoa New Zealand. Design: Data linkage study. Setting: National registries of pharmaceutical dispensing, hospital admission, and deaths linked to the Auckland/Northland regional repository of laboratory results to create a regional health contact population as of 31 December 2011. Participants: 942 416 residents of the Auckland/Northland region, aged 20-79 years with no history of cardiovascular disease. Main outcome measures: Time to first fatal or non-fatal cardiovascular event, identified from national datasets on hospital admissions and mortality, between 1 January 2012 and 31 December 2016. Cardiovascular disease was broadly defined as comprising ischaemic heart disease, ischaemic or haemorrhagic stroke, transient ischaemic attack, peripheral vascular disease, and heart failure. Interventions: A history of gout identified from a discharge diagnosis of gout from a public hospital admission or previous dispensing of gout specific drug treatments. The cohort was then linked to national hospital admissions and deaths through to 31 December 2016 (ie, 5 years' follow-up). Multivariable Cox proportional hazard models were constructed to assess the associations between gout, other risk factors, and cardiovascular outcomes. Results: Of 942 416 people included in the study, 31 907 (3.4%) had gout (6261 women and 25 646 men). After adjustment for multiple risk factors for cardiovascular disease, gout was associated with increased cardiovascular events (adjusted hazard ratio 1.34 (95% confidence interval 1.23 to 1.45) in women; 1.18 (1.12 to 1.24) in men). For men with gout, there was an increased risk of cardiovascular disease in those who were not dispensed regular allopurinol (1.15 (1.05 to 1.25)) and those with a serum urate above the treatment target of 0.36 mmol/L (1.16 (1.04 to 1.30)). Risk of cardiovascular events was lower for men with gout who were not dispensed colchicine compared with those who were (0.84 (0.77 to 0.92)). These findings were not observed in women. Conclusion: These results indicate that gout is associated with an increased risk of cardiovascular events. In men with gout without history of cardiovascular disease, the cardiovascular risk was lower in those regularly dispensed allopurinol and those with serum urate levels at the recommended treatment target. By contrast, colchicine dispensing was associated with an increased risk of cardiovascular events in men with gout without a cardiovascular history. The potential causal mechanisms of these associations require further exploration, including casual inference modelling in future studies.

Cardiovascular preventive pharmacotherapy stratified by predicted cardiovascular risk: a national data linkage study.

AIMS: Cardiovascular disease (CVD) risk management guided by predicted CVD risk is widely recommended internationally. This is the first study to examine CVD preventive pharmacotherapy in a whole-of-country primary prevention population, stratified by CVD risk. METHODS AND RESULTS: Anonymized individual-level linkage of New Zealand administrative health and non-health data identified 2 250 201 individuals without atherosclerotic CVD, alive, and aged 30-74 years on 31 March 2013. We identified individuals with ≥1 dispensing by community pharmacies of blood pressure lowering (BPL) and/or lipid-lowering (LL) medications at baseline (1 October 2012-31 March 2013) and in 6-month periods between 1 April 2013 and 31 March 2016. Individuals were stratified using 5-year CVD risk equations specifically developed for application in administrative datasets. One-quarter of individuals had ≥5% 5-year risk (the current New Zealand guideline threshold for discussing preventive medications) and 5% met the ≥15% risk threshold for recommended dual therapy. By study end, dual therapy was dispensed to 2%, 18%, 34%, and 49% of individuals with <5%, 5-9%, 10-14%, and ≥15% 5-year risk, respectively. Among those dispensed baseline dual therapy, 83-89% across risk strata were still treated after 3 years. Dual therapy initiation during follow-up occurred among only 13% of high-risk individuals untreated at baseline. People without diabetes and those aged ≥65 years were more likely to remain untreated. CONCLUSION: Cardiovascular disease primary preventive pharmacotherapy was strongly associated with predicted CVD risk and, once commenced, was generally continued. However, only half of high-risk individuals received recommended dual therapy and treatment initiation was modest. Individually linked administrative datasets can identify clinically relevant quality improvement opportunities for entire populations.

