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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., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Developing simplified risk assessment model based on non-laboratory risk factors that could determine cardiovascular risk as accurately as laboratory-based one can be valuable, particularly in developing countries where there are limited resources., Objective: To develop a simplified non-laboratory cardiovascular disease risk assessment chart based on previously reported laboratory-based chart and evaluate internal and external validation, and recalibration of both risk models to assess the performance of risk scoring tools in other population., Methods: A 10-year non-laboratory-based risk prediction chart was developed for fatal and non-fatal CVD using Cox Proportional Hazard regression. Data from the Isfahan Cohort Study (ICS), a population-based study among 6504 adults aged ≥ 35 years, followed-up for at least ten years was used for the non-laboratory-based model derivation. Participants were followed up until the occurrence of CVD events. Tehran Lipid and Glucose Study (TLGS) data was used to evaluate the external validity of both non-laboratory and laboratory risk assessment models in other populations rather than one used in the model derivation., Results: The discrimination and calibration analysis of the non-laboratory model showed the following values of Harrell's C: 0.73 (95% CI 0.71-0.74), and Nam-D'Agostino χ 2 :11.01 (p = 0.27), respectively. The non-laboratory model was in agreement and classified high risk and low risk patients as accurately as the laboratory one. Both non-laboratory and laboratory risk prediction models showed good discrimination in the external validation, with Harrell's C of 0.77 (95% CI 0.75-0.78) and 0.78 (95% CI 0.76-0.79), respectively., Conclusions: Our simplified risk assessment model based on non-laboratory risk factors could determine cardiovascular risk as accurately as laboratory-based one. This approach can provide simple risk assessment tool where laboratory testing is unavailable, inconvenient, and costly., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2021 The Author(s).)

We used longitudinal information on area deprivation status to explore the relationship between residential-deprivation mobility and Cardiovascular Disease (CVD). Data from 2,418,397 individuals who were: enrolled in any Primary Health Organisation within New Zealand (NZ) during at least 1 of 34 calendar quarters between 1st January 2006 and 30th June 2014; aged between 30 and 84 years (inclusive) at the start of the study period; had no prior history of CVD; and had recorded address information were analysed. Including a novel trajectory analysis, our findings suggest that movers are healthier than stayers. The deprivation characteristics of the move have a larger impact on the relative risk of CVD for younger movers than for older movers. For older movers any kind of move is associated with a decreased risk of CVD., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Clinical practice guidelines have traditionally recommended blood pressure treatment based primarily on blood pressure thresholds. In contrast, using predicted cardiovascular risk has been advocated as a more effective strategy to guide treatment decisions for cardiovascular disease (CVD) prevention. We aimed to compare outcomes from a blood pressure-lowering treatment strategy based on predicted cardiovascular risk with one based on systolic blood pressure (SBP) level., Methods and Findings: We used individual participant data from the Blood Pressure Lowering Treatment Trialists' Collaboration (BPLTTC) from 1995 to 2013. Trials randomly assigned participants to either blood pressure-lowering drugs versus placebo or more intensive versus less intensive blood pressure-lowering regimens. We estimated 5-y risk of CVD events using a multivariable Weibull model previously developed in this dataset. We compared the two strategies at specific SBP thresholds and across the spectrum of risk and blood pressure levels studied in BPLTTC trials. The primary outcome was number of CVD events avoided per persons treated. We included data from 11 trials (47,872 participants). During a median of 4.0 y of follow-up, 3,566 participants (7.5%) experienced a major cardiovascular event. Areas under the curve comparing the two treatment strategies throughout the range of possible thresholds for CVD risk and SBP demonstrated that, on average, a greater number of CVD events would be avoided for a given number of persons treated with the CVD risk strategy compared with the SBP strategy (area under the curve 0.71 [95% confidence interval (CI) 0.70-0.72] for the CVD risk strategy versus 0.54 [95% CI 0.53-0.55] for the SBP strategy). Compared with treating everyone with SBP ≥ 150 mmHg, a CVD risk strategy would require treatment of 29% (95% CI 26%-31%) fewer persons to prevent the same number of events or would prevent 16% (95% CI 14%-18%) more events for the same number of persons treated. Compared with treating everyone with SBP ≥ 140 mmHg, a CVD risk strategy would require treatment of 3.8% (95% CI 12.5% fewer to 7.2% more) fewer persons to prevent the same number of events or would prevent 3.1% (95% CI 1.5%-5.0%) more events for the same number of persons treated, although the former estimate was not statistically significant. In subgroup analyses, the CVD risk strategy did not appear to be more beneficial than the SBP strategy in patients with diabetes mellitus or established CVD., Conclusions: A blood pressure-lowering treatment strategy based on predicted cardiovascular risk is more effective than one based on blood pressure levels alone across a range of thresholds. These results support using cardiovascular risk assessment to guide blood pressure treatment decision-making in moderate- to high-risk individuals, particularly for primary prevention.

