Detail
Article
Online article
FT
Medvik - BMC
  • Something wrong with this record ?

Development and validation of two SCORE-based cardiovascular risk prediction models for Eastern Europe: a multicohort study

T. Tillmann, K. Läll, O. Dukes, G. Veronesi, H. Pikhart, A. Peasey, R. Kubinova, M. Kozela, A. Pajak, Y. Nikitin, S. Malyutina, A. Metspalu, T. Esko, K. Fischer, M. Kivimäki, M. Bobak

. 2020 ; 41 (35) : 3325-3333. [pub] 20200914

Language English Country Great Britain

Document type Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't

Grant support
MR/R024227/1 Medical Research Council - United Kingdom
106554/Z/14/Z Wellcome Trust - United Kingdom
064947/Z/01/Z Wellcome Trust - United Kingdom
R01 AG056477 NIA NIH HHS - United States

AIMS: Cardiovascular disease (CVD) risk prediction models are used in Western European countries, but less so in Eastern European countries where rates of CVD can be two to four times higher. We recalibrated the SCORE prediction model for three Eastern European countries and evaluated the impact of adding seven behavioural and psychosocial risk factors to the model. METHODS AND RESULTS: We developed and validated models using data from the prospective HAPIEE cohort study with 14 598 participants from Russia, Poland, and the Czech Republic (derivation cohort, median follow-up 7.2 years, 338 fatal CVD cases) and Estonian Biobank data with 4632 participants (validation cohort, median follow-up 8.3 years, 91 fatal CVD cases). The first model (recalibrated SCORE) used the same risk factors as in the SCORE model. The second model (HAPIEE SCORE) added education, employment, marital status, depression, body mass index, physical inactivity, and antihypertensive use. Discrimination of the original SCORE model (C-statistic 0.78 in the derivation and 0.83 in the validation cohorts) was improved in recalibrated SCORE (0.82 and 0.85) and HAPIEE SCORE (0.84 and 0.87) models. After dichotomizing risk at the clinically meaningful threshold of 5%, and when comparing the final HAPIEE SCORE model against the original SCORE model, the net reclassification improvement was 0.07 [95% confidence interval (CI) 0.02-0.11] in the derivation cohort and 0.14 (95% CI 0.04-0.25) in the validation cohort. CONCLUSION: Our recalibrated SCORE may be more appropriate than the conventional SCORE for some Eastern European populations. The addition of seven quick, non-invasive, and cheap predictors further improved prediction accuracy.

