- Email: [email protected]
Lifetime Risk of Cardiovascular Disease: The Next Generation in Risk Prediction
Canadian Journal of Cardiology 29 (2013) 147–150
Viewpoint
Lifetime Risk of Cardiovascular Disease: The Next Generation in Risk Prediction Caroline Bleakley, MB, BCh, BAO, MRCP(UK), Auleen Millar, MB, BCh, BAO, MRCP(UK), Mark Harbinson, MD, FRCP(UK), and Gary Eugene McVeigh, MD, FRCP(UK) Department of Cardiovascular Therapeutics and Pharmacology, Queen’s University Belfast, Whitla Medical Building, Northern Ireland, United Kingdom
See editorial by Gryn and Hackam, pages 142-143 of this issue. The Development of Lifetime Risk Prediction Amid mounting concern that younger individuals are inadequately served by short-term risk prediction, the assessment of lifetime risk of a cardiovascular event is gaining credence. The majority of US adults (82%) are at low shortterm risk of a cardiovascular event,1 with almost all young individuals and women classified as low risk by current algorithms,2 in part because models such as Framingham weight excessively for age and sex (Table 1).3 This is misleading, as more than half of all cardiovascular events will occur in those labelled with a low or intermediate 10-year risk score (Fig. 1).4 To some degree, this apparent paradox may be attributed to the extent of the low- and intermediate-risk population, meaning that by sheer volume these individuals are expected to accrue the majority of events.5 However, within the low-risk category, there is a substantial variation in lifetime risk, with the emergence of a significant new group of those who are low short-term but high longterm risk. In those younger than 50 years, around half of those in the low short-term risk category fall into this group.6 The question is, why do some individuals continue to experience a low level of threat of an event for their life duration while others seemingly accumulate risk at a much greater rate? The answer may in part be found in the influence of various risk factors at different stages of life. For instance, absence of any risk factor at the age of 50 years is associated with persistently low lifetime risk compared with those with at least 2 risk factors, who seem to experience a dramatic escalation in risk over the course of their lifetime: 5.2% vs 68.9% in men and 8.2% vs 50.2% in women.7 What may be underappreciated is the interplay between separate risk factors and the potential for quiet accumulation of subclinical Received for publication August 25, 2011. Accepted March 30, 2012. Corresponding author: Dr Caroline Bleakley, Department of cardiovascular therapeutics and pharmacology, Queen’s University Belfast, Whitla Medical Building, 97 Lisburn Road, BT9 7BL, Northern Ireland, UK. E-mail: [email protected] See page 149 for disclosure information.
disease,5 a phenomenon referred to as the “cumulative damage theory.” This theory proposes that those without any risk factor have the advantage of nonexposure to the unseen accumulation of subclinical disease that affects counterparts with even a single risk factor.3,5 In addition, current risk prediction is limited by algorithms that demonstrate little or no evidence of the incorporation of treatment effects in the allocation of risk.8 Therapeutic intervention with statin and antiplatelet agents could reduce risk by as much as 50%, translating into a 12.5% risk reduction if even one-quarter of a cohort received medication.8 Depending on whether treatment was initiated prior to or following the initial assessment of risk, the model is likely to generate an inaccurate prediction for those with “treated” risk factors. This inflexibility in the algorithm would consequently result in either over- or underprediction of risk, respectively. For instance, even when treated, pre-existing risk factors will continue to exert over future cardiovascular events a cumulative influence that the model will not perceive. Time to Treat? Long-term treatment with few short-term gains is a hard sell both economically and morally. However, following the loss of simvastatin’s patent protection in 2006 and the subsequent advent of generically available statins, market competition has driven down costs, making it a more