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2000
Volume 20, Issue 6
  • ISSN: 1573-403X
  • E-ISSN:

Abstract

Over the past decades, there has been a notable increase in the risk of Cardiovascular Disease (CVD), even among younger individuals. Policymakers and the health community have revised CVD prevention programs to include younger people in order to take these new circumstances into account. A variety of CVD risk assessment tools have been developed in the past years with the aim of identifying potential CVD candidates at the population level; however, they can hardly discriminate against younger individuals at high risk of CVD.Therefore, in addition to the traditional 10-year CVD risk assessment, lifetime CVD risk assessment has recently been recommended by the American Heart Association/American College of Cardiology and the European Society of Cardiology prevention guidelines, particularly for young individuals. Methodologically, the benefits of these lifetime prediction models are the incorporation of left truncation observed in survival curves and the risk of competing events which are not considered equivalent in the common survival analysis. Thus, lifetime risk data are easily understandable and can be utilized as a risk communication tool for Public Health surveillance. However, given the peculiarities behind these estimates, structural harmonization should be conducted in order to create a sex-, race-specific tool that is sensitive to accurately identifying individuals who are at high risk of CVD. In this review manuscript, we present the most commonly used lifetime CVD risk tools, elucidate several methodological and critical points, their limitations, and the rationale behind their integration into everyday clinical practice.

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References

  1. TimmisA. VardasP. TownsendN. European Society of Cardiology: cardiovascular disease statistics 2021.Eur. Heart J.202243871679910.1093/eurheartj/ehab892 35016208
    [Google Scholar]
  2. RothG.A. MensahG.A. JohnsonC.O. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019.J. Am. Coll. Cardiol.202076252982302110.1016/j.jacc.2020.11.010 33309175
    [Google Scholar]
  3. SunJ. QiaoY. ZhaoM. MagnussenC.G. XiB. Global, regional, and national burden of cardiovascular diseases in youths and young adults aged 15–39 years in 204 countries/territories, 1990–2019: a systematic analysis of Global Burden of Disease Study 2019.BMC Med.202321122210.1186/s12916‑023‑02925‑4 37365627
    [Google Scholar]
  4. VisserenF.L.J. MachF. SmuldersY.M. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice.Eur. Heart J.202142343227333710.1093/eurheartj/ehab484 34458905
    [Google Scholar]
  5. GrundyS.M. StoneN.J. BaileyA.L. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.Circulation201913925e1082e1143 30586774
    [Google Scholar]
  6. ArnettD.K. BlumenthalR.S. AlbertM.A. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.Circulation201914011e596e64610.1161/CIR.0000000000000678 30879355
    [Google Scholar]
  7. WheltonP.K. CareyR.M. AronowW.S. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults.J. Am. Coll. Cardiol.20187119e127e24810.1016/j.jacc.2017.11.006 29146535
    [Google Scholar]
  8. SDG target 3.4 reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being.2023Available from: https://www.who.int/data/gho/data/themes/topics/indicator-groups/indicator-group-details/GHO/sdg-target-3.4-noncommunicable-diseases-and-mental-health
  9. United States Transforming our world: The 2030 agenda for sustainable development.2016Available from: https://sdgs.un.org/2030agenda
    [Google Scholar]
  10. PanagiotakosD.B. StavrinosV. Methodological issues in cardiovascular epidemiology: the risk of determining absolute risk through statistical models.Vasc. Health Risk Manag.20062330931510.2147/vhrm.2006.2.3.309 17326336
    [Google Scholar]
  11. CooneyM.T. DudinaA.L. GrahamI.M. Value and limitations of existing scores for the assessment of cardiovascular risk: a review for clinicians.J. Am. Coll. Cardiol.200954141209122710.1016/j.jacc.2009.07.020 19778661
    [Google Scholar]
  12. Lloyd-JonesD.M. BraunL.T. NdumeleC.E. Use of risk assessment tools to guide decision-making in the primary prevention of atherosclerotic cardiovascular disease.J. Am. Coll. Cardiol.201973243153316710.1016/j.jacc.2018.11.005 30423392