Are competing-risk models superior to standard Cox models for predicting cardiovascular risk in older adults? Analysis of a whole-of-country primary prevention cohort aged ≥65 years.

BACKGROUND: Both cardiovascular disease (CVD) risk and deaths from non-CVD causes, which may preclude a CVD event, increase with age. We evaluated whether accounting for the competing risk of non-CVD death improves the performance of CVD risk-prediction equations in older adults. METHODS: All New Zealanders aged ≥65 years in 2012 without a prior CVD hospitalization were identified by anonymized linkage of eight routinely collected national health data sets. Sex-specific equations estimating the 5-year risk of a fatal or non-fatal CVD event were constructed using standard Cox and Fine-Gray (competing-risk) approaches. The pre-specified predictors were: age, ethnicity, deprivation level, diabetes, atrial fibrillation and baseline preventive pharmacotherapy. Model performance was evaluated by assessing calibration and discrimination in the overall cohort and in ethnic and age-specific subgroups. RESULTS: Among 360 443 people aged ≥65 years with 1 615 412 person-years of follow-up, 14.6% of men and 12.1% of women had a first CVD event, whereas 8.5% of men and 7.6% of women died from a non-CVD cause. Standard Cox models overestimated the mean predicted the 5-year CVD risk by ∼1% overall and by 5-6% in the highest risk deciles. The mean predicted CVD risk from the Fine-Gray models approximated the observed risk overall, although slight underestimation occurred in some subgroups. Discrimination was similar for both models. CONCLUSIONS: In a whole-of-country primary prevention cohort aged ≥65 years, standard Cox models overestimated the 5-year CVD risk whereas the Fine-Gray models were generally better calibrated. New CVD risk equations that take competing risks into account should be considered for older people.

Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach.

BACKGROUND: Machine learning-based risk prediction models may outperform traditional statistical models in large datasets with many variables, by identifying both novel predictors and the complex interactions between them. This study compared deep learning extensions of survival analysis models with Cox proportional hazards models for predicting cardiovascular disease (CVD) risk in national health administrative datasets. METHODS: Using individual person linkage of administrative datasets, we constructed a cohort of all New Zealanders aged 30-74 who interacted with public health services during 2012. After excluding people with prior CVD, we developed sex-specific deep learning and Cox proportional hazards models to estimate the risk of CVD events within 5 years. Models were compared based on the proportion of explained variance, model calibration and discrimination, and hazard ratios for predictor variables. RESULTS: First CVD events occurred in 61 927 of 2 164 872 people. Within the reference group, the largest hazard ratios estimated by the deep learning models were for tobacco use in women (2.04, 95% CI: 1.99, 2.10) and chronic obstructive pulmonary disease with acute lower respiratory infection in men (1.56, 95% CI: 1.50, 1.62). Other identified predictors (e.g. hypertension, chest pain, diabetes) aligned with current knowledge about CVD risk factors. Deep learning outperformed Cox proportional hazards models on the basis of proportion of explained variance (R2: 0.468 vs 0.425 in women and 0.383 vs 0.348 in men), calibration and discrimination (all P <0.0001). CONCLUSIONS: Deep learning extensions of survival analysis models can be applied to large health administrative datasets to derive interpretable CVD risk prediction equations that are more accurate than traditional Cox proportional hazards models.

Cardiovascular risk prediction in type 2 diabetes before and after widespread screening: a derivation and validation study.

