Assessment of diet quality improves the classification ability of cardiovascular risk score in predicting future events: The 10-year follow-up of the ATTICA study (2002-2012)

European Journal of Preventive Cardiology

Volumn 22, Issue 11, 2015, Pages 1488-1498

  Georgousopoulou, Ekavi N ^a   Panagiotakos, Demosthenes B ^a   Pitsavos, Christos ^b   Stefanadis, Christodoulos ^b  

^a HAROKOPIO UNIVERSITY   (Greece)

^b UNIVERSITY OF ATHENS MEDICAL SCHOOL   (Greece)

Author keywords

CVD risk; diet; discrimination; epidemiology; estimation; prediction

Indexed keywords

C REACTIVE PROTEIN; CHOLESTEROL; GLUCOSE; INTERLEUKIN 6; BIOLOGICAL MARKER;

ACUTE CORONARY SYNDROME; ADULT; AGED; CARDIOVASCULAR DISEASE; CARDIOVASCULAR RISK; CLINICAL CLASSIFICATION; CLINICAL EVALUATION; CONTROLLED STUDY; DIASTOLIC BLOOD PRESSURE; FEMALE; FOLLOW UP; FUTUROLOGY; HUMAN; MAJOR CLINICAL STUDY; MALE; MEDITERRANEAN DIET; NUTRITIONAL ASSESSMENT; NUTRITIONAL VALUE; PREDICTION; PRIORITY JOURNAL; REVIEW; SYSTOLIC BLOOD PRESSURE; ADOLESCENT; ADVERSE EFFECTS; AGE; BLOOD; BLOOD PRESSURE; CARDIOVASCULAR DISEASES; COMPLICATION; DECISION SUPPORT SYSTEM; DYSLIPIDEMIA; GREECE; HEALTH STATUS; HYPERTENSION; INCIDENCE; MIDDLE AGED; NUTRITIONAL STATUS; PATHOPHYSIOLOGY; RISK ASSESSMENT; RISK FACTOR; RISK REDUCTION; SEX DIFFERENCE; SMOKING; TIME FACTOR; VERY ELDERLY; YOUNG ADULT;

ADOLESCENT; ADULT; AGE FACTORS; AGED; AGED, 80 AND OVER; BIOMARKERS; BLOOD PRESSURE; CARDIOVASCULAR DISEASES; CHOLESTEROL; DECISION SUPPORT TECHNIQUES; DIET, MEDITERRANEAN; DYSLIPIDEMIAS; FEMALE; FOLLOW-UP STUDIES; GREECE; HEALTH STATUS; HUMANS; HYPERTENSION; INCIDENCE; MALE; MIDDLE AGED; NUTRITION ASSESSMENT; NUTRITIONAL STATUS; RISK ASSESSMENT; RISK FACTORS; RISK REDUCTION BEHAVIOR; SEX FACTORS; SMOKING; TIME FACTORS; YOUNG ADULT;

EID: 84944223224     PISSN: 20474873     EISSN: 20474881     Source Type: Journal    
DOI: 10.1177/2047487314555095     Document Type: Review

References (48)