    [Google Scholar]
  13. D’AgostinoR.B.Sr VasanR.S. PencinaM.J. General cardiovascular risk profile for use in primary care: the Framingham Heart Study.Circulation2008117674375310.1161/CIRCULATIONAHA.107.699579 18212285
    [Google Scholar]
  14. GoffDCJr Lloyd-JonesDM BennettG 2013 ACC/AHA guideline on the assessment of cardiovascular risk. Circulation201412925_suppl_2)(Suppl. 2S497310.1161/01.cir.0000437741.48606.9824222018
    [Google Scholar]
  15. ConroyR. PyöräläK. FitzgeraldA.P. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project.Eur. Heart J.20032411987100310.1016/S0195‑668X(03)00114‑3 12788299
    [Google Scholar]
  16. HagemanS. PennellsL. OjedaF. SCORE2 risk prediction algorithms: new models to estimate 10-year risk of cardiovascular disease in Europe.Eur. Heart J.202142252439245410.1093/eurheartj/ehab309 34120177
    [Google Scholar]
  17. de VriesT.I. CooneyM.T. SelmerR.M. SCORE2-OP risk prediction algorithms: estimating incident cardiovascular event risk in older persons in four geographical risk regions.Eur. Heart J.202142252455246710.1093/eurheartj/ehab312 34120185
    [Google Scholar]
  18. CooneyM.T. SelmerR. LindmanA. Cardiovascular risk estimation in older persons: SCORE O.P.Eur. J. Prev. Cardiol.201623101093110310.1177/2047487315588390 26040999
    [Google Scholar]
  19. Hippisley-CoxJ. CouplandC. VinogradovaY. Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2.BMJ200833676591475148210.1136/bmj.39609.449676.25 18573856
    [Google Scholar]
  20. Hippisley-CoxJ. CouplandC. BrindleP. Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study.BMJ2017357j209910.1136/bmj.j2099 28536104
    [Google Scholar]
  21. Hippisley-CoxJ. CouplandC. VinogradovaY. RobsonJ. MayM. BrindleP. Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study.BMJ2007335761113610.1136/bmj.39261.471806.55 17615182
    [Google Scholar]
  22. BudoffM.J. YoungR. BurkeG. Ten-year association of coronary artery calcium with atherosclerotic cardiovascular disease (ASCVD) events: the multi-ethnic study of atherosclerosis (MESA).Eur. Heart J.201839252401240810.1093/eurheartj/ehy217 29688297
    [Google Scholar]
  23. McClellandR.L. JorgensenN.W. BudoffM. 10-Year coronary heart disease risk prediction using coronary artery calcium and traditional risk factors.J. Am. Coll. Cardiol.201566151643165310.1016/j.jacc.2015.08.035 26449133
    [Google Scholar]
  24. WoodwardM. BrindleP. Tunstall-PedoeH. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC).Heart200593217217610.1136/hrt.2006.108167 17090561
    [Google Scholar]
  25. NHS ScotlandASSIGN Score – prioritising prevention of cardiovascular disease.2023Available from: https://www.assign-score.com
    [Google Scholar]
  26. RidkerP.M. PaynterN.P. RifaiN. GazianoJ.M. CookN.R. C-reactive protein and parental history improve global cardiovascular risk predic-tion: The Reynolds Risk Score for men.Circulation20081182222432251
    [Google Scholar]
  27. RidkerP.M. BuringJ.E. RifaiN. CookN.R. Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score.JAMA2007297661161910.1001/jama.297.6.611 17299196
    [Google Scholar]
  28. AssmannG. CullenP. SchulteH. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Münster (PROCAM) study.Circulation2002105331031510.1161/hc0302.102575 11804985
    [Google Scholar]
  29. McGorrianC. YusufS. IslamS. Estimating modifiable coronary heart disease risk in multiple regions of the world: the INTERHEART Modifiable Risk Score.Eur. Heart J.201132558158910.1093/eurheartj/ehq448 21177699
    [Google Scholar]
  30. NavarA.M. WangT.Y. MiX. Influence of cardiovascular risk communication tools and presentation formats on patient perceptions and preferences.JAMA Cardiol.20183121192119910.1001/jamacardio.2018.3680 30419113
    [Google Scholar]
  31. JacksonR. LawesC. BennettD. MilneR. RodgersA. Treatment with drugs to lower blood pressure and blood cholesterol based on an individual’s absolute cardiovascular risk.Lancet2005365945743444110.1016/S0140‑6736(05)70240‑3 15680460
    [Google Scholar]
  32. GidlowCJ EllisNJ RileyV Cardiovascular disease risk communication in NHS Health Checks: A qualitative video-stimulated re-call interview study with practitioners. BJGP Open202155BJGPO.2021.0049.10.3399/BJGPO.2021.004934172476
    [Google Scholar]