fiscally attractive long-term prescription.9 Data from the Heart Protection Study found that in those aged 40 to 49 years with a 5-year risk level of 12%, 1.67 life-years were gained from treatment.10 Moreover, the cost of treatment was found to be economical in subjects aged 35 to 85 years, costing less than £2500 (CAD3946.58 at £1 ⫽ CAD1.57863) per life-year gained.10 The question still remains, though, whether medical intervention is warranted at this level of risk, with little proof at this stage to support a substantial gain even in the long term. One study that does bring evidence to this debate is the West of Scotland Coronary Prevention Study (WOSCOPS),11 the pravastatin primary prevention trial
0828-282X/$ – see front matter © 2013 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.cjca.2012.03.025
148
Canadian Journal of Cardiology Volume 29 2013
Table 1. Summary of existing risk prediction models Outcomes
Comments
Framingham
Model
Traditional
Risk factors included
US, white, 30-62 years
Derivation population
CHD, stroke, TIA, PVD, HF
ATP (III)
Traditional
US, ⬎ 19 years
CHD
ASSIGN
Traditional ⫹ social deprivation ⫹ family history
Scotland, 30-74 years
CHD, revascularisation, fatal CV event
SCORE
Traditional
European, 45-64 years
Fatal CV event
Reynold’s
Traditional ⫹ family history ⫹ HbA1c (if person with diabetes) ⫹ hsCRP
US, women, aged ⬎ 45 years
MI, stroke, revascularization, fatal CV event
QRISK1
Traditional ⫹ family history ⫹ BMI ⫹ social deprivation
UK, 35-74 years
QRISK2
Traditional ⫹ ethnicity ⫹ BMI ⫹ family history ⫹ social deprivation ⫹ RA ⫹ AF ⫹ CKD
UK, 30-84 years
Composite CV endpoint, including MI, CHD, CVA, and TIA Composite CV endpoint including MI, CHD, CVA, and TIA
Exclusively white population. In a systematic review of 27 studies using the Framingham algorithm, the predicted-to-observed ratios varied from underestimation in a high-risk group by 0.43 to overestimation in a low-risk group by 2.87.24 Excludes family history and ethnicity. Divides predicted risk into 3 categories: high, moderate and low (⬎ 20%, 10%-20%, and ⬍ 10%). Distinguishes itself in recommendation of target LDL-C levels for each group; ⬍ 100, ⬍ 130, and ⬍ 160 mg/dL.25 Quantitative smoking assessment. Performed only marginally better than Framingham when applied to Scottish population.26 Still tended to overestimate risk.25 Based on 12 cohort studies with ⬎ 200,000 participants. Excludes family history and ethnicity. Unusually, the end points are fatal CV events, and therefore study provides no estimate of nonfatal event risk. Women only, inclusion of hsCRP. Using an adapted male algorithm, the model was successfully applied to a male population with greater accuracy than the original Framingham model. Provided more appropriate risk estimates when validated against Framingham in a UK population.27 In a recent UK study of ⬎ 1.5 million patients in primary care, QRISK2 was more accurate in identifying a highrisk population than was the NICE version of the Framingham equation. Limited evidence of superior risk identification when compared with its predecessor, QRISK1.28
AF, atrial fibrillation; ASSIGN, Scottish Intercollegiate Guidelines Network; BMI, body mass index; CHD, coronary heart disease; CKD, chronic kidney disease; CVA, cerebrovascular accident; CV, cardiovascular; HbA1c, hemoglobin A1c; hsCRP, high-sensitivity C-reactive protein; HF, heart failure; LDL-C, low-density lipoprotein cholesterol; MI, myocardial infarction; NICE, National Institute for Health and Clinical Excellence (UK); PVD, peripheral vascular disease; QRISK1 and QRISK2, QRESEARCH database risk score algorithms; RA, rheumatoid arthritis; SCORE, Systematic Coronary Risk Evaluation Project; TIA, transient ischaemic attack; traditional risk factors: hypertension, smoking, hyperlipidemia, diabetes.
and more specifically its follow-up study.12 These demonstrated the persistence of benefit from pravastatin therapy for at least a decade after the initial study period, and it is important that there was no indication of additional harm in the pravastatin group, providing insight into the incremental rewards that could possibly be on offer to those low-risk individuals willing to accept daily medication.
