Predicting the Effects of Blood Pressure–Lowering Treatment on Major Cardiovascular Events for Individual Patients With Type 2 Diabetes Mellitus

Personalizing medicine in Africa: current state, progress and challenges

Personalized medicine has been identified as a powerful tool for addressing the myriad of health issues facing different health systems globally. Although recent studies have expanded our understanding of how different factors such as genetics and the environment play significant roles in affecting the health of individuals, there are still several other issues affecting their translation into personalizing health interventions globally. Since African populations have demonstrated huge genetic diversity, there is a significant need to apply the concepts of personalized medicine to overcome various African-specific health challenges. Thus, we review the current state, progress, and challenges facing the adoption of personalized medicine in Africa with a view to providing insights to critical stakeholders on the right approach to deploy.

Cannabinoids in the management of behavioral, psychological, and motor symptoms of neurocognitive disorders: a mixed studies systematic review

Aim

We undertook this systematic review to determine the efficacy and safety of cannabis-based medicine as a treatment for behavioral, psychological, and motor symptoms associated with neurocognitive disorders.

Methods

We conducted a PRISMA-guided systematic review to identify studies using cannabis-based medicine to treat behavioral, psychological, and motor symptoms among individuals with Alzheimer's disease (AD) dementia, Parkinson’s disease (PD), and Huntington’s disease (HD). We considered English-language articles providing original data on three or more participants, regardless of design.

Findings

We identified 25 studies spanning 1991 to 2021 comprised of 14 controlled trials, 5 pilot studies, 5 observational studies, and 1 case series. In most cases, the cannabinoids tested were dronabinol, whole cannabis, and cannabidiol, and the diagnoses included AD (n = 11), PD (n = 11), and HD (n = 3). Primary outcomes were motor symptoms (e.g., dyskinesia), sleep disturbance, cognition, balance, body weight, and the occurrence of treatment-emergent adverse events.

Conclusions

A narrative summary of the findings from the limited number of studies in the area highlights an apparent association between cannabidiol-based products and relief from motor symptoms in HD and PD and an apparent association between synthetic cannabinoids and relief from behavioral and psychological symptoms of dementia across AD, PD, and HD. These preliminary conclusions could guide using plant-based versus synthetic cannabinoids as safe, alternative treatments for managing neuropsychiatric symptoms in neurocognitive vulnerable patient populations.

Time to benefit for stroke reduction after blood pressure treatment in older adults: A meta-analysis

Background

Hypertension treatment in older adults can decrease mortality, cardiovascular events, including heart failure, cognitive impairment, and stroke risk, but may also lead to harms such as syncope and falls. Guidelines recommend targeting preventive interventions with immediate harms and delayed benefits to patients whose life expectancy exceeds the intervention's time to benefit (TTB). Our objective was to estimate a meta‐analyzed TTB for stroke prevention after initiation of more intensive hypertension treatment in adults aged ≥65 years.

Methods

Studies were identified from two Cochrane systematic reviews and a search of MEDLINE and Google Scholar for subsequent publications until August 31, 2021. We abstracted data from randomized controlled trials comparing standard (untreated, placebo, or less intensive treatment) to more intensive treatment groups in older adults (mean age ≥ 65 years). We fit Weibull survival curves and used a random‐effects model to estimate the pooled annual absolute risk reduction (ARR) between control and intervention groups. We applied Markov chain Monte Carlo methods to determine the time to ARR thresholds (0.002, 0.005, and 0.01) for a first stroke.

Results

Nine trials (n = 38,779) were identified. The mean age ranged from 66 to 84 years and study follow‐up times ranged from 2.0 to 5.8 years. We determined that 1.7 (95%CI: 1.0–2.9) years were required to prevent 1 stroke for 200 persons (ARR = 0.005) receiving more intensive hypertensive treatment. Heterogeneity was found across studies, with those focusing on tighter systolic blood pressure control (SBP < 150 mmHg) showing longer TTB. For example, in the SPRINT study (baseline SBP = 140 mmHg, achieved SBP = 121 mmHg), the TTB to avoid 1 stroke for 200 patients treated was 5.9 years (95%CI: 2.2–13.0).

Conclusions

More intensive hypertension treatment in 200 older adults prevents 1 stroke after 1.7 years. Given the heterogeneity across studies, the TTB estimates from individual studies may be more relevant for clinical decision‐making than our summary estimate.