BACKGROUND: Until recently, most patients with diabetes worldwide have been diagnosed when symptomatic and have high cardiovascular risk, meaning most should be prescribed cardiovascular preventive medications. However, in New Zealand, a world-first national programme led to approximately 90% of eligible adults being screened for diabetes by 2016, up from 50% in 2012, identifying many asymptomatic patients with recent-onset diabetes. We hypothesised that cardiovascular risk prediction equations derived before widespread screening would now significantly overestimate risk in screen-detected patients. METHODS: New Zealanders aged 30-74 years with type 2 diabetes and without known cardiovascular disease, heart failure, or substantial renal impairment were identified from the 400 000-person PREDICT primary care cohort study between Oct 27, 2004, and Dec 30, 2016, covering the period before and after widespread screening. Sex-specific equations estimating 5-year risk of cardiovascular disease were developed using Cox regression models, with 18 prespecified predictors, including diabetes-related and renal function measures. Equation performance was compared with an equivalent equation derived in the New Zealand Diabetes Cohort Study (NZDCS), which recruited between 2000 and 2006, before widespread screening. FINDINGS: 46 652 participants were included in the PREDICT-1° Diabetes subcohort, of whom 4114 experienced first cardiovascular events during follow-up (median 5·2 years, IQR 3·3-7·4). 14 829 (31·8%) were not taking oral hypoglycaemic medications or insulin at baseline. Median 5-year cardiovascular risk estimated by the new equations was 4·0% (IQR 2·3-6·8) in women and 7·1% (4·5-11·2) in men. The older NZDCS equation overestimated median cardiovascular risk by three times in women (median 14·2% [9·7-20·0]) and two times in men (17·1% [4·5-20·0]). Model and discrimination performance measures for PREDICT-1° Diabetse equations were also significantly better than for the NZDCS equation (eg, for women: R2=32% [95% CI 29-34], Harrell's C=0·73 [0·72-0·74], Royston's D=1·410 [1·330-1·490] vs R2=24% [21-26], C=0·69 [0·67-0·70], and D=1·147 [1·107-1·187]). INTERPRETATION: International treatment guidelines still consider most people with diabetes to be at high cardiovascular risk; however, we show that recent widespread diabetes screening has radically changed the cardiovascular risk profile of people with diabetes in New Zealand. Many of these patients have normal renal function, are not dispensed glucose-lowering medications, and have low cardiovascular risk. These findings have clear international implications as increased diabetes screening is inevitable due to increasing obesity, simpler screening tests, and the introduction of new-generation glucose-lowering medications that prevent cardiovascular events. Cardiovascular risk prediction equations derived from contemporary diabetes populations, with multiple diabetes-related and renal function predictors, will be required to better differentiate between low-risk and high-risk patients in this increasingly heterogeneous population and to inform appropriate non-pharmacological management and cost-effective targeting of expensive new medications. FUNDING: Health Research Council of New Zealand, Heart Foundation of New Zealand, and Healthier Lives National Science Challenge.

Risk of major bleeding by ethnicity and socioeconomic deprivation among 488,107 people in primary care: a cohort study.

