SCORE
| Background info: SCORE |
Two types of SCORE risk charts:
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1) End-points measured
- 10 year risk of cardiovascular mortality (ICD-9 codes 401 to 414, 426 to 443, except ICD-9 codes for 426.7, 429, 430.0, 432.1, 437.3, 437.4 and 437.5 which are non-atherosclerotic causes of death)
- Include classification of 789.1 (instantaneous death) and 789.2 (death within 24 h of symptom onset)
2) Profile of original population at baseline
- 12 European cohort studies from Finland, Russia, Norway, UK (Scotland and British), Denmark, Sweden, Belgium, Germany, Italy, France and Spain
- Participant number: 205 178 (88 080 women and 117 098 men)
- Use of non selected population vs. trial population
- Number of participants
3) Validation (the following prospective studies excludes cohort with history of CVD and diabetes at baseline)
| Author | Year | Ethnicity | Age group | Follow up | Calibration ^ | Discrimination ^^ | Conclusion |
|---|---|---|---|---|---|---|---|
| Aktas (1) | 2004 | US (Cleveland clinic) | 50-75 | 8 years | 0.73 | SCORE was superior to Framingham-ATPIII | |
| Aspelund (2) | 2007 | Iceland | 10 years | Relative risk in Iceland was comparable with low-risk version of SCORE | |||
| Barroso (3) | 2010 | Spain | 40-65 | 10 years | 1.4 | 0.86 | Framingham-Wilson over-predict risk by 64% while SCORE over-predict by 40%. SCORE performed better for discrimination and calibration. |
| Bhopal (4) | 2005 | South Asian, UK | 25-74 | 9.6 years (European), 7.1 years (South Asian) | Unlike Framingham-Anderson, SCORE did not follow expected observed patterns | ||
| Buitrago (5) | 2006 | Spainish | 40-65 | 10 years | 1.4 | ||
| Chen (6) | 2009 | Australia | 40-74 | AusSCORE is superior than both SCORE and Framingham-unknown | |||
| Coin (7) | 2006 | Spain (hypertensive cohort) | 1 year | ||||
| Comin (8) | 2007 | Spain | 35-74 | 5 years | More than half of coronary events occur in patients not classified as high risk. Sensitivity of all algorithms is low. | ||
| De Bacquer (10) | 2010 | Belgium | 10 years | 1.04 | 0.86 (0.82 men, 0.88 women) | SCORE-Belgium risk chart proves to be accurate and precise estimation tool | |
| Donfrancesco (11) | 2010 | Italy | 35-69 | 10 years | SCORE reflects Italian cardiovascular mortality quite well | ||
| Goh (12) | 2014 | Australian adult women | 20-69 | 10 years | Hosmer-Lemeshow chi sq: SCORE-low (6.09), SCORE-high (12.06) | SCORE-low: 0.877 (0.827-0.927) SCORE-high:0.877 (0.827-0.927) | Both Framingham risk score model and SCORE risk chart for low-risk regions are recommended for use in Australian women population for predicting 10-year CVD mortality risk. |
| Hense (13) | 2008 | Germany | 40-65 | Overestimation of risk with original SCORE model is reduced with SCORE-Germany. | |||
| Jdanov (14) | 2014 | Russian | 45-64 | 10 year | 2.3 (45-49 yr old) 2.2 (50-54 yr old) 1.4 (55-64 yr old) | Using non-calibrated scoring models for Russian may lead to substantial underestimation of cardiovascular mortality risk in some groups of individuals. | |
| Jorstad (15) | 2015 | UK (EPIC-Norfolk) | 39-79 | 10 years | Predicted SCORE-high: 2.85%, Predicted SCORE-low: 1.55% Observed mortality: 1.25% | SCORE-low: 0.78 SCORE-high: 0.78 | SCORE low-risk algorithm performed better than the high-risk algorithm in predicting 10year CVD mortality. UK should be classified as a low risk country. |
| Lindman (16) | 2007 | Norway | 40-69 | SCORE high risk overestimate number of CVD deaths, low risk predict reasonably well for men but overestimate for women | |||
| Lindman (17) | 2006 | Norway | For men, high risk function overestimated and low risk function underestimated. For women, both function underestimated mortality. | ||||
| Marchant (18) | 2009 | French | SCORE provides a better estimation than Framingham | ||||