See related Editorial by Mark A. Supiano in this issue.

Pharmacological treatment of hypertension in people without prior cerebrovascular disease for the prevention of cognitive impairment and dementia

BACKGROUND

This is an update of a Cochrane Review first published in 2006 (McGuinness 2006), and previously updated in 2009 (McGuinness 2009). Hypertension is a risk factor for dementia. Observational studies suggest antihypertensive treatment is associated with lower incidences of cognitive impairment and dementia. There is already clear evidence to support the treatment of hypertension after stroke.

OBJECTIVES

To assess whether pharmacological treatment of hypertension can prevent cognitive impairment or dementia in people who have no history of cerebrovascular disease.

SEARCH METHODS

We searched the Specialised Register of the Cochrane Dementia and Cognitive Improvement Group, CENTRAL, MEDLINE, Embase, three other databases, as well as many trials registries and grey literature sources, most recently on 7 July 2020.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) in which pharmacological interventions to treat hypertension were given for at least 12 months. We excluded trials of pharmacological interventions to lower blood pressure in non-hypertensive participants. We also excluded trials conducted solely in people with stroke.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed trial quality and extracted data. We contacted study authors for additional information. We collected information regarding incidence of dementia, cognitive decline, change in blood pressure, adverse effects and quality of life. We assessed the certainty of evidence using GRADE.

MAIN RESULTS

We included 12 studies, totaling 30,412 participants, in this review. Eight studies compared active treatment with placebo. Of the four non-placebo-controlled studies, two compared intensive versus standard blood pressure reduction. The two final included studies compared different classes of antihypertensive drug. Study durations varied from one to five years. The combined result of four placebo-controlled trials that reported incident dementia indicated no evidence of a difference in the risk of dementia between the antihypertensive treatment group and the placebo group (236/7767 versus 259/7660, odds ratio (OR) 0.89, 95% confidence interval (CI) 0.72 to 1.09; very low certainty evidence, downgraded due to study limitations and indirectness). The combined results from five placebo-controlled trials that reported change in Mini-Mental State Examination (MMSE) may indicate a modest benefit from antihypertensive treatment (mean difference (MD) 0.20, 95% CI 0.10 to 0.29; very low certainty evidence, downgraded due to study limitations, indirectness and imprecision). The certainty of evidence for both cognitive outcomes was downgraded on the basis of study limitations and indirectness. Study durations were too short, overall, to expect a significant difference in dementia rates between groups. Dementia and cognitive decline were secondary outcomes for most studies. Additional sources of bias include: the use of antihypertensive medication by the placebo group in the placebo-controlled trials; failure to reach recruitment targets; and early termination of studies on safety grounds. Meta-analysis of the placebo-controlled trials reporting results found a mean change in systolic blood pressure of -9.25 mmHg (95% CI -9.73, -8.78) between treatment (n = 8973) and placebo (n = 8820) groups, and a mean change in diastolic blood pressure of -2.47 mmHg (95% CI -2.70, -2.24) between treatment (n = 7700) and placebo (n = 7509) groups (both low certainty evidence downgraded on the basis of study limitations and inconsistency). Three trials - SHEP 1991, LOMIR MCT IL 1996 and MRC 1996 - reported more withdrawals due to adverse events in active treatment groups than placebo groups. Participants on active treatment in Syst Eur 1998 were less likely to discontinue treatment due to side effects, and participants on active treatment in HYVET 2008 reported fewer 'serious adverse events' than in the placebo group. There was no evidence of a difference in withdrawals rates between groups in SCOPE 2003, and results were unclear for Perez Stable 2000 and Zhang 2018. Heterogeneity precluded meta-analysis. Five of the placebo-controlled trials provided quality of life (QOL) data. Heterogeneity again precluded meta-analysis. SHEP 1991, Syst Eur 1998 and HYVET 2008 reported no evidence of a difference in QOL measures between active treatment and placebo groups over time. The SCOPE 2003 sub-study (Degl'Innocenti 2004) showed a smaller drop in QOL measures in the active treatment compared to the placebo group. LOMIR MCT IL 1996 reported an improvement in a QOL measure at twelve months in one active treatment group and deterioration in another.