Background: Most current clinical guidelines focus primarily on the management of individual cardiovascular risk factors, such as high blood pressure (BP), hypercholesterolemia, or diabetes. A more appropriate clinical approach to reducing cardiovascular disease risk would be based on a comprehensive evaluation of risk profile, and accurate stratification of global (absolute) risk in individual patients. We propose that global risk should be used as the main determinant of whom to treat, how to treat, and how much to treat., Methods: In this article we use a series of case studies to demonstrate the implications of replacing the traditional "single risk factor-based" approach to managing hypertension by one based on global risk assessment. In some situations patients with mildly elevated BP levels would not be recommended for antihypertensive drug treatment whereas others with lower BP would be treated, depending upon the entire risk profile., Conclusion: We propose to replace the single risk factor-based approach with the assessment of global cardiovascular risk, both in the clinical management of individual patients and in guidelines.

Aim: To compare the discriminative ability of a multivariate risk-prediction model with individual continuous cardiovascular risk factors in a free-living population., Methods: Standard cardiovascular risk factors were measured in 6354 participants (4638 men and 1716 women) aged 35 to 74 years with no history of cardiovascular disease either enrolled on Auckland general electoral rolls or employed by a New Zealand-wide multi-industry corporation, in 1992-3. The sensitivity and specificity of individual risk factors versus a five-year cardiovascular risk-prediction equation and the corresponding New Zealand risk charts in predicting hospitalisation and mortality from cardiovascular disease in the subsequent five-year period were estimated over a range of risk thresholds., Results: Discrimination between individuals who had or did not have subsequent cardiovascular events was poor for individual risk factors. Increasing age had significantly more discriminability than blood pressure or lipids and the Framingham Heart Study risk tool had better discriminability than any single risk factor., Conclusions: A Framingham risk equation and corresponding New Zealand risk charts discriminate between individuals who will or will not experience hospitalisation or death from cardiovascular events. Discriminability is only modest but it is better than that achieved using individual risk factors.

Aim: To establish the population-level predictive validity of the Framingham Heart Study risk equation used to derive cardiovascular disease risk-prediction charts for New Zealand management guidelines on raised blood pressure and dyslipidaemia., Methods: During 1992-3, standard cardiovascular risk factors were measured in a cohort of 6354 people (4638 men and 1716 women) aged 35-74 years with no history of cardiovascular disease, who were either enrolled on Auckland general electoral rolls or employed by a nationwide multi-industry corporation. Five-year cardiovascular event rates were predicted for the cohort using a Framingham risk equation and were compared with observed five-year cardiovascular event rates for hospitalisation and mortality., Results: Incident cardiovascular hospitalisations or death were reported for 411 cohort participants (325 men and 86 women) during five years of follow up. There was good agreement between observed and predicted five-year cardiovascular event rates in all five-year age/sex categories up to 69 years. The risk equation tended to underestimate risk slightly in men and overestimate risk slightly in women up to 69 years, while in 70- to 74-year-olds it was accurate for men. Its accuracy in older women is uncertain., Conclusion: A Framingham Heart Study risk equation used to estimate incident cardiovascular events in individuals without previous cardiovascular disease accurately predicts five-year risk of hospitalisation or death from a first cardiovascular event in New Zealand men aged 35-74 and women aged 35-69 years at the population level.