| Merry (19) | 2012 | Dutch (Maastricht) | 20-59 | max 16.9 years | 1.06 | 0.799 | Re-estimated SCORE function with total and HDL cholesterol levels instead of the cholesterol ratio can be used for the risk prediction of CHD incidence |
| Sehestedt (20) | 2009 | Danish (higher than optimal blood pressure) | 41, 51, 61, 71 | 12.8 years | Both SCORE and European Society of Hypertension risk chart recommended antihypertensive treatment to almost the same patients. | ||
| Uthoff (21) | 2010 | Switzerland (clinically overt atherosclerosis) | 6 years | 0.6 | Framingham-Wilson and SCORE seem to be barely useful in secondary prevention setting | ||
| Van der Heijden (22) | 2009 | Dutch Caucasian | 50-75 | 10 years | 0.82 | SCORE was the better predictor of fatal CHD events compared to Framingham-Wilson | |
| Van Dis (23) | 2010 | Dutch | 37.5-62.5 | 10 years | 0.82 | SCORE-low predicts the number of CVD deaths well in Dutch population | |
| Versteylen (24) | 2011 | Netherlands (cohort with stable chest pain) | 19+-9 months | >1.0 | 0.72 | Framingham-D'Agostino and SCORE prediction for coronary artery disease was similar | |
| Vikhireva (25) | 2014 | Czech republic, Poland, Lithuania, Russia (MONICA) | 35-64 | 10 year | MONICA men: Czech: 1.05 Poland (Warsaw): 0.87 Poland (Tarnobrzeg): 1.11 Lithuania: 1.43 Russia: 0.76 MONICA women: Czech: 0.96 Poland (Warsaw): 1.08 Poland (Tarnobrzeg): 1.29 Lithuania: 1.01 Russia: 0.52 | MONICA men: Czech: 0.69 Poland (Warsaw): 0.67 Poland (Tarnobrzeg): 0.63 Lithuania: 0.67 Russia: 0.62 MONICA women: Czech: 0.64 Poland (Warsaw): 0.54 Poland (Tarnobrzeg): 0.59 Lithuania: 0.61 Russia: 0.64 | High-risk SCORE underestimated the fatal CVD risk in Russian MONICA but performed well in most MONICA samples. This SCORE version might overestimate the risk in contemporary Czech and Polish populations. |
Note:
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4) Length of follow up
- 95th centile of follow up for each cohort at least 10 years or more
- Total of 2.7 million person years of follow up
5) Risk factors involved
- Non-modifiable risk factors
- Gender
- Age
- Modifiable risk factors
- Smoking status
- Systolic blood pressure
- Total cholesterol
References
Primary publication:
Conroy RM, Pyörälä K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. Eur Heart J 2003;24:987-1003. http://eurheartj.oxfordjournals.org/content/24/11/987.abstract
1. Aktas MK, Ozduran V, Pothier CE, et al. Global risk scores and exercise testing for predicting all-cause mortality in a preventive medicine program. JAMA. 2004;292(12):1462-1468.
2. Aspelund T, Thorgeirsson G, Sigurdsson G, Gudnason V. Estimation of 10-year risk of fatal cardiovascular disease and coronary heart disease in Iceland with results comparable with those of the Systematic Coronary Risk Evaluation project. European Journal of Cardiovascular Prevention and Rehabilitation. 2007;14(6):761-768.
3. Barroso LC, Muro EC, Herrera ND, et al. Performance of the Framingham and SCORE cardiovascular risk prediction functions in a non-diabetic population of a Spanish health care centre: a validation study. Scandinavian Journal of Primary Health Care. 2010;28(4):242-248.
4. Bhopal R, Fischbacher C, Vartiainen E, Unwin N, White M, Alberti G. Predicted and observed cardiovascular disease in South Asians: Application of FINRISK, Framingham and SCORE models to Newcastle Heart Project data. Journal of Public Health. 2005;27(1):93-100.
5. Buitrago Ramirez F, Canon Barroso L, Diaz Herrera N, Cruces Muro E, Bravo Simon B, Perez Sanchez I. Comparison of the SCORE function chart and the Framingham-REGICOR equation to estimate the cardiovascular risk in an urban population after 10 years of follow-up. Medicina Clinica. 2006;127(10):368-373.
6. Chen L, Tonkin AM, Moon L, et al. Recalibration and validation of the SCORE risk chart in the Australian population: The AusSCORE chart. European Journal of Cardiovascular Prevention and Rehabilitation. 2009;16(5):562-570.