BACKGROUND: Antithrombotic medications (antiplatelets and anticoagulants) reduce the risk of cardiovascular disease (CVD), but with the disadvantage of increasing bleeding risk. Ethnicity and socioeconomic deprivation are independent predictors of major bleeds among patients without CVD, but it is unclear whether they are also predictors of major bleeds among patients with CVD or atrial fibrillation (AF) after adjustment for clinical variables. METHODS: Prospective cohort study of 488,107 people in New Zealand Primary Care (including 64,420 Maori, the indigenous people of New Zealand) aged 30-79 years who had their CVD risk assessed between 2007 and 2016. Participants were divided into three mutually exclusive subgroups: (1) AF with or without CVD (n = 15,212), (2) CVD and no AF (n = 43,790), (3) no CVD or AF (n = 429,105). Adjusted hazards ratios (adjHRs) were estimated from Cox proportional hazards models predicting major bleeding risk for each of the three subgroups to determine whether ethnicity and socioeconomic deprivation are independent predictors of major bleeds in different cardiovascular risk groups. RESULTS: In all three subgroups (AF, CVD, no CVD/AF), Maori (adjHR 1.63 [1.39-1.91], 1.24 [1.09-1.42], 1.57 [95% CI 1.45-1.70], respectively), Pacific people (adjHR 1.90 [1.58-2.28], 1.30 [1.12-1.51], 1.62 [95% CI 1.49-1.75], respectively) and Chinese people (adjHR 1.53 [1.08-2.16], 1.15 [0.90-1.47], 1.13 [95% CI 1.01-1.26], respectively) were at increased risk of a major bleed compared to Europeans, although for Chinese people the effect did not reach statistical significance in the CVD subgroup. Compared to Europeans, Maori and Pacific peoples were generally at increased risk of all bleed types (gastrointestinal, intracranial and other bleeds). An increased risk of intracranial bleeds was observed among Chinese and Other Asian people and, in the CVD and no CVD/AF subgroups, among Indian people. Increasing socioeconomic deprivation was also associated with increased risk of a major bleed in all three subgroups (adjHR 1.07 [1.02-1.12], 1.07 [1.03-1.10], 1.10 [95% CI 1.08-1.12], respectively, for each increase in socioeconomic deprivation quintile). CONCLUSION: Ethnicity and socioeconomic status should be considered in bleeding risk assessments to guide the use of antithrombotic medication for the management of AF and CVD.

Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study.

Aims: The aim of this study was to derive and validate a risk prediction model with nationwide coverage to predict the individual and population-level risk of cardiovascular disease (CVD). Methods and results: All 2.98 million Danish residents aged 30-85 years free of CVD were included on 1 January 2014 and followed through 31 December 2018 using nationwide administrative healthcare registries. Model predictors and outcome were pre-specified. Predictors were age, sex, education, use of antithrombotic, blood pressure-lowering, glucose-lowering, or lipid-lowering drugs, and a smoking proxy of smoking-cessation drug use or chronic obstructive pulmonary disease. Outcome was 5-year risk of first CVD event, a combination of ischaemic heart disease, heart failure, peripheral artery disease, stroke, or cardiovascular death. Predictions were computed using cause-specific Cox regression models. The final model fitted in the full data was internally-externally validated in each Danish Region. The model was well-calibrated in all regions. Area under the receiver operating characteristic curve (AUC) and Brier scores ranged from 76.3% to 79.6% and 3.3 to 4.4. The model was superior to an age-sex benchmark model with differences in AUC and Brier scores ranging from 1.2% to 1.5% and -0.02 to -0.03. Average predicted risks in each Danish municipality ranged from 2.8% to 5.9%. Predicted risks for a 66-year old ranged from 2.6% to 25.3%. Personalized predicted risks across ages 30-85 were presented in an online calculator (https://hjerteforeningen.shinyapps.io/cvd-risk-manuscript/). Conclusion: A CVD risk prediction model based solely on nationwide administrative registry data provided accurate prediction of personal and population-level 5-year first CVD event risk in the Danish population. This may inform clinical and public health primary prevention efforts.

Ethnic differences in cardiovascular risk profiles among 475,241 adults in primary care in Aotearoa, New Zealand.

AIM: In Aotearoa, New Zealand, cardiovascular disease (CVD) burden is greatest among Indigenous Maori, Pacific and Indian people. The aim of this study was to describe CVD risk profiles by ethnicity. METHODS: We conducted a cross-sectional analysis of a cohort of people aged 35-74 years who had a CVD risk assessment in primary care between 2004 and 2016. Primary care data were supplemented with linked data from regional/national databases. Comparisons between ethnic groups were made using age-adjusted summaries of continuous or categorical data. RESULTS: 475,241 people (43% women) were included. Fourteen percent were Maori, 13% Pacific, 8% Indian, 10% Other Asian and 55% European. Maori and Pacific people had a much higher prevalence of smoking, obesity, heart failure, atrial fibrillation and prior CVD compared with other ethnic groups. Pacific and Indian peoples, and to a lesser extent Maori and Other Asian people, had markedly elevated diabetes prevalence compared with Europeans. Indian men had the highest prevalence of prior coronary heart disease. CONCLUSIONS: Maori and Pacific people experience the most significant inequities in exposure to CVD risk factors compared with other ethnic groups. Indians have a high prevalence of diabetes and coronary heart disease. Strong political commitment and cross-sectoral action to implement effective interventions are urgently needed.