Figure 1. Percentage of 10-year coronary heart disease events in each risk category. Adapted from Enriquez and De Lemos4 with permission from Wiley Periodicals, Inc.
However, this is not to imprudently dismiss the potential for consequences to emerge from prolonged therapy. Indeed, there has been recent concern regarding statins’ potential hyperglycemic effect,13 which had previously been highlighted in a meta-analysis.14,15 While undoubtedly of concern, these findings may be tempered by the potential for cardiovascular risk reduction with statin therapy and consequently may not warrant anything besides vigilance. A suggested alternative approach is that of a low-dose regime of statin or aspirin therapy, the rationale being to minimize the potential side effects of long-term pharmacotherapy while still providing “background” cardiovascular protection. However, the Management of Elevated Cholesterol in the Primary Prevention Group of Adult Japanese (MEGA) trial16 and 2 recent meta-analyses17,18 failed to provide a conclusive recommendation for either therapy in primary prevention and highlighted an increased bleeding risk with daily aspirin. What may prove more palatable is to target lifestyle modification through primordial prevention.1 This strategy aims to avoid the onset of risk factors in the first instance through lifestyle adjustment and has been shown to be most effective in circumventing cardiovascular mortality.19,20 It is supported by evidence outlining the substantially increased life span of those with no risk factors as opposed to those with 1 or more, conveying the survival advantage conferred by risk factor avoidance.21,22
Bleakley et al. Next Generation in Risk Prediction
Future Guidelines Within the European setting, the just published draft guidance from the UK’s National Institute for Health and Clinical Excellence on hypertension does refer to the separate calculation of lifetime risk for hypertensive patients younger than 40 years. This approach is similar to that outlined almost a decade ago in the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) guidelines, which were comparatively ahead of their time in recommending identification, lifetime stratification, and lifestyle intervention in this subgroup but which again fell short of endorsing medical therapy.23 The current impasse, with no major body seemingly keen to be the first to take a more aggressive approach, may be slowly shifting. Guidelines imminently expected from the US (Adult Treatment Panel IV and the Eighth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure [JNC 8]) are widely anticipated to address the need for lifetime risk assessment, particularly in the young. While it remains unlikely that their basic stance of identification and lifestyle modification will be replaced by an aggressive primary prevention regime, the inclusion of lifetime risk should impact positively on conveyance of cardiovascular risk to the public. Conclusion Certainly the initiation of pharmacotherapy in large numbers of apparently healthy individuals is controversial. The incremental benefit of commencing medication at an early stage is currently overshadowed by safety and financial concerns about exposing vast numbers of the apparently healthy population to potent drugs. Neither of these arguments, however, is supported by current evidence, which gives credence to both the long-term safety of the statin group in particular and the financial viability of lifetime treatment. The anticipated incorporation of lifetime risk in the next generation of guidelines is a warranted advance in risk management. Funding Sources Dr Caroline Bleakley and Dr Auleen Millar are supported by Doctoral Fellowship Awards from the Northern Ireland Research and Development Office.