References provided by Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc21020127
003      
CZ-PrNML
005      
20210830101735.0
007      
ta
008      
210728s2020 xxk f 000 0|eng||
009      
AR
024    7_
$a 10.1093/eurheartj/ehaa571 $2 doi
035    __
$a (PubMed)33011775
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxk
100    1_
$a Tillmann, Taavi $u Department of Epidemiology & Public Health, University College London, 1-19 Torrington Place, London WC1E 7HB, UK $u Centre for Non-Communicable Disease, Institute for Global Health, University College London, 30 Guilford Street, London WC1N 1EH, UK
245    10
$a Development and validation of two SCORE-based cardiovascular risk prediction models for Eastern Europe: a multicohort study / $c T. Tillmann, K. Läll, O. Dukes, G. Veronesi, H. Pikhart, A. Peasey, R. Kubinova, M. Kozela, A. Pajak, Y. Nikitin, S. Malyutina, A. Metspalu, T. Esko, K. Fischer, M. Kivimäki, M. Bobak
520    9_
$a AIMS: Cardiovascular disease (CVD) risk prediction models are used in Western European countries, but less so in Eastern European countries where rates of CVD can be two to four times higher. We recalibrated the SCORE prediction model for three Eastern European countries and evaluated the impact of adding seven behavioural and psychosocial risk factors to the model. METHODS AND RESULTS: We developed and validated models using data from the prospective HAPIEE cohort study with 14 598 participants from Russia, Poland, and the Czech Republic (derivation cohort, median follow-up 7.2 years, 338 fatal CVD cases) and Estonian Biobank data with 4632 participants (validation cohort, median follow-up 8.3 years, 91 fatal CVD cases). The first model (recalibrated SCORE) used the same risk factors as in the SCORE model. The second model (HAPIEE SCORE) added education, employment, marital status, depression, body mass index, physical inactivity, and antihypertensive use. Discrimination of the original SCORE model (C-statistic 0.78 in the derivation and 0.83 in the validation cohorts) was improved in recalibrated SCORE (0.82 and 0.85) and HAPIEE SCORE (0.84 and 0.87) models. After dichotomizing risk at the clinically meaningful threshold of 5%, and when comparing the final HAPIEE SCORE model against the original SCORE model, the net reclassification improvement was 0.07 [95% confidence interval (CI) 0.02-0.11] in the derivation cohort and 0.14 (95% CI 0.04-0.25) in the validation cohort. CONCLUSION: Our recalibrated SCORE may be more appropriate than the conventional SCORE for some Eastern European populations. The addition of seven quick, non-invasive, and cheap predictors further improved prediction accuracy.
650    12
$a kardiovaskulární nemoci $x epidemiologie $7 D002318
650    _2
$a kohortové studie $7 D015331
650    _2
$a rizikové faktory kardiovaskulárních chorob $7 D000082742
650    _2
$a lidé $7 D006801
650    _2
$a prospektivní studie $7 D011446
650    _2
$a hodnocení rizik $7 D018570
650    _2
$a rizikové faktory $7 D012307
651    _2
$a Česká republika $7 D018153
651    _2
$a Polsko $7 D011044
651    _2
$a Rusko $7 D012426
655    _2
$a časopisecké články $7 D016428
655    _2
$a Research Support, N.I.H., Extramural $7 D052061
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a Läll, Kristi $u Estonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia
700    1_
$a Dukes, Oliver $u Department of Applied Mathematics Computer Science and Statistics, Ghent University, Krijgslaan 281, S9, 9000 Ghent, Belgium
700    1_
$a Veronesi, Giovanni $u Research Center in Epidemiology and Preventive Medicine, University of Insubria, Via O. Rossi 9, 21100 Varese, Italy
700    1_
$a Pikhart, Hynek $u Department of Epidemiology & Public Health, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
700    1_
$a Peasey, Anne $u Department of Epidemiology & Public Health, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
700    1_
$a Kubinova, Ruzena $u Centre for Environmental Health Monitoring, National Institute of Public Health, Šrobárova 48, 10042 Prague, Czech Republic
700    1_
$a Kozela, Magdalena $u Department of Epidemiology and Population Studies, Institute of Public Health, Jagiellonian University Medical College, ul. Grzegórzecka 20, 31531 Krakow, Poland
700    1_
$a Pajak, Andrzej $u Department of Epidemiology and Population Studies, Institute of Public Health, Jagiellonian University Medical College, ul. Grzegórzecka 20, 31531 Krakow, Poland
700    1_
$a Nikitin, Yuri $u Research Institute of Internal and Preventive Medicine, Branch of the Institute of Cytology and Genetics, SB RAS, 10 Ac. Lavrentieva ave, 630090 Novosibirsk, Russia
700    1_
$a Malyutina, Sofia $u Research Institute of Internal and Preventive Medicine, Branch of the Institute of Cytology and Genetics, SB RAS, 10 Ac. Lavrentieva ave, 630090 Novosibirsk, Russia $u Novosibirsk State Medical University, Krasny Prospect 52, 630091 Novosibirsk, Russia
700    1_
$a Metspalu, Andres $u Estonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia $u Institute of Cell and Molecular Biology, University of Tartu, Riia 23b, 51010 Tartu, Estonia
700    1_
$a Esko, Tõnu $u Estonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia
700    1_
$a Fischer, Krista $u Estonian Genome Center, Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia $u Institute of Mathematics and Statistics, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia
700    1_
$a Kivimäki, Mika $u Department of Epidemiology & Public Health, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
700    1_
$a Bobak, Martin $u Department of Epidemiology & Public Health, University College London, 1-19 Torrington Place, London WC1E 7HB, UK
773    0_
$w MED00009622 $t European heart journal $x 1522-9645 $g Roč. 41, č. 35 (2020), s. 3325-3333
856    41
$u https://pubmed.ncbi.nlm.nih.gov/33011775 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y p $z 0
990    __
$a 20210728 $b ABA008
991    __
$a 20210830101735 $b ABA008
999    __
$a ok $b bmc $g 1690836 $s 1140573
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2020 $b 41 $c 35 $d 3325-3333 $e 20200914 $i 1522-9645 $m European heart journal $n Eur Heart J $x MED00009622
GRA    __
$a MR/R024227/1 $p Medical Research Council $2 United Kingdom
GRA    __
$a 106554/Z/14/Z $p Wellcome Trust $2 United Kingdom
GRA    __
$a 064947/Z/01/Z $p Wellcome Trust $2 United Kingdom
GRA    __
$a R01 AG056477 $p NIA NIH HHS $2 United States
LZP    __
$a Pubmed-20210728

Find record

Citation metrics

Loading data ...

Archiving options

Loading data ...