  33. Lloyd-JonesD.M. LeipE.P. LarsonM.G. Prediction of lifetime risk for cardiovascular disease by risk factor burden at 50 years of age.Circulation2006113679179810.1161/CIRCULATIONAHA.105.548206 16461820
    [Google Scholar]
  34. WilsonP.W.F. Prediction of cardiovascular disease events.Cardiol. Clin.201129111310.1016/j.ccl.2010.10.004 21257097
    [Google Scholar]
  35. AlagonaP.Jr AhmadT.A. Cardiovascular disease risk assessment and prevention: current guidelines and limitations.Med. Clin. North Am.201599471173110.1016/j.mcna.2015.02.003 26042878
    [Google Scholar]
  36. RuwanpathiranaT. OwenA. ReidC.M. Review on cardiovascular risk prediction.Cardiovasc. Ther.2015332627010.1111/1755‑5922.12110 25758853
    [Google Scholar]
  37. SofogianniA. StalikasN. AntzaC. TziomalosK. Cardiovascular risk prediction models and scores in the era of personalized medicine.J. Pers. Med.2022127118010.3390/jpm12071180 35887677
    [Google Scholar]
  38. KannelW.B. McGeeD. GordonT. A general cardiovascular risk profile: The Framingham study.Am. J. Cardiol.1976381465110.1016/0002‑9149(76)90061‑8 132862
    [Google Scholar]
  39. Lloyd-JonesD.M. WangT.J. LeipE.P. Lifetime risk for development of atrial fibrillation: the Framingham Heart Study.Circulation200411091042104610.1161/01.CIR.0000140263.20897.42 15313941
    [Google Scholar]
  40. PutterH. FioccoM. GeskusR.B. Tutorial in biostatistics: competing risks and multi‐state models.Stat. Med.200726112389243010.1002/sim.2712 17031868
    [Google Scholar]
  41. HuebnerM. WolkewitzM. Enriquez-SaranoM. SchumacherM. Competing risks need to be considered in survival analysis models for cardiovascular outcomes.J. Thorac. Cardiovasc. Surg.201715361427143110.1016/j.jtcvs.2016.12.039 28526103
    [Google Scholar]
  42. AustinP.C. LeeD.S. FineJ.P. Introduction to the analysis of survival data in the presence of competing risks.Circulation2016133660160910.1161/CIRCULATIONAHA.115.017719 26858290
    [Google Scholar]
  43. DhingraR. VasanR.S. Age as a risk factor.Med. Clin. North Am.2012961879110.1016/j.mcna.2011.11.003 22391253
    [Google Scholar]
  44. RidkerP.M. CookN. Should age and time be eliminated from cardiovascular risk prediction models? Rationale for the creation of a new national risk detection program.Circulation2005111565765810.1161/01.CIR.0000154544.90488.52 15699285
    [Google Scholar]
  45. NavarA.M. StoneN.J. MartinS.S. What to say and how to say it.Curr. Opin. Cardiol.201631553754410.1097/HCO.0000000000000322 27428113
    [Google Scholar]
  46. PetrE.J. AyersC.R. PandeyA. Perceived lifetime risk for cardiovascular disease (from the Dallas Heart Study).Am. J. Cardiol.20141141535810.1016/j.amjcard.2014.04.006 24834788
    [Google Scholar]
  47. BonnerC. BatcupC. CornellS. Interventions Using Heart Age for Cardiovascular Disease Risk Communication: Systematic Review of Psychological, Behavioral, and Clinical Effects.JMIR Cardio202152e3105610.2196/31056 34738908
    [Google Scholar]
  48. KarmaliK.N. Lloyd-JonesD.M. Adding a life-course perspective to cardiovascular-risk communication.Nat. Rev. Cardiol.201310211111510.1038/nrcardio.2012.185 23296067
    [Google Scholar]
  49. MarmaA.K. Lloyd-JonesD.M. Systematic examination of the updated Framingham heart study general cardiovascular risk profile.Circulation2009120538439010.1161/CIRCULATIONAHA.108.835470 19620502
    [Google Scholar]
  50. ACC ASCVD Risk Estimator + 2023.2023Available from: https://tools.acc.org/ASCVD-Risk-Estimator-Plus/#!/calculate/estimate
    [Google Scholar]
  51. AHA 2018 Prevention Guidelines Tool CV Risk Calculator.2023Available from: https://professional.heart.org/en/science-news/food-is-medicine
    [Google Scholar]
  52. EAPC HeartScore.2023Available from: https://www.heartscore.org/en_GB?_gl=1*cyfpox*_ga*MTk1ODEyNjc3Ni4xNzAxMzc5ODcz*_ga_5Y189L6T14*MTcwMjgyNTg5NS41LjEuMTcwMjgyNTk4NS42MC4wLjA.*_ga_VPF4X3T28K*MTcwMjgyNTg5NS41LjEuMTcwMjgyNTk4NS4wLjAuMA.&_ga=2.39271651.1158321762.1702825895-1958126776.1701379873
    [Google Scholar]
  53. ClinRisk Ltd. QRISK3. 2023. Available from: https://qrisk.org
  54. Multi-ethnic study of atherosclerosis. MESA 10-Year CHD risk with coronary artery calcification.2023Available from: https://www.mesa-nhlbi.org/MESACHDRisk/MesaRiskScore/RiskScore.aspx
  55. Reynolds Risk Score2023Available from: https://www.scymed.com/en/smnxph/phqgg440.htm