149 4. Enriquez JR, De Lemos JA. Should we focus on novel risk markers and screening tests to better predict and prevent cardiovascular disease? Prev Cardiol 2010;13:152-9. 5. James AS. Framing cardiovascular disease event risk prediction. Can J Cardiol 2011;27:171-3. 6. Berry JD, Liu K, Folsom AR, et al. Prevalence and progression of subclinical atherosclerosis in younger adults with low short-term but high lifetime estimated risk for cardiovascular disease: the coronary artery risk development in young adults study and multi-ethnic study of atherosclerosis. Circulation 2009;119: 382-9. 7. Lloyd-Jones DM, Leip EP, Larson MG, et al. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age. Circulation 2006;113:791-8. 8. Liew SM, Doust J, Glasziou P. Cardiovascular risk scores do not account for the effect of treatment: a review. Heart 2011;97:689-97. 9. Nambi V, Ballantyne CM. “Risky business”: ten years is not a lifetime. Circulation 2009;119:362-4. 10. Heart Protection Study Collaborative. Lifetime cost effectiveness of simvastatin in a range of risk groups and age groups derived from a randomised trial of 20536 people. BMJ 2006;333:1145. 11. Shepherd J, Cobbe SM, Ford I, et al. Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. N Engl J Med 1995;333:1301-8. 12. Ford I, Murray H, Packard CJ, Shepherd J, Macfarlane PW, Cobbe SM. Long-term follow-up of the West of Scotland Coronary Prevention Study. N Engl J Med 2007;357:1477-86. 13. Ridker PM, Danielson E, Fonseca FAH, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. New Eng J Med 2008;359:2195-207. 14. Sattar N, Preiss D, Murray HM, et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet 2010;375:735-42. 15. Pletcher MJ, Hulley SB. Statin therapy in young adults: ready for prime time?. J Am Coll Cardiol 2010;56:637-40. 16. Nakamura H, Arakawa K, Itakura H, et al. Primary prevention of cardiovascular disease with pravastatin in Japan (MEGA study): a prospective randomised controlled trial. Lancet 2006;368:1155-63. 17. Seshasai SRK, Wijesuriya S, Sivakumaran R, et al. Effect of aspirin on vascular and nonvascular outcomes: meta-analysis of randomized controlled trials. Arch Intern Med 2012;172:209-16. 18. Bartolucci AA, Tendera M, Howard G. Meta-analysis of multiple primary prevention trials of cardiovascular events using aspirin. Am J Cardiol 2011;107:1796-801.
Disclosures None of the authors have any conflicts of interest.
19. Labarthe DR. Prevention of cardiovascular risk factors in the first place. Prev Med 1999;29:S72-8.
References
20. Stampfer MJ, Hu FB, Manson JE, Rimm EB, Willett WC. Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med 2000;343:16-22.
1. Marma AK, Berry JD, Ning H, Persell SD, Lloyd-Jones DM. Distribution of 10-year and lifetime predicted risks for cardiovascular disease in US adults: findings from the National Health and Nutrition Examination Survey 2003 to 2006. Circ Cardiovasc Qual Outcomes 2010; 3:8-14.
21. Daviglus ML, Liu K, Greenland P, et al. Benefit of a Favorable Cardiovascular risk-factor profile in middle age with respect to Medicare costs. N Engl J Med 1998;339:1122-9.
2. Jackson R. Cardiovascular risk prediction: are we there yet?. Heart 2008; 94:1-3.
22. Daviglus ML, Liu K, Pirzada A, et al. Favorable cardiovascular risk profile in middle age and health-related quality of life in older age. Arch Intern Med 2003;163:2460-8.
3. Lloyd-Jones DM, Wilson PW, Larson MG, et al. Framingham risk score and prediction of lifetime risk for coronary heart disease. Am J Cardiol 2004;94:20-4.
23. Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood
150
Canadian Journal of Cardiology Volume 29 2013
Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002;106:3143.
assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC). Heart 2007;93:172-6.
24. Brindle P, Beswick A, Fahey T, Ebrahim S. Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart 2006;92:1752-9.
27. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Brindle P. Performance of the QRISK cardiovascular risk prediction algorithm in an independent UK sample of patients from general practice: a validation study. Heart 2008;94:34-9.
25. Berger JS, Jordan CO, Lloyd-Jones D, Blumenthal RS. Screening for cardiovascular risk in asymptomatic patients. J Am Coll Cardiol 2010;55:1169-77. 26. Woodward M, Brindle P, Tunstall-Pedoe H; SIGN group on risk estimation. Adding social deprivation and family history to cardiovascular risk
28. Collins GS, Altman DG. An independent and external validation of QRISK2 cardiovascular disease risk score: a prospective open cohort study. BMJ 2010;340:2442.