Inequity in one-year mortality after first myocardial infarction in Maori and Pacific patients: how much is associated with differences in modifiable clinical risk factors? (ANZACS-QI 49).

AIMS: Ischaemic heart disease (IHD) mortality rates after myocardial infarction (MI) are higher in Maori and Pacific compared to European people. The reasons for these differences are complex and incompletely understood. Our aim was to use a contemporary real-world national cohort of patients presenting with their first MI to better understand the extent to which differences in the clinical presentation, cardiovascular (CVD) risk factors, comorbidity and in-hospital treatment explain the mortality outcomes for Maori and Pacific peoples. METHODS: New Zealand residents (≥20 years old) hospitalised with their first MI (2014-2017), and who underwent coronary angiography, were identified from the All New Zealand Acute Coronary Syndrome Quality Improvement (ANZACS-QI) registry. All-cause mortality up to one year after the index admission date was obtained by linkage to the national mortality database. RESULTS: There were 17,404 patients with a first ever MI. European/other comprised 76% of the population, Maori 11.5%, Pacific 5.1%, Indian 4.3% and Other Asian 2.9%. Over half (55%) of Maori, Pacific and Indian patients were admitted with their first MI before age 60 years, compared with 29% of European/other patients. Maori and Pacific patients had a higher burden of traditional and non-traditional cardiovascular risk factors, and despite being younger, were more likely to present with heart failure and, together with Indian peoples, advanced coronary disease at presentation with first MI. After adjustment for age and sex, Maori and Pacific, but not Indian or Other Asian patients had significantly higher all-cause mortality at one year compared with the European/other reference group (HR 2.55 (95% CI 2.12-3.07), HR 2.98 (95% CI 2.34-3.81) for Maori and Pacific respectively). When further adjusted for differences in clinical presentation, clinical history and cardiovascular risk factors, the excess mortality risk for Maori and Pacific patients was reduced substantially, but a differential persisted (HR 1.77 (95% CI 1.44-2.19), HR 1.42 (95% CI 1.07-1.83)) which was not further reduced by adjustment for differences in in-hospital management and discharge medications. CONCLUSION: In New Zealand patients after their first MI there is a three-fold variation in one-year mortality based on ethnicity. At least half of the inequity in outcomes for Maori, and three-quarters for Pacific people, is associated with differences in preventable or modifiable clinical factors present at, or prior to, presentation.

Performance of CVD risk equations for older patients assessed in general practice: a cohort study.

AIMS: To investigate how well the New Zealand PREDICT-CVD risk equations, derived in people aged 30-74 years and US Pooled Cohort Equations (PCEs) derived in people aged 40-79 years, perform for older people. METHODS: The PREDICT cohort study automatically recruits participants when clinicians use PREDICT software to conduct a CVD risk assessment. We identified patients aged 70 years and over, without prior CVD, renal disease or heart failure who had been risk assessed between 2004 and 2016. Equation performance was assessed in five-year age bands using calibration graphs and standard discrimination metrics. RESULTS: 40,161 patients (median 73 years; IQR 71-77) experienced 5,948 CVD events during 185,150 person-years follow-up. PREDICT-CVD equations were well calibrated in 70-74 year olds but underestimated events for women from 75 years and men from 80 years. Discrimination metrics were also poor for these age groups. Recalibrated PCEs overestimated CVD risk in both sexes and had poor discrimination from age 70 years for men and from age 75 years for women. CONCLUSIONS: While PREDICT-CVD equations performed better than PCEs, neither performed well. Multimorbidity and competing risks are likely to contribute to the poor performance and new CVD risk equations need to include these factors.