1. Araújo F, Gouvinhas C, Fontes F, et al. Trends in cardiovascular diseases and cancer mortality in 45 countries from five continents (1980-2010). Eur J Prev Cardiol 2013; 21: 1004-1017.
2. Petersen S, Peto V, Rayner M, et al. European Cardiovascular Disease Statistics: 2005 edition.
3. Perk J, De Backer G, Gohlke H, et al. European guidelines on cardiovascular disease prevention in clinical practice (version 2012). Eur Heart J 2012; 33: 1635-1701.
4. Kannel WB, McGee D, Gordon T,. A general cardiovascular risk profile: The Framingham Study. Am J Cardiol 1976; 38: 46-51.
5. Panagiotakos D,. Health measurement scales: Methodological issues. Open Cardiovasc Med J 2009; 3: 160-165.
6. Pyorala K,. Assessment of coronary heart disease risk in populations with different levels of risk. Eur Heart J 2000; 21: 348-350.
7. Conroy RM, Pyörälä K, Fitzgerald AP, et al. SCORE project group. Estimation of ten-year risk of fatal cardiovascular disease in Europe: The SCORE project. Eur Heart J 2003; 24: 987-1003.
8. Graham IM,. The importance of total cardiovascular risk assessment in clinical practice. Eur J Gen Pract 2006; 12: 148-155.
9. Panagiotakos DB, Fitzgerald AP, Pitsavos C, et al. Statistical modelling of 10-year fatal cardiovascular disease risk in Greece: The HellenicSCORE (a calibration of the ESC SCORE project). Hellenic J Cardiol 2007; 48: 55-63.
10. Sans S, Fitzgerald AP, Royo D, et al. Calibrating the SCORE cardiovascular risk chart for use in Spain. Rev Esp Cardiol 2007; 60: 476-485.
11. World Health Organization (WHO). Cardiovascular diseases (CVDs), Fact sheet no. 317, http://www.who.int/mediacentre/factsheets/fs317/en/index.html (accessed 21 April 2012).
12. Hinai A, Keltai M, Yusuf S,. INTERHEART Study Investigators. Dietary patterns and the risk of acute myocardial infarction in 52 countries: Results of the INTERHEART study. Circulation 2008; 118: 1929-1937.
13. Georgousopoulou EN, Pitsavos C, Yannakoulia M, et al. The role of dietary patterns' assessment in the predictive ability of cardiovascular disease risk estimation models: A review. Int J Food Sci Nutr 2014; 65: 3-8.
14. Cooney MT, Dudina AL, Graham IM,. Value and limitations of existing scores for the assessment of cardiovascular risk: A review for clinicians. J Am Coll Cardiol 2009; 54: 1209-1227.
15. Graham IM,. The importance of total cardiovascular risk assessment in clinical practice. Eur J Gen Pract 2006; 12: 148-155.
16. Panagiotakos DB, Pitsavos C, Stefanadis C,. Dietary patterns: a Mediterranean diet score and its relation to clinical and biological markers of cardiovascular risk. Nutr Metab Cardiovasc Dis 2006; 16: 559-568.
17. Bountziouka V, Tzavelas G, Polychronopoulos E, et al. Validity of dietary patterns derived in nutrition surveys using a priori and a posteriori multivariate statistical methods. Int J Food Sci Nutr 2011; 62: 617-627.
18. Kastorini CM, Papadakis G, Milionis HJ, et al. Comparative analysis of a-priori and a-posteriori dietary patterns using state-of-the-art classification algorithms: A case/case-control study. Artif Intell Med 2013; 59: 175-183.
19. Bountziouka V, Constantinidis TC, Polychronopoulos E, et al. Short-term stability of dietary patterns defined a priori or a posterior. Maturitas 2011; 68: 272-278.
20. Panagiotakos D, Kalogeropoulos N, Pitsavos C, et al. Validation of the MedDietScore via the determination of plasma fatty acids. Int J Food Sci Nutr 2009; 60: 168-180.
21. Panagiotakos DB, Pitsavos C, Stefanadis C,. Alpha-priori and alpha-posterior dietary pattern analyses have similar estimating and discriminating ability in predicting 5-Y incidence of cardiovascular disease: Methodological issues in nutrition assessment. Food Sci 2009; 74: H218-H224.
22. World Health Organization. Mortality data statistics, http://www3.who.int/whosis/mort/table1.cfm?path=whosis,mort,mort-table1&language=english (accessed 10 February 2006).
23. D'Agostino RB Sr, Grundy S, Sullivan LM, et al.CDH Risk Prediction Group,. Validation of the Framingham coronary heart disease prediction scores: Results of a multiple ethnic group's investigation. JAMA 2001; 286: 180-187.
24. Cox DR and Oakes D. Analysis of survival data-monographs on statistics and applied probability. Chapman and Hall, London, UK, 1998.
25. Pitsavos C, Panagiotakos DB, Chrysohoou C, et al. Epidemiology of cardiovascular risk factors in Greece: Aims, design and baseline characteristics of the ATTICA study. BMC Public Health 2003; 3: 32-32.
26. Cook N,. Use and misuse of the Receiver Operating Characteristic Curve in risk prediction. Circulation 2007; 115: 928-935.
27. Harrell FE Jr, Lee KL, Mark DB,. Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15: 361-387.