Viewpoint
Lifetime Risk of Cardiovascular Disease: The Next Generation in Risk Prediction Caroline Bleakley, MB, BCh, BAO, MRCP(UK), Auleen Millar, MB, BCh, BAO, MRCP(UK), Mark Harbinson, MD, FRCP(UK), and Gary Eugene McVeigh, MD, FRCP(UK) Department of Cardiovascular Therapeutics and Pharmacology, Queen’s University Belfast, Whitla Medical Building, Northern Ireland, United Kingdom
See editorial by Gryn and Hackam, pages 142-143 of this issue. The Development of Lifetime Risk Prediction Amid mounting concern that younger individuals are inadequately served by short-term risk prediction, the assessment of lifetime risk of a cardiovascular event is gaining credence. The majority of US adults (82%) are at low shortterm risk of a cardiovascular event,1 with almost all young individuals and women classified as low risk by current algorithms,2 in part because models such as Framingham weight excessively for age and sex (Table 1).3 This is misleading, as more than half of all cardiovascular events will occur in those labelled with a low or intermediate 10-year risk score (Fig. 1).4 To some degree, this apparent paradox may be attributed to the extent of the low- and intermediate-risk population, meaning that by sheer volume these individuals are expected to accrue the majority of events.5 However, within the low-risk category, there is a substantial variation in lifetime risk, with the emergence of a significant new group of those who are low short-term but high longterm risk. In those younger than 50 years, around half of those in the low short-term risk category fall into this group.6 The question is, why do some individuals continue to experience a low level of threat of an event for their life duration while others seemingly accumulate risk at a much greater rate? The answer may in part be found in the influence of various risk factors at different stages of life. For instance, absence of any risk factor at the age of 50 years is associated with persistently low lifetime risk compared with those with at least 2 risk factors, who seem to experience a dramatic escalation in risk over the course of their lifetime: 5.2% vs 68.9% in men and 8.2% vs 50.2% in women.7 What may be underappreciated is the interplay between separate risk factors and the potential for quiet accumulation of subclinical Received for publication August 25, 2011. Accepted March 30, 2012. Corresponding author: Dr Caroline Bleakley, Department of cardiovascular therapeutics and pharmacology, Queen’s University Belfast, Whitla Medical Building, 97 Lisburn Road, BT9 7BL, Northern Ireland, UK. E-mail: [email protected] See page 149 for disclosure information.
disease,5 a phenomenon referred to as the “cumulative damage theory.” This theory proposes that those without any risk factor have the advantage of nonexposure to the unseen accumulation of subclinical disease that affects counterparts with even a single risk factor.3,5 In addition, current risk prediction is limited by algorithms that demonstrate little or no evidence of the incorporation of treatment effects in the allocation of risk.8 Therapeutic intervention with statin and antiplatelet agents could reduce risk by as much as 50%, translating into a 12.5% risk reduction if even one-quarter of a cohort received medication.8 Depending on whether treatment was initiated prior to or following the initial assessment of risk, the model is likely to generate an inaccurate prediction for those with “treated” risk factors. This inflexibility in the algorithm would consequently result in either over- or underprediction of risk, respectively. For instance, even when treated, pre-existing risk factors will continue to exert over future cardiovascular events a cumulative influence that the model will not perceive. Time to Treat? Long-term treatment with few short-term gains is a hard sell both economically and morally. However, following the loss of simvastatin’s patent protection in 2006 and the subsequent advent of generically available statins, market competition has driven down costs, making it a more fiscally attractive long-term prescription.9 Data from the Heart Protection Study found that in those aged 40 to 49 years with a 5-year risk level of 12%, 1.67 life-years were gained from treatment.10 Moreover, the cost of treatment was found to be economical in subjects aged 35 to 85 years, costing less than £2500 (CAD3946.58 at £1 ⫽ CAD1.57863) per life-year gained.10 The question still remains, though, whether medical intervention is warranted at this level of risk, with little proof at this stage to support a substantial gain even in the long term. One study that does bring evidence to this debate is the West of Scotland Coronary Prevention Study (WOSCOPS),11 the pravastatin primary prevention trial