How do cardiovascular risk prediction equations developed among 30-74 year olds perform in older age groups? A validation study in 125 000 people aged 75-89 years.

BACKGROUND: Cardiovascular disease (CVD) risk prediction equations are being used to guide risk management among increasingly older individuals. We examined the performance of recent equations, derived from a 2006 cohort including almost all New Zealanders aged 30-74 years, among older people. METHODS: All New Zealanders aged 75-89 years in contact with state-funded health services in 2006 without prior CVD or heart failure and with complete predictor data were identified by anonymised individual-level linkage of eight national administrative health datasets. Baseline 5-year CVD risk was estimated using sex-specific New Zealand risk equations, and CVD hospitalisations or deaths occurring between 2007 and 2011 inclusive were ascertained. Performance was assessed with calibration plots and standard metrics. RESULTS: Among 124 358 New Zealanders aged 75-89 years old, 30 152 CVD events were recorded during follow-up. Sex-specific equations derived from 30-74 year olds slightly underestimated CVD risk among women and slightly overestimated risk among men aged 75-89 years. Discrimination metrics were poor in both sexes and the risk equations explained only 9.4% of the variation in time to CVD event among women and 6.0% for men. In the 5-year age bands, progressively worsening underprediction in women, overprediction in men and poorer performance metrics were observed with increasing age. CONCLUSION: Entire-population CVD risk equations developed among 30-74 year olds do not perform well among older people. Existing risk algorithms developed from primarily middle-aged or early-retirement cohorts should be used with caution in those aged ≥75 years until carefully validated in narrow age bands to avoid masking poorer performance in older age groups.

Personalized Prediction of Cardiovascular Benefits and Bleeding Harms From Aspirin for Primary Prevention: A Benefit-Harm Analysis.

Background: Whether the benefits of aspirin for the primary prevention of cardiovascular disease (CVD) outweigh its bleeding harms in some patients is unclear. Objective: To identify persons without CVD for whom aspirin would probably result in a net benefit. Design: Individualized benefit-harm analysis based on sex-specific risk scores and estimates of the proportional effect of aspirin on CVD and major bleeding from a 2019 meta-analysis. Setting: New Zealand primary care. Participants: 245 028 persons (43.6% women) aged 30 to 79 years without established CVD who had their CVD risk assessed between 2012 and 2016. Measurements: The net effect of aspirin was calculated for each participant by subtracting the number of CVD events likely to be prevented (CVD risk score × proportional effect of aspirin on CVD risk) from the number of major bleeds likely to be caused (major bleed risk score × proportional effect of aspirin on major bleeding risk) over 5 years. Results: 2.5% of women and 12.1% of men were likely to have a net benefit from aspirin treatment for 5 years if 1 CVD event was assumed to be equivalent in severity to 1 major bleed, increasing to 21.4% of women and 40.7% of men if 1 CVD event was assumed to be equivalent to 2 major bleeds. Net benefit subgroups had higher baseline CVD risk, higher levels of most established CVD risk factors, and lower levels of bleeding-specific risk factors than net harm subgroups. Limitations: Risk scores and effect estimates were uncertain. Effects of aspirin on cancer outcomes were not considered. Applicability to non-New Zealand populations was not assessed. Conclusion: For some persons without CVD, aspirin is likely to result in net benefit. Primary Funding Source: Health Research Council of New Zealand.

Relationship between estimated glomerular filtration rate and incident cardiovascular disease in an ethnically diverse primary care cohort.