AUTHORS' CONCLUSIONS

High certainty randomised controlled trial evidence regarding the effect of hypertension treatment on dementia and cognitive decline does not yet exist. The studies included in this review provide low certainty evidence (downgraded primarily due to study limitations and indirectness) that pharmacological treatment of hypertension, in people without prior cerebrovascular disease, leads to less cognitive decline compared to controls. This difference is below the level considered clinically significant. The studies included in this review also provide very low certainty evidence that pharmacological treatment of hypertension, in people without prior cerebrovascular disease, prevents dementia.

Improving treatment decisions using personalized risk assessment from the International IgA Nephropathy Prediction Tool

Immunosuppression in IgA nephropathy (IgAN) should be reserved for patients at high-risk of disease progression, which KDIGO guidelines determine based solely on proteinuria 1g or more/day. To investigate if treatment decisions can be more accurately accomplished using individualized risk from the International IgAN Prediction Tool, we simulated allocation of a hypothetical immunosuppression therapy in an international cohort of adults with IgAN. Two decision rules for treatment were applied based on proteinuria of 1g or more/day or predicted risk from the Prediction Tool above a threshold probability. An appropriate decision was defined as immunosuppression allocated to patients experiencing the primary outcome (50% decline in eGFR or ESKD) and withheld otherwise. The net benefit and net reduction in treatment are the proportion of patients appropriately allocated to receive or withhold immunosuppression, adjusted for the harm from inappropriate decisions, calculated for all threshold probabilities from 0-100%. Of 3299 patients followed for 5.1 years, 522 (15.8%) experienced the primary outcome. Treatment allocation based solely on proteinuria of 1g or more/day had a negative net benefit (was harmful) because immunosuppression was increasingly allocated to patients without progressive disease. Compared to using proteinuria, treatment allocation using the Prediction Tool had a larger net benefit up to 23.4% (95% confidence interval 21.5-25.2%) and a larger net reduction in treatment up to 35.1% (32.3-37.8%). Thus, allocation of immunosuppression to high-risk patients with IgAN can be substantially improved using the Prediction Tool compared to using proteinuria.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP)

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of – usually interactive and online available – tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Predicting the Effect of Fenofibrate on Cardiovascular Risk for Individual Patients With Type 2 Diabetes

OBJECTIVE

In clinical trials, treatment with fenofibrate did not reduce the incidence of major cardiovascular events (MCVE) in patients with type 2 diabetes mellitus (T2DM). However, treatment effects reported by trials comprise patients who respond poorly and patients who respond well to fenofibrate. Our aim was to use statistical modeling to estimate the expected treatment effect of fenofibrate for individual patients with T2DM.

RESEARCH DESIGN AND METHODS

To estimate individual risk, the FIELD risk model, with 5-year MCVE as primary outcome, was externally validated in T2DM patients from ACCORD and the SMART observational cohort. Fenofibrate treatment effect was estimated in 17,142 T2DM patients from FIELD, ACCORD, and SMART. Individual treatment effect, expressed as absolute risk reduction (ARR), is the difference between treated and untreated MCVE risk. Results were stratified for patients with and without dyslipidemia (i.e., high triglycerides and low LDL cholesterol).

RESULTS

External validation of the FIELD risk model showed good calibration and moderate discrimination in ACCORD (C-statistic 0.67 [95% CI 0.65-0.69]) and SMART (C-statistic 0.66 [95% CI 0.63-0.69]). Median 5-year MCVE risk in all three studies combined was 6.7% (interquartile range [IQR] 4.0-11.7) in patients without (N = 13,224) and 9.4% (IQR 5.4-16.1%) in patients with (N = 3,918) dyslipidemia. The median ARR was 2.15% (IQR 1.23-3.68) in patients with dyslipidemia, corresponding with a number needed to treat (NNT) of 47, and 0.22% (IQR 0.13-0.38) in patients without dyslipidemia (NNT 455).

CONCLUSIONS

In individual patients with T2DM, there is a wide range of absolute treatment effect of fenofibrate, and overall the fenofibrate treatment effect was larger in patients with dyslipidemia. The method of individualized treatment effect prediction of fenofibrate on MCVE risk reduction in T2DM can be used to guide clinical decision making.

HAPT2D: high accuracy of prediction of T2D with a model combining basic and advanced data depending on availability

OBJECTIVE

Type 2 diabetes arises from the interaction of physiological and lifestyle risk factors. Our objective was to develop a model for predicting the risk of T2D, which could use various amounts of background information.