0828-282X/$ – see front matter © 2013 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.cjca.2012.03.025
148
Canadian Journal of Cardiology Volume 29 2013
Table 1. Summary of existing risk prediction models Outcomes
Comments
Framingham
Model
Traditional
Risk factors included
US, white, 30-62 years
Derivation population
CHD, stroke, TIA, PVD, HF
ATP (III)
Traditional
US, ⬎ 19 years
CHD
ASSIGN
Traditional ⫹ social deprivation ⫹ family history
Scotland, 30-74 years
CHD, revascularisation, fatal CV event
SCORE
Traditional
European, 45-64 years
Fatal CV event
Reynold’s
Traditional ⫹ family history ⫹ HbA1c (if person with diabetes) ⫹ hsCRP
US, women, aged ⬎ 45 years
MI, stroke, revascularization, fatal CV event
QRISK1
Traditional ⫹ family history ⫹ BMI ⫹ social deprivation
UK, 35-74 years
QRISK2
Traditional ⫹ ethnicity ⫹ BMI ⫹ family history ⫹ social deprivation ⫹ RA ⫹ AF ⫹ CKD
UK, 30-84 years
Composite CV endpoint, including MI, CHD, CVA, and TIA Composite CV endpoint including MI, CHD, CVA, and TIA
Exclusively white population. In a systematic review of 27 studies using the Framingham algorithm, the predicted-to-observed ratios varied from underestimation in a high-risk group by 0.43 to overestimation in a low-risk group by 2.87.24 Excludes family history and ethnicity. Divides predicted risk into 3 categories: high, moderate and low (⬎ 20%, 10%-20%, and ⬍ 10%). Distinguishes itself in recommendation of target LDL-C levels for each group; ⬍ 100, ⬍ 130, and ⬍ 160 mg/dL.25 Quantitative smoking assessment. Performed only marginally better than Framingham when applied to Scottish population.26 Still tended to overestimate risk.25 Based on 12 cohort studies with ⬎ 200,000 participants. Excludes family history and ethnicity. Unusually, the end points are fatal CV events, and therefore study provides no estimate of nonfatal event risk. Women only, inclusion of hsCRP. Using an adapted male algorithm, the model was successfully applied to a male population with greater accuracy than the original Framingham model. Provided more appropriate risk estimates when validated against Framingham in a UK population.27 In a recent UK study of ⬎ 1.5 million patients in primary care, QRISK2 was more accurate in identifying a highrisk population than was the NICE version of the Framingham equation. Limited evidence of superior risk identification when compared with its predecessor, QRISK1.28
AF, atrial fibrillation; ASSIGN, Scottish Intercollegiate Guidelines Network; BMI, body mass index; CHD, coronary heart disease; CKD, chronic kidney disease; CVA, cerebrovascular accident; CV, cardiovascular; HbA1c, hemoglobin A1c; hsCRP, high-sensitivity C-reactive protein; HF, heart failure; LDL-C, low-density lipoprotein cholesterol; MI, myocardial infarction; NICE, National Institute for Health and Clinical Excellence (UK); PVD, peripheral vascular disease; QRISK1 and QRISK2, QRESEARCH database risk score algorithms; RA, rheumatoid arthritis; SCORE, Systematic Coronary Risk Evaluation Project; TIA, transient ischaemic attack; traditional risk factors: hypertension, smoking, hyperlipidemia, diabetes.
and more specifically its follow-up study.12 These demonstrated the persistence of benefit from pravastatin therapy for at least a decade after the initial study period, and it is important that there was no indication of additional harm in the pravastatin group, providing insight into the incremental rewards that could possibly be on offer to those low-risk individuals willing to accept daily medication.
Figure 1. Percentage of 10-year coronary heart disease events in each risk category. Adapted from Enriquez and De Lemos4 with permission from Wiley Periodicals, Inc.