  56. MDAppCardiovascular Risk PROCAM Score Calculator.2017Available from: https://www.mdapp.co/cardiovascular-risk-procam-score-calculator-255/
    [Google Scholar]
  57. Lloyd-JonesD.M. LarsonM.G. BeiserA. LevyD. Lifetime risk of developing coronary heart disease.Lancet19993539147899210.1016/S0140‑6736(98)10279‑9 10023892
    [Google Scholar]
  58. SeshadriS. WolfP.A. Lifetime risk of stroke and dementia: current concepts, and estimates from the Framingham Study.Lancet Neurol.20076121106111410.1016/S1474‑4422(07)70291‑0 18031707
    [Google Scholar]
  59. ConnerS.C. BeiserA. BenjaminE.J. LaValleyM.P. LarsonM.G. TrinquartL. A comparison of statistical methods to predict the residual lifetime risk.Eur. J. Epidemiol.202237217319410.1007/s10654‑021‑00815‑8 34978669
    [Google Scholar]
  60. FeuerE.J. WunL.M. BoringC.C. FlandersW.D. TimmelM.J. TongT. The lifetime risk of developing breast cancer.J. Natl. Cancer Inst.1993851189289710.1093/jnci/85.11.892 8492317
    [Google Scholar]
  61. GeskusR.B. Data analysis with competing risks and intermediate states.CRC Press201510.1201/b18695
    [Google Scholar]
  62. BeiserA. D’AgostinoR.B.Sr SeshadriS. SullivanL.M. WolfP.A. Computing estimates of incidence, including lifetime risk: Alzheimer’s disease in the Framingham Study. The Practical Incidence Estimators (PIE) macro.Stat. Med.20001911-121495152210.1002/(SICI)1097‑0258(20000615/30)19:11/12<1495::AID‑SIM441>3.0.CO;2‑E 10844714
    [Google Scholar]
  63. DeoS.V. DeoV. SundaramV. Survival analysis—part 3: intermediate events and the importance of competing risks.Indian Journal of Thoracic and Cardiovascular Surgery202137336737010.1007/s12055‑021‑01151‑y 33967437
    [Google Scholar]
  64. LacnyS. WilsonT. ClementF. Kaplan–Meier survival analysis overestimates cumulative incidence of health-related events in competing risk settings: a meta-analysis.J. Clin. Epidemiol.201893253510.1016/j.jclinepi.2017.10.006 29045808
    [Google Scholar]
  65. HagemanS.H.J. DorresteijnJ.A.N. PennellsL. The relevance of competing risk adjustment in cardiovascular risk prediction models for clinical practice.Eur. J. Prev. Cardiol.202330161741174710.1093/eurjpc/zwad202 37338108
    [Google Scholar]
  66. Lloyd-JonesD.M. WilsonP.W.F. LarsonM.G. Framingham risk score and prediction of lifetime risk for coronary heart disease.Am. J. Cardiol.2004941202410.1016/j.amjcard.2004.03.023 15219502
    [Google Scholar]
  67. ImaiY. Mizuno TanakaS. SatohM. Prediction of Lifetime Risk of Cardiovascular Disease Deaths Stratified by Sex in the Japanese Population.J. Am. Heart Assoc.20211023e02175310.1161/JAHA.121.021753 34845914
    [Google Scholar]
  68. PanagiotakosD. ChrysohoouC. DamigouE. Prediction of lifetime risk for cardiovascular disease, by risk factors level: the ATTICA epidemiological cohort study (2002–2022).Ann. Epidemiol.202387172410.1016/j.annepidem.2023.09.010 37866102
    [Google Scholar]
  69. CollettD. Modelling survival data in medical research.4th edBoca RatonCRC Press, Taylor and Francis202310.1201/9781003282525
    [Google Scholar]
  70. De BackerG. De BacquerD. Lifetime-risk prediction: a complicated business.Lancet19993539147828310.1016/S0140‑6736(98)00404‑8 10023886
    [Google Scholar]
  71. LicherS. HeshmatollahA. van der WillikK.D. Lifetime risk and multimorbidity of non-communicable diseases and disease-free life expectancy in the general population: A population-based cohort study.PLoS Med.2019162e100274110.1371/journal.pmed.1002741 30716101
    [Google Scholar]
  72. BenderA.P. PunykoJ. WilliamsA.N. BushhouseS.A. A standard person-years approach to estimating lifetime cancer risk.Cancer Causes Control199231697510.1007/BF00051915 1536916
    [Google Scholar]
  73. QwasmehA.A.H. SalehB.A.A. Radiation dose and lifetime risk for radiation-induced cancer due to natural radioactivity in tap water from Jordan.Radiat. Environ. Biophys.202362227928510.1007/s00411‑023‑01018‑3 36862217
    [Google Scholar]
  74. AldekheelM. FarahaniV.J. SioutasC. Assessing Lifetime Cancer Risk Associated with Population Exposure to PM-Bound PAHs and Carcinogenic Metals in Three Mid-Latitude Metropolitan Cities.Toxics202311869710.3390/toxics11080697 37624202
    [Google Scholar]
  75. OtansevP. BingöldağN. Indoor Radon Concentration and Excess Lifetime Cancer Risk.Radiat. Prot. Dosimetry20221981-2536110.1093/rpd/ncab191 35043176
    [Google Scholar]