RESEARCH DESIGN AND METHODS

We trained a survival analysis model on 8483 people from three large Finnish and Spanish data sets, to predict the time until incident T2D. All studies included anthropometric data, fasting laboratory values, an oral glucose tolerance test (OGTT) and information on co-morbidities and lifestyle habits. The variables were grouped into three sets reflecting different degrees of information availability. Scenario 1 included background and anthropometric information; Scenario 2 added routine laboratory tests; Scenario 3 also added results from an OGTT. Predictive performance of these models was compared with FINDRISC and Framingham risk scores.

RESULTS

The three models predicted T2D risk with an average integrated area under the ROC curve equal to 0.83, 0.87 and 0.90, respectively, compared with 0.80 and 0.75 obtained using the FINDRISC and Framingham risk scores. The results were validated on two independent cohorts. Glucose values and particularly 2-h glucose during OGTT (2h-PG) had highest predictive value. Smoking, marital and professional status, waist circumference, blood pressure, age and gender were also predictive.

CONCLUSIONS

Our models provide an estimation of patient's risk over time and outweigh FINDRISC and Framingham traditional scores for prediction of T2D risk. Of note, the models developed in Scenarios 1 and 2, only exploited variables easily available at general patient visits.

LEADER 7: cardiovascular risk profiles of US and European participants in the LEADER diabetes trial differ

AIMS

To determine whether US and European participants in the Liraglutide Effect and Action in Diabetes: Evaluation of cardiovascular outcome Results (LEADER) trial differ regarding risk factors for cardiovascular mortality and morbidity.

METHODS

Baseline data, stratified for prior cardiovascular disease (CVD), were compared using multivariable logistic regression analysis to establish whether region is an independent determinant of achieved targets for glycated hemoglobin (HbA1c), blood pressure (BP), and low-density lipoprotein (LDL)-cholesterol.

RESULTS

Independent of CVD history, US participants were more often of non-White origin and had a longer history of type 2 diabetes, higher body weight, and higher baseline HbA1c. They had substantially lower systolic and diastolic BP, and a marginally lower LDL-cholesterol level. Fewer US participants were diagnosed with left ventricular dysfunction. In the largest group of patients, those with prior CVD and the highest cardiovascular risk, US participants were more often female, had a higher waist circumference, and had a decreased estimated glomerular filtration rate, but less frequently prior myocardial infarction or angina pectoris.

CONCLUSIONS

There were baseline differences between US and European participants. These differences may result from variation in regional targets for cardiovascular risk factor management, and should be considered in the analysis and reporting of the trial results. Clinical trial identifier: ClinicalTrials.gov, NCT01179048.

Endothelial Gata5 transcription factor regulates blood pressure

Despite its high prevalence and economic burden, the aetiology of human hypertension remains incompletely understood. Here we identify the transcription factor GATA5, as a new regulator of blood pressure (BP). GATA5 is expressed in microvascular endothelial cells and its genetic inactivation in mice (Gata5-null) leads to vascular endothelial dysfunction and hypertension. Endothelial-specific inactivation of Gata5 mimics the hypertensive phenotype of the Gata5-null mice, suggestive of an important role for GATA5 in endothelial homeostasis. Transcriptomic analysis of human microvascular endothelial cells with GATA5 knockdown reveals that GATA5 affects several genes and pathways critical for proper endothelial function, such as PKA and nitric oxide pathways. Consistent with a role in human hypertension, we report genetic association of variants at the GATA5 locus with hypertension traits in two large independent cohorts. Our results unveil an unsuspected link between GATA5 and a prominent human condition, and provide a new animal model for hypertension.

Unravelling the molecular basis of hypertension remains a major challenge. Here, the authors identify the transcription factor GATA5 as a novel regulator of blood pressure and potential genetic determinant of human hypertension and describe a unique mouse model for research of salt-sensitive hypertension.

Screening for cardiovascular disease risk and subsequent management in low and middle income countries: challenges and opportunities

Background

Cardiovascular disease (CVD), mainly heart attack and stroke, is the leading cause of premature mortality in low and middle income countries (LMICs). Identifying and managing individuals at high risk of CVD is an important strategy to prevent and control CVD, in addition to multisectoral population-based interventions to reduce CVD risk factors in the entire population.