However, this is not to imprudently dismiss the potential for consequences to emerge from prolonged therapy. Indeed, there has been recent concern regarding statins’ potential hyperglycemic effect,13 which had previously been highlighted in a meta-analysis.14,15 While undoubtedly of concern, these findings may be tempered by the potential for cardiovascular risk reduction with statin therapy and consequently may not warrant anything besides vigilance. A suggested alternative approach is that of a low-dose regime of statin or aspirin therapy, the rationale being to minimize the potential side effects of long-term pharmacotherapy while still providing “background” cardiovascular protection. However, the Management of Elevated Cholesterol in the Primary Prevention Group of Adult Japanese (MEGA) trial16 and 2 recent meta-analyses17,18 failed to provide a conclusive recommendation for either therapy in primary prevention and highlighted an increased bleeding risk with daily aspirin. What may prove more palatable is to target lifestyle modification through primordial prevention.1 This strategy aims to avoid the onset of risk factors in the first instance through lifestyle adjustment and has been shown to be most effective in circumventing cardiovascular mortality.19,20 It is supported by evidence outlining the substantially increased life span of those with no risk factors as opposed to those with 1 or more, conveying the survival advantage conferred by risk factor avoidance.21,22
Bleakley et al. Next Generation in Risk Prediction
Future Guidelines Within the European setting, the just published draft guidance from the UK’s National Institute for Health and Clinical Excellence on hypertension does refer to the separate calculation of lifetime risk for hypertensive patients younger than 40 years. This approach is similar to that outlined almost a decade ago in the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) guidelines, which were comparatively ahead of their time in recommending identification, lifetime stratification, and lifestyle intervention in this subgroup but which again fell short of endorsing medical therapy.23 The current impasse, with no major body seemingly keen to be the first to take a more aggressive approach, may be slowly shifting. Guidelines imminently expected from the US (Adult Treatment Panel IV and the Eighth Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure [JNC 8]) are widely anticipated to address the need for lifetime risk assessment, particularly in the young. While it remains unlikely that their basic stance of identification and lifestyle modification will be replaced by an aggressive primary prevention regime, the inclusion of lifetime risk should impact positively on conveyance of cardiovascular risk to the public. Conclusion Certainly the initiation of pharmacotherapy in large numbers of apparently healthy individuals is controversial. The incremental benefit of commencing medication at an early stage is currently overshadowed by safety and financial concerns about exposing vast numbers of the apparently healthy population to potent drugs. Neither of these arguments, however, is supported by current evidence, which gives credence to both the long-term safety of the statin group in particular and the financial viability of lifetime treatment. The anticipated incorporation of lifetime risk in the next generation of guidelines is a warranted advance in risk management. Funding Sources Dr Caroline Bleakley and Dr Auleen Millar are supported by Doctoral Fellowship Awards from the Northern Ireland Research and Development Office.