AIM: To investigate eGFR as an independent risk factor for CVD in a New Zealand primary care cohort, stratified by disease status (prior CVD, diabetes or no CVD or diabetes). METHOD: The PREDICT-CVD open cohort study is a large, ethnically diverse, New Zealand primary care cohort, generated by using a web-based CVD risk assessment tool. Using encrypted identifiers, participant profiles were linked anonymously to a regional laboratory database (to determine renal function) and to national hospitalisation and mortality datasets. Analyses using a single baseline eGFR measurement were undertaken in three clinical sub-cohorts of participants: those with prior CVD (n=29,742), with diabetes (n=44,416) and with neither CVD nor diabetes (n=192,696). The association between baseline eGFR (by category ≥90, 60-89.9, 30-59.9, and <30ml/min/1.73m2) and incident CVD was analysed with Kaplan Meier plots and Cox regression models. RESULTS: After adjustment for traditional CVD risk factors, there was an inverse relationship between CVD risk and eGFR, up to an eGFR of 60ml/min/1.73m2 in all three clinical sub-cohorts, and up to an eGFR of 90ml/min/1.73m2 in the sub-cohort with CVD or diabetes. Compared to eGFR ≥90ml/min/1.73m2, the adjusted hazard ratios of a new CVD event for eGFR <30ml/min/1.73m2 in the CVD, diabetes and no CVD/no diabetes sub-cohorts were 2.29 (95% CI 2.00-2.61), 4.71 (3.92-5.67) and 2.78 (2.05-3.77), respectively. Compared to European/Other ethnic groups, Maori participants remained at greater adjusted risk of a new CVD event in all clinical sub-cohorts and Pacific people only in the no CVD/no diabetes sub-cohort, whereas Indian participants had a similar adjusted risk to European/Other, and Other Asian patients were consistently at lower adjusted risk. Sensitivity analyses for individuals with consecutive eGFR results (>90 days apart) yielded similar results. CONCLUSION: This study has confirmed that, in a large ethnically diverse primary care cohort, eGFR is a significant independent predictor of CVD risk, and the risk varies by ethnic group.

Predicting Bleeding Risk to Guide Aspirin Use for the Primary Prevention of Cardiovascular Disease: A Cohort Study.

Background: Many prognostic models for cardiovascular risk can be used to estimate aspirin's absolute benefits, but few bleeding risk models are available to estimate its likely harms. Objective: To develop prognostic bleeding risk models among persons in whom aspirin might be considered for the primary prevention of cardiovascular disease (CVD). Design: Prospective cohort study. Setting: New Zealand primary care. Participants: The study cohort comprised 385 191 persons aged 30 to 79 years whose CVD risk was assessed between 2007 and 2016. Those with indications for or contraindications to aspirin and those who were already receiving antiplatelet or anticoagulant therapy were excluded. Measurements: For each sex, Cox proportional hazards models were developed to predict major bleeding risk; participants were censored at the earliest of the date on which they first met an exclusion criterion, date of death, or study end date (30 June 2017). The main models included the following predictors: demographic characteristics (age, ethnicity, and socioeconomic deprivation), clinical measurements (systolic blood pressure and ratio of total-high-density lipoprotein cholesterol), family history of premature CVD, medical history (smoking, diabetes, bleeding, peptic ulcer disease, cancer, chronic liver disease, chronic pancreatitis, or alcohol-related conditions), and medication use (nonsteroidal anti-inflammatory agents, corticosteroids, and selective serotonin reuptake inhibitors). Results: During 1 619 846 person-years of follow-up, 4442 persons had major bleeding events (of which 313 [7%] were fatal). The main models predicted a median 5-year bleeding risk of 1.0% (interquartile range, 0.8% to 1.5%) in women and 1.1% (interquartile range, 0.7% to 1.6%) in men. Plots of predicted-against-observed event rates showed good calibration throughout the risk range. Limitation: Hemoglobin level, platelet count, and body mass index were excluded from the main models because of high numbers of missing values, and the models were not externally validated in non-New Zealand populations. Conclusion: Prognostic bleeding risk models were developed that can be used to estimate the absolute bleeding harms of aspirin among persons in whom aspirin is being considered for the primary prevention of CVD. Primary Funding Source: The Health Research Council of New Zealand.