7. Coin Aguilar J, Hernandiz Martinez A, Rodriguez Padial L, et al. Assessment of cardiovascular risk in population groups. Comparison of Score system and Framingham in hypertensive patients. Revista Clinica Espanola. 2006;206(4):182-187.
8. Comin E, Solanas P, Cabezas C, et al. Estimating cardiovascular risk in Spain using different algorithms. Revista Espanola de Cardiologia. 2007;60(7):693-702.
9. Conroy RM, Pyorala K, Fitzgerald AP, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: The SCORE project. European Heart Journal. 2003;24(11):987-1003.
10. De Bacquer D, De Backer G. Predictive ability of the SCORE Belgium risk chart for cardiovascular mortality. International Journal of Cardiology. 2010;143(3):385-390.
11. Donfrancesco C, Palmieri L, Cooney MT, et al. Italian cardiovascular mortality charts of the CUORE project: Are they comparable with the SCORE charts? European Journal of Cardiovascular Prevention and Rehabilitation. August 2010;17(4):403-409.
12. Goh LGH, Welborn TA, Dhaliwal SS. Independent external validation of cardiovascular disease mortality in women utilising Framingham and SCORE risk models: a mortality follow-up study. BMC Women’s Health. 2014;14:118.
13. Hense H-W, Koesters E, Wellmann J, Meisinger C, et al. Evaluation of a recalibrated Systematic Coronary Risk Evaluation cardiovascular risk chart: results from Systematic Coronary Risk Evaluation Germany. European Journal of Cardiovascular Prevention & Rehabilitation. 2008;15(4):409-415.
14. Jdanov DA, Deev AD, Jasilionis D, et al. Recalibration of the SCORE risk chart for the Russian population. European Journal of Epidemiology. 2014;29(9):621-628.
15. Jorstad HT, Colkesen EB, Minneboo M, et al. The Systematic Coronary Risk Evaluation (SCORE) in a large UK population: 10 year follow up in the EPIC-Norfolk prospective population study. European Journal of Preventive Cardiology. 2015;22(1):119-126.
16. Lindman AS, Selmer R, Tverdal A, et al. The SCORE risk model applied to recent population surveys in Norway compared to observed mortality in the general population. European Journal of Cardiovascular Prevention and Rehabilitation. 2006;13(5):731-737.
17. Lindman AS, Veierod MB, Pedersen JI, et al. The ability of the SCORE high-risk model to predict 10-year cardiovascular disease mortality in Norway. European Journal of Cardiovascular Prevention and Rehabilitation. 2007;14(4):501-507.
18. Marchant I, Boissel JP, Kassai B, et al. SCORE should be preferred to Framingham to predict cardiovascular death in French population. European Journal of Cardiovascular Prevention and Rehabilitation. 2009;16(5):609-615.
19. Merry AHH, Boer JMA, Schouten LJ, et al. Risk prediction of incident coronary heart disease in the Netherlands: re-estimation and improvement of the SCORE risk function. European Journal of Preventive Cardiology. 2011;19(4):840-848.
20. Sehestedt T, Jeppesen J, Hansen TW, et al. Risk stratification with the risk chart from the European Society of Hypertension compared with SCORE in the general population. Journal of Hypertension. 2009;27(12):2351-2357.
21. Uthoff H, Staub D, Socrates T, et al. PROCAM-, FRAMINGHAM-, SCORE- and SMART-risk score for predicting cardiovascular morbidity and mortality in patients with overt atherosclerosis. Vasa. 2010;39(4):325-333.
22. van der Heijden AAWA, Ortegon MM, Niessen LW, et al. Prediction of coronary heart disease risk in a general, pre-diabetic, and diabetic population during 10 years of follow-up: accuracy of the Framingham, SCORE, and UKPDS risk functions: The Hoorn Study. Diabetes Care. 2009;32(11):2094-2098.
23. van Dis I, Kromhout D, Geleijnse JM, et al. Evaluation of cardiovascular risk predicted by different SCORE equations: the Netherlands as an example. European Journal of Cardiovascular Prevention & Rehabilitation. 2010;17(2):244-249.
24. Versteylen MO, Joosen IA, Shaw LJ, et al. Comparison of Framingham, PROCAM, SCORE, and Diamond Forrester to predict coronary atherosclerosis and cardiovascular events. Journal of Nuclear Cardiology. 2011;18(5):904-911.
25. Vikhireva O, Pajak A, Broda G, et al. SCORE performance in Central and Eastern Europe and former Soviet Union: MONICA and HAPIEE results. European Heart Journal. 2014;35:571-577.