Methods

We describe key public health considerations in identifying and managing individuals at high risk of CVD in LMICs.

Results

A main objective of any strategy to identify individuals at high CVD risk is to maximize the number of CVD events averted while minimizing the numbers of individuals needing treatment. Scores estimating the total risk of CVD (e.g. ten-year risk of fatal and non-fatal CVD) are available for LMICs, and are based on the main CVD risk factors (history of CVD, age, sex, tobacco use, blood pressure, blood cholesterol and diabetes status). Opportunistic screening of CVD risk factors enables identification of persons with high CVD risk, but this strategy can be widely applied in low resource settings only if cost effective interventions are used (e.g. the WHO Package of Essential NCD interventions for primary health care in low resource settings package) and if treatment (generally for years) can be sustained, including continued availability of affordable medications and funding mechanisms that allow people to purchase medications without impoverishing them (e.g. universal access to health care). This also emphasises the need to re-orient health systems in LMICs towards chronic diseases management.

Conclusion

The large burden of CVD in LMICs and the fact that persons with high CVD can be identified and managed along cost-effective interventions mean that health systems need to be structured in a way that encourages patient registration, opportunistic screening of CVD risk factors, efficient procedures for the management of chronic conditions (e.g. task sharing) and provision of affordable treatment for those with high CVD risk. The focus needs to be in primary care because that is where most of the population can access health care and because CVD programmes can be run effectively at this level.

Update on glycemic control for the treatment of diabetic kidney disease

Diabetic kidney disease (DKD) is a common, complex condition that has become a significant public health problem. The beneficial effects of intensive glycemic control in type 1 diabetes mellitus on development of DKD are proven; however, the evidence for nephroprotection in patients with type 2 diabetes is conflicting. Moreover, a strategy of intensive glycemic control increases the risk for adverse effects (hypoglycemic episodes) with no obvious impact on macrovascular events or mortality in recent large randomized controlled trials. The risk for hypoglycemia with intensive therapy is heightened in patients with significant renal dysfunction, due to decreased renal clearance of insulin. Establishing an ideal level of glycemic control in patients requires an individualized approach taking into account duration of diabetes and presence of coexisting comorbidities and pre-existing DKD. In this article, we review the available evidence from both observational studies and randomized controlled trials and provide suggestions about evaluating the potential benefits and harm from intensive glycemic control in patients. We also discuss how in the future, a personalized approach using biomarkers might help identify patients most likely to respond as well as those most susceptible to harm. We believe that using the optimal level of glycemic control in diabetic patients using a multi-pronged strategy will improve individual patient outcomes and decrease the overall burden of morbidity and mortality.

Prediction of absolute risk reduction of cardiovascular events with perindopril for individual patients with stable coronary artery disease - results from EUROPA

BACKGROUND

Angiotensin-converting-enzyme inhibition reduces the risk of cardiovascular events at a group level. Presumably, the absolute effect of treatment varies between individuals. We sought to develop multivariable prediction scores to estimate individual treatment effect of perindopril in patients with stable coronary artery disease (sCAD).

METHODS

In EUROPA trial participants, we estimated the individual patient 5-year absolute risk reduction (ARR) of major adverse cardiovascular events(MACE) by perindopril. Predictions were based on a new Coxproportional-hazards model with clinical characteristics and an external risk score in combination with the observed relative risk reduction. Second, a genetic profile modifying the relative efficacy of perindopril was added. The individual patient ARR was defined as the difference in MACE risk with and without treatment. The group level impact of selectively treating patients with the largest predicted treatment effect was evaluated using net benefit analysis.

RESULTS

The risk score combining clinical and genetic characteristics estimated the 5-year absolute treatment effect to be absent or adverse in 27% of patients. On the other hand, the risk score estimated a small 5-year ARR of ≤2% (NNT5≥50) in 20% of patients, a modest ARR of 2-4% (NNT5 25-50) in 26%, and a large ARR of ≥4% (NNT5≤25) in 28%. The external risk score yielded similar predictions. Selective prediction-based treatment resulted in higher net benefit compared to treat everyone at any treatment threshold.

CONCLUSION

A prediction score combining clinical characteristics and genetic information can quantify the ARR of MACE by perindopril for individual patients with sCAD and may be used to guide treatment decisions.

TRIAL REGISTRATION NUMBER

ISRCTN37166280.