149 4. Enriquez JR, De Lemos JA. Should we focus on novel risk markers and screening tests to better predict and prevent cardiovascular disease? Prev Cardiol 2010;13:152-9. 5. James AS. Framing cardiovascular disease event risk prediction. Can J Cardiol 2011;27:171-3. 6. Berry JD, Liu K, Folsom AR, et al. Prevalence and progression of subclinical atherosclerosis in younger adults with low short-term but high lifetime estimated risk for cardiovascular disease: the coronary artery risk development in young adults study and multi-ethnic study of atherosclerosis. Circulation 2009;119: 382-9. 7. Lloyd-Jones DM, Leip EP, Larson MG, et al. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age. Circulation 2006;113:791-8. 8. Liew SM, Doust J, Glasziou P. Cardiovascular risk scores do not account for the effect of treatment: a review. Heart 2011;97:689-97. 9. Nambi V, Ballantyne CM. “Risky business”: ten years is not a lifetime. Circulation 2009;119:362-4. 10. Heart Protection Study Collaborative. Lifetime cost effectiveness of simvastatin in a range of risk groups and age groups derived from a randomised trial of 20536 people. BMJ 2006;333:1145. 11. Shepherd J, Cobbe SM, Ford I, et al. Prevention of coronary heart disease with pravastatin in men with hypercholesterolemia. N Engl J Med 1995;333:1301-8. 12. Ford I, Murray H, Packard CJ, Shepherd J, Macfarlane PW, Cobbe SM. Long-term follow-up of the West of Scotland Coronary Prevention Study. N Engl J Med 2007;357:1477-86. 13. Ridker PM, Danielson E, Fonseca FAH, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. New Eng J Med 2008;359:2195-207. 14. Sattar N, Preiss D, Murray HM, et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet 2010;375:735-42. 15. Pletcher MJ, Hulley SB. Statin therapy in young adults: ready for prime time?. J Am Coll Cardiol 2010;56:637-40. 16. Nakamura H, Arakawa K, Itakura H, et al. Primary prevention of cardiovascular disease with pravastatin in Japan (MEGA study): a prospective randomised controlled trial. Lancet 2006;368:1155-63. 17. Seshasai SRK, Wijesuriya S, Sivakumaran R, et al. Effect of aspirin on vascular and nonvascular outcomes: meta-analysis of randomized controlled trials. Arch Intern Med 2012;172:209-16. 18. Bartolucci AA, Tendera M, Howard G. Meta-analysis of multiple primary prevention trials of cardiovascular events using aspirin. Am J Cardiol 2011;107:1796-801.
Disclosures None of the authors have any conflicts of interest.
19. Labarthe DR. Prevention of cardiovascular risk factors in the first place. Prev Med 1999;29:S72-8.
References
20. Stampfer MJ, Hu FB, Manson JE, Rimm EB, Willett WC. Primary prevention of coronary heart disease in women through diet and lifestyle. N Engl J Med 2000;343:16-22.
1. Marma AK, Berry JD, Ning H, Persell SD, Lloyd-Jones DM. Distribution of 10-year and lifetime predicted risks for cardiovascular disease in US adults: findings from the National Health and Nutrition Examination Survey 2003 to 2006. Circ Cardiovasc Qual Outcomes 2010; 3:8-14.
21. Daviglus ML, Liu K, Greenland P, et al. Benefit of a Favorable Cardiovascular risk-factor profile in middle age with respect to Medicare costs. N Engl J Med 1998;339:1122-9.
2. Jackson R. Cardiovascular risk prediction: are we there yet?. Heart 2008; 94:1-3.
22. Daviglus ML, Liu K, Pirzada A, et al. Favorable cardiovascular risk profile in middle age and health-related quality of life in older age. Arch Intern Med 2003;163:2460-8.
3. Lloyd-Jones DM, Wilson PW, Larson MG, et al. Framingham risk score and prediction of lifetime risk for coronary heart disease. Am J Cardiol 2004;94:20-4.
23. Third report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood
150
Canadian Journal of Cardiology Volume 29 2013
Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002;106:3143.
assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC). Heart 2007;93:172-6.
24. Brindle P, Beswick A, Fahey T, Ebrahim S. Accuracy and impact of risk assessment in the primary prevention of cardiovascular disease: a systematic review. Heart 2006;92:1752-9.
27. Hippisley-Cox J, Coupland C, Vinogradova Y, Robson J, Brindle P. Performance of the QRISK cardiovascular risk prediction algorithm in an independent UK sample of patients from general practice: a validation study. Heart 2008;94:34-9.
25. Berger JS, Jordan CO, Lloyd-Jones D, Blumenthal RS. Screening for cardiovascular risk in asymptomatic patients. J Am Coll Cardiol 2010;55:1169-77. 26. Woodward M, Brindle P, Tunstall-Pedoe H; SIGN group on risk estimation. Adding social deprivation and family history to cardiovascular risk
28. Collins GS, Altman DG. An independent and external validation of QRISK2 cardiovascular disease risk score: a prospective open cohort study. BMJ 2010;340:2442.