  76. WetmoreJ.B. OtarolaL. PaulinoL.J. Estimating lifetime risk for breast cancer as a screening tool for identifying those who would benefit from additional services among women utilizing mobile mammography.J. Cancer Policy20223410035410.1016/j.jcpo.2022.100354 35995395
    [Google Scholar]
  77. FraserG.E. ShavlikD. Risk factors, lifetime risk, and age at onset of breast cancer.Ann. Epidemiol.19977637538210.1016/S1047‑2797(97)00042‑2 9279446
    [Google Scholar]
  78. BruderC. BulliardJ.L. GermannS. Estimating lifetime and 10-year risk of lung cancer.Prev. Med. Rep.20181112513010.1016/j.pmedr.2018.06.010 29942733
    [Google Scholar]
  79. RigelD.S. FriedmanR.J. KopfA.W. Lifetime risk for development of skin cancer in the U.S. population: Current estimate is now 1 in 5.J. Am. Acad. Dermatol.19963561012101310.1016/S0190‑9622(96)90139‑5 8959974
    [Google Scholar]
  80. AlharfiS. FureyN. Al-ShakhshirH. GhannoumM. CooperG.S. Fecal Microbiome Associated with Both Colon Adenomas and Lifetime Colorectal Cancer Risk.Dig. Dis. Sci.20236841492149910.1007/s10620‑022‑07673‑8 35986796
    [Google Scholar]
  81. GrundyA. SandhuS. ArseneauJ. Lifetime caffeine intake and the risk of epithelial ovarian cancer.Cancer Epidemiol.20227610205810.1016/j.canep.2021.102058 34800867
    [Google Scholar]
  82. DalmartelloM. VermuntJ. NegriE. LeviF. La VecchiaC. Adult lifetime body mass index trajectories and endometrial cancer risk.BJOG202212991521152910.1111/1471‑0528.17087 34962692
    [Google Scholar]
  83. LloydT. HounsomeL. MehayA. MeeS. VerneJ. CooperA. Lifetime risk of being diagnosed with, or dying from, prostate cancer by major ethnic group in England 2008–2010.BMC Med.201513117110.1186/s12916‑015‑0405‑5 26224061
    [Google Scholar]
  84. RoweT.W. KatzourouI.K. Stevenson-HoareJ.O. Bracher-SmithM.R. IvanovD.K. Escott-PriceV. Machine learning for the life-time risk prediction of Alzheimer’s disease: a systematic review.Brain Commun.202134fcab24610.1093/braincomms/fcab246 34805994
    [Google Scholar]
  85. SeshadriS. DrachmanD.A. LippaC.F. Apolipoprotein E epsilon 4 allele and the lifetime risk of Alzheimer’s disease. What physicians know, and what they should know.Arch. Neurol.199552111074107910.1001/archneur.1995.00540350068018 7487559
    [Google Scholar]
  86. LoboA. Lopez-AntonR. SantabárbaraJ. Incidence and lifetime risk of dementia and Alzheimer’s disease in a Southern European population.Acta Psychiatr. Scand.2011124537238310.1111/j.1600‑0447.2011.01754.x 21848704
    [Google Scholar]
  87. Oakley BrowneM.A. Elisabeth WellsJ. ScottK.M. McgeeM.A. Lifetime prevalence and projected lifetime risk of DSM-IV disorders in Te Rau Hinengaro: The New Zealand Mental Health Survey.Aust. N. Z. J. Psychiatry2006401086587410.1080/j.1440‑1614.2006.01905.x 16959012
    [Google Scholar]
  88. BonnewynA. BruffaertsR. VilagutG. AlmansaJ. DemyttenaereK. Lifetime risk and age-of-onset of mental disorders in the Belgian gen-eral population.Soc. Psychiatry Psychiatr. Epidemiol.200742752252910.1007/s00127‑007‑0191‑2 17473902
    [Google Scholar]
  89. CrowsonC.S. MattesonE.L. MyasoedovaE. The lifetime risk of adult-onset rheumatoid arthritis and other inflammatory autoimmune rheumatic diseases.Arthritis Rheum.201163363363910.1002/art.30155 21360492
    [Google Scholar]
  90. HessK.L. HuX. LanskyA. MerminJ. HallH.I. Lifetime risk of a diagnosis of HIV infection in the United States.Ann. Epidemiol.201727423824310.1016/j.annepidem.2017.02.003 28325538
    [Google Scholar]
  91. TuomilehtoJ. BahijriS. Lifetime risk of diabetes mellitus — how high?Nat. Rev. Endocrinol.201612312712810.1038/nrendo.2015.227 26729040
    [Google Scholar]
  92. NarayanK.M.V. BoyleJ.P. ThompsonT.J. SorensenS.W. WilliamsonD.F. Lifetime risk for diabetes mellitus in the United States.JAMA2003290141884189010.1001/jama.290.14.1884 14532317
    [Google Scholar]
  93. McMahonG.M. HwangS.J. FoxC.S. Residual lifetime risk of chronic kidney disease.Nephrol. Dial. Transplant.2017321017051709 27358274
    [Google Scholar]
  94. GaillardF. FournierC. LegendreC. Lifetime ESKD risk stratification for living kidney donor studies.Am. J. Transplant.20191992658265910.1111/ajt.15524 31278848
    [Google Scholar]
  95. WangZ. HoyW.E. Remaining lifetime risk for developing end stage renal disease among Australian Aboriginal people with diabetes.Diabetes Res. Clin. Pract.20141033e24e2610.1016/j.diabres.2013.12.048 24456995