28. Newson RB,. Comparing the predictive powers of survival models using Harrell's C or Somers' D. The Stata Journal 2010; 10: 339-358.
29. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, et al. Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond. Stat Med 2008; 27: 157-172.
30. Pencina MJ, D'Agostino RB Sr, Steyerberg EW,. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011; 30: 11-21.
31. Vickers AJ, Cronin AM, Elkin EB, et al. Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers. BMC Med Inform Decis Mak 2008; 8: 53-53.
32. Graham I, Atar D, Borch-Johnsen K, et al. European Society of Cardiology (ESC); European Association for Cardiovascular Prevention and Rehabilitation (EACPR); Council on Cardiovascular Nursing; European Association for Study of Diabetes (EASD); International Diabetes Federation Europe (IDF-Europe); European Stroke Initiative (EUSI); Society of Behavioural Medicine (ISBM); European Society of Hypertension (ESH); WONCA Europe (European Society of General Practice/Family Medicine); European Heart Network (EHN); European Atherosclerosis Society (EAS). European guidelines on cardiovascular disease prevention in clinical practice: full text. Fourth Joint Task Force of the European Society of Cardiology and other societies on cardiovascular disease prevention in clinical practice constituted by representatives of nine societies and by invited experts). Eur J Cardiovasc Prev Rehabil 2007; 14: S1-113.
33. Panagiotakos DB, Stavrinos V,. Methodological issues in cardiovascular epidemiology: The risk of determining absolute risk through statistical models. Vasc Health Risk Manag 2006; 2: 309-315.
34. Pettilä V,. Predicting risk of death from cardiovascular disease. Outcome prediction is hampered by methodological problems. BMJ 2001; 323: 1000-1000.
35. Katz M, Laurinavicius AG, Franco FG, et al. Calculated and perceived cardiovascular risk in asymptomatic subjects submitted to a routine medical evaluation: The perception gap∗. Eur J Prev Cardiol. Epub ahead of print 18 July 2014. pii: 2047487314543074.
36. Pitsavos C, Panagiotakos DB, Chrysohoou C, et al. The benefits from Mediterranean diet on the risk of developing acute coronary syndromes, in hypercholesterolemic subjects: A case-control study (CARDIO2000). Coron Artery Dis 2002; 13: 295-300.
37. Trichopoulou A, Costacou T, Bamia C, et al. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med 2003; 348: 2599-2608.
38. Martinez-Gonzalez MA, Fernandez-Jarne E, Serrano-Martinez M,. Mediterranean diet and reduction in the risk of a first acute myocardial infarction: An operational healthy dietary score. Eur J Nutr 2002; 41: 153-160.
39. Panagiotakos DB, Pitsavos C, Stefanadis C,. Inclusion of dietary evaluation in cardiovascular disease risk prediction models increases accuracy and reduces bias of the estimations. Risk Anal 2009; 29: 176-186.
40. Baik I, Cho NH, Kim SH, et al. Dietary information improves cardiovascular disease risk prediction risk prediction models. Eur J Clin Nutr 2013; 67: 25-30.
41. Woo J, Chumlea WC, Sun SS, et al. Development of the Chinese nutrition screen (CNS) for use in institutional settings. J Nutr Health Aging 2005; 9: 203-210.
42. Panagiotakos DB, Milias GA, Pitsavos C, et al. MedDietScore: a computer program that evaluates the adherence to the Mediterranean dietary pattern and its relation to cardiovascular disease risk. Comput Methods Programs Biomed 2006; 83: 73-77.
43. Bach A, Serra-Majem L, Carrasco JL, et al. The use of indexes evaluating the adherence to the Mediterranean diet in epidemiological studies: A review. Public Health Nutr 2006; 9: 132-146.
44. Cushman M, Arnold AM, Psaty BM, et al. C-reactive protein and the 10-year incidence of coronary heart disease in older men and women: The cardiovascular health study. Circulation 2005; 112: 25-31.
45. Chrysohoou C, Panagiotakos DB, Pitsavos C, et al. Adherence to the Mediterranean diet attenuates inflammation and coagulation process in healthy adults: The ATTICA study. J Am Coll Cardiol 2004; 44: 152-158.
46. Marrugat J, D'Agostino R, Sullivan L,. An adaptation of the Framingham coronary heart disease risk function to European Mediterranean areas. J Epidemiol Commun Health 2003; 57: 634-638.
47. Brindle P, Emberson J, Lampe F,. Predictive accuracy of the Framingham coronary risk score in British men: Prospective cohort. BMJ 2003; 327: 1227-1233.
48. Thomsen TF, McGee D, Davidsen M,. A cross-validation of risk-scores for coronary heart disease mortality based on data from the Glostrup Population Studies and Framingham Heart Study. Int J Epidemiol 2002; 31: 817-822.