Development and validation of alternative cardiovascular risk prediction equations for population health planning: a routine health data linkage study of 1.7 million New Zealanders.

Background: Cardiovascular disease (CVD) risk prediction equations are primarily used in clinical settings to inform individual risk management decisions. We sought to develop and validate alternative equations derived solely from linked routinely collected national health data that could be applied countrywide to inform population health planning. Methods: Individual-level linkage of eight administrative health datasets identified all New Zealand residents aged 30-74 years in contact with publicly funded health services during 2006 with no previous hospitalizations for CVD or heart failure, and with complete data on eight pre-specified predictors. The linked health datasets encompassed demographic characteristics, hospitalizations, outpatient visits, primary care enrolment, primary care reimbursement, community laboratory requests, community pharmaceutical dispensing and mortality. Sex-specific Cox models were developed to estimate the risk of CVD death or hospitalization within 5 years and included sex, age, ethnicity, level of deprivation, diabetes, previous hospitalization for atrial fibrillation and baseline preventive pharmacotherapy (blood-pressure-lowering, lipid-lowering and antiplatelet/anticoagulant medications) as predictors. Calibration and discrimination were assessed in the whole cohort, in 15-year age bands, in different ethnic groups, in quintiles of deprivation, according to baseline dispensing of pharmacotherapy, and in regional sub-populations. Results: First CVD events occurred in 62 031 of the 1 746 695 people during 8 526 024 person-years of follow-up (mean = 4.8 years). Median 5-year CVD risk was 1.1% in women and 2.6% in men. In both sexes, the risk equations were well calibrated throughout the risk range and had good risk discrimination in the national, regional and ethnic populations, within 15-year age bands, in deprivation quintiles and according to baseline medication dispensing. Conclusions: Robust policy-focused CVD risk equations can be developed solely from administrative health data to inform population health planning, and will complement CVD primary prevention at the individual level using clinical risk tools. Similar policy-focused equations could be replicated in countries and regions with linked administrative health datasets.

Performance of a Framingham cardiovascular risk model among Indians and Europeans in New Zealand and the role of body mass index and social deprivation.

Objectives: To evaluate a Framingham 5-year cardiovascular disease (CVD) risk score in Indians and Europeans in New Zealand, and determine whether body mass index (BMI) and socioeconomic deprivation were independent predictors of CVD risk. Methods: We included Indians and Europeans, aged 30-74 years without prior CVD undergoing risk assessment in New Zealand primary care during 2002-2015 (n=256 446). Risk profiles included standard Framingham predictors (age, sex, systolic blood pressure, total cholesterol/high-density lipoprotein ratio, smoking and diabetes) and were linked with national CVD hospitalisations and mortality datasets. Discrimination was measured by the area under the receiver operating characteristics curve (AUC) and calibration examined graphically. We used Cox regression to study the impact of BMI and deprivation on the risk of CVD with and without adjustment for the Framingham score. Results: During follow-up, 8105 and 1156 CVD events occurred in Europeans and Indians, respectively. Higher AUCs of 0.76 were found in Indian men (95% CI 0.74 to 0.78) and women (95% CI 0.73 to 0.78) compared with 0.74 (95% CI 0.73 to 0.74) in European men and 0.72 (95% CI 0.71 to 0.73) in European women. Framingham was best calibrated in Indian men, and overestimated risk in Indian women and in Europeans. BMI and deprivation were positively associated with CVD, also after adjustment for the Framingham risk score, although the BMI association was attenuated. Conclusions: The Framingham risk model performed reasonably well in Indian men, but overestimated risk in Indian women and in Europeans. BMI and socioeconomic deprivation could be useful predictors in addition to a Framingham score.