    [Google Scholar]
  96. MeltonL.J.R.D. Lifetime risk of a hip fracture.Am. J. Public Health199080450050110.2105/AJPH.80.4.500 2316781
    [Google Scholar]
  97. WangY.X.J. GriffithJ.F. BlakeG.M. Revision of the 1994 World Health Organization T-score definition of osteoporosis for use in older East Asian women and men to reconcile it with their lifetime risk of fragility fracture.Skeletal Radiol.2023 37889317
    [Google Scholar]
  98. ChenV. NingH. AllenN. Lifetime Risks for Hypertension by Contemporary Guidelines in African American and White Men and Women.JAMA Cardiol.20194545545910.1001/jamacardio.2019.0529 30916719
    [Google Scholar]
  99. van RielA.C.M.J. BlokI.M. ZwindermanA.H. Lifetime Risk of Pulmonary Hypertension for All Patients After Shunt Closure.J. Am. Coll. Cardiol.20156691084108610.1016/j.jacc.2015.06.1318 26314539
    [Google Scholar]
  100. LigthartS. van HerptT.T.W. LeeningM.J.G. Lifetime risk of developing impaired glucose metabolism and eventual progression from prediabetes to type 2 diabetes: a prospective cohort study.Lancet Diabetes Endocrinol.201641445110.1016/S2213‑8587(15)00362‑9 26575606
    [Google Scholar]
  101. PencinaM.J. D’AgostinoR.B.Sr LarsonM.G. MassaroJ.M. VasanR.S. Predicting the 30-year risk of cardiovascular disease: the framingham heart study.Circulation2009119243078308410.1161/CIRCULATIONAHA.108.816694 19506114
    [Google Scholar]
  102. SaitoI. Lifetime Risk of Coronary Heart Disease in Japan.J. Atheroscler. Thromb.20212811210.5551/jat.ED131 32493882
    [Google Scholar]
  103. UrbutS.M. YeungM.W. KhurshidS. MSGene: Derivation and validation of a multistate model for lifetime risk of coronary artery disease using genetic risk and the electronic health record.medRxiv202310.1101/2023.11.08.23298229
    [Google Scholar]
  104. WangZ. HoyW.E. Lifetime risk of developing coronary heart disease in Aboriginal Australians: a cohort study.BMJ Open201331e00230810.1136/bmjopen‑2012‑002308 23370013
    [Google Scholar]
  105. ThomasE.A. EnduruN. TinA. Polygenic Risk, Midlife Life’s Simple 7, and Lifetime Risk of Stroke.J. Am. Heart Assoc.20221115e02570310.1161/JAHA.122.025703 35862192
    [Google Scholar]
  106. TurinT.C. KokuboY. MurakamiY. Lifetime risk of stroke in Japan.Stroke20104171552155410.1161/STROKEAHA.110.581363 20489172
    [Google Scholar]
  107. WangY. LiuJ. WangW. Lifetime risk of stroke in young-aged and middle-aged Chinese population.J. Hypertens.201634122434244010.1097/HJH.0000000000001084 27512963
    [Google Scholar]
  108. ZhaoH.L. HuangY. Lifetime Risk of Stroke in the Global Burden of Disease Study.N. Engl. J. Med.2019380141377137810.1056/NEJMc1900607 30943348
    [Google Scholar]
  109. BruggerN. KrauseR. CarlenF. Effect of lifetime endurance training on left atrial mechanical function and on the risk of atrial fibril-lation.Int. J. Cardiol.2014170341942510.1016/j.ijcard.2013.11.032 24342396
    [Google Scholar]
  110. GuoY. TianY. WangH. SiQ. WangY. LipG.Y.H. Prevalence, incidence, and lifetime risk of atrial fibrillation in China: new insights into the global burden of atrial fibrillation.Chest2015147110911910.1378/chest.14‑0321 24921459
    [Google Scholar]
  111. HeeringaJ. van der KuipD.A.M. HofmanA. Prevalence, incidence and lifetime risk of atrial fibrillation: the Rotterdam study.Eur. Heart J.200627894995310.1093/eurheartj/ehi825 16527828
    [Google Scholar]
  112. KheirbekR.E. FokarA. MooreH.J. SharaN. DoukkyR. FletcherR.D. Association between lifetime risk of atrial fibrillation and mortality in the oldest old.Clin. Cardiol.201841563463910.1002/clc.22941 29566272
    [Google Scholar]
  113. StaerkL. WangB. PreisS.R. Lifetime risk of atrial fibrillation according to optimal, borderline, or elevated levels of risk factors: cohort study based on longitudinal data from the Framingham Heart Study.BMJ2018361k145310.1136/bmj.k1453 29699974
    [Google Scholar]
  114. JaspersN.E.M. BlahaM.J. MatsushitaK. Prediction of individualized lifetime benefit from cholesterol lowering, blood pressure lower-ing, antithrombotic therapy, and smoking cessation in apparently healthy people.Eur. Heart J.202041111190119910.1093/eurheartj/ehz239 31102402
    [Google Scholar]
  115. ZipkinD.A. UmscheidC.A. KeatingN.L. Evidence-based risk communication: a systematic review.Ann. Intern. Med.2014161427028010.7326/M14‑0295 25133362
    [Google Scholar]
  116. PiersonC.A. Understanding and communicating risk.J. Am. Assoc. Nurse Pract.201527312310.1002/2327‑6924.12244 25739355
    [Google Scholar]
  117. HimesD.O. RootA.E. GammonA. LuthyK.E. Breast Cancer Risk Assessment: Calculating Lifetime Risk Using the Tyrer-Cuzick Model.J. Nurse Pract.201612958159210.1016/j.nurpra.2016.07.027
    [Google Scholar]
  118. GailM.H. CostantinoJ.P. PeeD. Projecting individualized absolute invasive breast cancer risk in African American women.J. Natl. Cancer Inst.200799231782179210.1093/jnci/djm223 18042936
    [Google Scholar]
  119. MatsunoR.K. CostantinoJ.P. ZieglerR.G. Projecting individualized absolute invasive breast cancer risk in Asian and Pacific Islander American women.J. Natl. Cancer Inst.20111031295196110.1093/jnci/djr154 21562243
    [Google Scholar]
  120. GailM.H. BrintonL.A. ByarD.P. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually.J. Natl. Cancer Inst.198981241879188610.1093/jnci/81.24.1879 2593165
    [Google Scholar]
  121. BanegasM.P. JohnE.M. SlatteryM.L. Projecting Individualized Absolute Invasive Breast Cancer Risk in US Hispanic Women.J. Natl. Cancer Inst.20171092djw21510.1093/jnci/djw215 28003316
    [Google Scholar]
  122. SaadatagahS. VarugheseM.G. NambiV. Coronary Artery Disease Risk Prediction in Young Adults: How Can We Overcome the Dominant Effect of Age?Curr. Atheroscler. Rep.202325625726510.1007/s11883‑023‑01106‑1 37195598
    [Google Scholar]
  123. StoneNJ RobinsonJG LichtensteinAH 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation201412925_suppl_2)(Suppl. 2S1S4510.1161/01.cir.0000437738.63853.7a24222016
    [Google Scholar]
  124. PiepoliM.F. HoesA.W. AgewallS. 2016 European Guidelines on cardiovascular disease prevention in clinical practice.Eur. Heart J.201637292315238110.1093/eurheartj/ehw106 27222591
    [Google Scholar]
  125. HagemanS.H.J. KaptogeS. de VriesT.I. Prediction of individual lifetime cardiovascular risk and potential treatment benefit: develop-ment and recalibration of the LIFE-CVD2 model to four European risk regions.Eur. J. Prev. Cardiol.202330181975198510.1093/eurjpc/zwae174 38752762
    [Google Scholar]
  126. LIFE-CVD: A new lifetime risk score model that estimates treatment benefit. J American College of Cardiology 2023Available from: https://www.acc.org/Latest-in-Cardiology/Articles/2019/06/24/14/13/LIFE-CVD-A-New-Lifetime-Risk-Score-Model-That-Estimates-Treatment-Benefit
  127. BrotonsC. MoralI. FernándezD. Estimation of Lifetime Risk of Cardiovascular Disease (IBERLIFERISK): A New Tool for Cardio-vascular Disease Prevention in Primary Care.Rev. Esp. Cardiol. (Engl. Ed.)201972756256810.1016/j.rec.2018.05.028 30097396
    [Google Scholar]
  128. BrotonsC. Moral-PeláezI. VicuñaJ. AmeixeirasC. Fernández-LavanderaC. Sánchez-ChaparroM.Á. Update and validation of the lifetime cardiovascular risk in Spain: IBERLIFERISK2. Clínica e Investigación en Arteriosclerosis (English Edition)202335311512210.1016/j.artere.2023.05.00836344347
    [Google Scholar]
  129. BrotonsC. Calvo-BonachoE. MoralI. Comparison of application of different methods to estimate lifetime cardiovascular risk.Eur. J. Prev. Cardiol.201623656457110.1177/2047487315579616 25827686
    [Google Scholar]
  130. DorresteijnJ.A.N. KaasenbroodL. CookN.R. How to translate clinical trial results into gain in healthy life expectancy for individual patients.BMJ2016352i1548
    [Google Scholar]
  131. BerryJ.D. DyerA. CaiX. Lifetime risks of cardiovascular disease.N. Engl. J. Med.2012366432132910.1056/NEJMoa1012848 22276822
    [Google Scholar]
  132. Hippisley-CoxJ CouplandC RobsonJ BrindleP Derivation, validation, and evaluation of a new QRISK model to estimate lifetime risk of cardiovascular disease: cohort study using QResearch database. BMJ2010341dec09 1c662410.1136/bmj.c662421148212
    [Google Scholar]
  133. Joint British Societies’ consensus recommendations for the prevention of cardiovascular disease (JBS3).Heart2014100Suppl. 2ii1ii6710.1136/heartjnl‑2014‑305693 24667225
    [Google Scholar]
  134. National Institute for Health and Care ExcellenceRecommendations | Cardiovascular disease: Risk assessment and reduction, including lipid modification | Guidance | NICE.2023Available from: https://www.nice.org.uk/guidance/ng238/chapter/Recommendations#identifying-and-assessing-cardiovascular-disease-risk-for-people-without-established-cardiovascular
    [Google Scholar]
  135. ClinRisk LtdQRISK3-lifetime.2023Available from: https://qrisk.org/lifetime/
    [Google Scholar]
  136. LivingstoneS. MoralesD.R. FleuriotJ. DonnanP.T. GuthrieB. External validation of the QLifetime cardiovascular risk prediction tool: population cohort study.BMC Cardiovasc. Disord.202323119410.1186/s12872‑023‑03209‑8 37061672
    [Google Scholar]
  137. de VriesT.I. JaspersN.E.M. VisserenF.L.J. DorresteijnJ.A.N. An update to the lifetime-perspective CardioVascular Disease (LIFE-CVD) model for prediction of individualized lifetime benefit from cardiovascular risk factor management in apparently healthy people.MedRxiv2021202125340010.1101/2021.03.15.21253400
    [Google Scholar]
  138. U-preventLIFE-CVD model.2023Available from: https://u-prevent.com/calculators/lifeCvd
    [Google Scholar]
  139. HagemanSHJ LuW KaptogeS Prediction of lifetime cardiovascular risk and individual lifetime treatment benefit in four European risk regions: geographic recalibration of the LIFE-CVD model. Eur Heart J202243: S2.ehac544.2276.10.1093/eurheartj/ehac544.2276
    [Google Scholar]
  140. Iberliferisk2023Available from: https://www.iberliferisk.com
  141. MarmaA.K. BerryJ.D. NingH. PersellS.D. Lloyd-JonesD.M. 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. Outcomes20103181410.1161/CIRCOUTCOMES.109.869727 20123666
    [Google Scholar]
  142. BerryJ.D. LiuK. FolsomA.R. 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.Circulation2009119338238910.1161/CIRCULATIONAHA.108.800235 19139385
    [Google Scholar]
  143. PaixaoA.R.M. AyersC.R. RohatgiA. Cardiovascular lifetime risk predicts incidence of coronary calcification in individuals with low short-term risk: the Dallas Heart Study.J. Am. Heart Assoc.201436e00128010.1161/JAHA.114.001280 25424574
    [Google Scholar]
  144. Lloyd-JonesD.M. DyerA.R. WangR. DaviglusM.L. GreenlandP. Risk factor burden in middle age and lifetime risks for cardiovascular and non-cardiovascular death (Chicago Heart Association Detection Project in Industry).Am. J. Cardiol.200799453554010.1016/j.amjcard.2006.09.099 17293199
    [Google Scholar]
  145. WangY. LiuJ. WangW. Lifetime risk for cardiovascular disease in a Chinese population: the Chinese Multi–Provincial Cohort Study.Eur. J. Prev. Cardiol.201522338038810.1177/2047487313516563 24336461
    [Google Scholar]
  146. WilkinsJ.T. NingH. BerryJ. ZhaoL. DyerA.R. Lloyd-JonesD.M. Lifetime risk and years lived free of total cardiovascular disease.JAMA2012308171795180110.1001/jama.2012.14312 23117780
    [Google Scholar]
  147. European Commission Cardiovascular diseases prevention | Knowledge for policy.2021Available from: https://knowledge4policy.ec.europa.eu/health-promotion-knowledge-gateway/cardiovascular-diseases-prevention_en
    [Google Scholar]
  148. World Health Organization Cardiovascular diseases (CVDs).Available from: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)
  149. HayıroğluM.İ. Telemedicine: Current Concepts and Future Perceptions.Anatol. J. Cardiol.201922Suppl. 2212210.14744/AnatolJCardiol.2019.12525 31670712
    [Google Scholar]
  150. TekkeşinA.İ. HayıroğluM.İ. ÇinierG. Lifestyle intervention using mobile technology and smart devices in patients with high cardio-vascular risk: A pragmatic randomised clinical trial.Atherosclerosis2021319212710.1016/j.atherosclerosis.2020.12.020 33465658
    [Google Scholar]
  151. HayıroğluM.İ. ÇınarT. ÇinierG. The effect of 1-year mean step count on the change in the atherosclerotic cardiovascular disease risk calculation in patients with high cardiovascular risk: a sub-study of the LIGHT randomized clinical trial.Kardiol. Pol.202179101140114210.33963/KP.a2021.0108 34506630
    [Google Scholar]
  152. MagnussenC. OjedaF.M. LeongD.P. Global effect of modifiable risk factors on cardiovascular disease and mortality.N. Engl. J. Med.2023389141273128510.1056/NEJMoa2206916 37632466
    [Google Scholar]
  153. KatsagoniC.N. PsarraG. GeorgoulisM. TambalisK. PanagiotakosD.B. SidossisL.S. High and moderate adherence to Mediterranean life-style is inversely associated with overweight, general and abdominal obesity in children and adolescents: The MediLIFE-index.Nutr. Res.202073384710.1016/j.nutres.2019.09.009 31841746
    [Google Scholar]
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