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Equalization of four cardiovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies.

Journal article
Authors Lisa Pennells
Stephen Kaptoge
Angela Wood
Mike Sweeting
Xiaohui Zhao
Ian White
Stephen Burgess
Peter Willeit
Thomas Bolton
Karel G M Moons
Yvonne T van der Schouw
Randi Selmer
Kay-Tee Khaw
Vilmundur Gudnason
Gerd Assmann
Philippe Amouyel
Veikko Salomaa
Mika Kivimaki
Børge G Nordestgaard
Michael J Blaha
Lewis H Kuller
Hermann Brenner
Richard F Gillum
Christa Meisinger
Ian Ford
Matthew W Knuiman
Annika Rosengren
Debbie A Lawlor
Henry Völzke
Cyrus Cooper
Alejandro Marín Ibañez
Edoardo Casiglia
Jussi Kauhanen
Jackie A Cooper
Beatriz Rodriguez
Johan Sundström
Elizabeth Barrett-Connor
Rachel Dankner
Paul J Nietert
Karina W Davidson
Robert B Wallace
Dan G Blazer
Cecilia Björkelund
Chiara Donfrancesco
Harlan M Krumholz
Aulikki Nissinen
Barry R Davis
Sean Coady
Peter H Whincup
Torben Jørgensen
Pierre Ducimetiere
Maurizio Trevisan
Gunnar Engström
Carlos J Crespo
Tom W Meade
Marjolein Visser
Daan Kromhout
Stefan Kiechl
Makoto Daimon
Jackie F Price
Agustin Gómez de la Cámara
J Wouter Jukema
Benoît Lamarche
Altan Onat
Leon A Simons
Maryam Kavousi
Yoav Ben-Shlomo
John Gallacher
Jacqueline M Dekker
Hisatomi Arima
Nawar Shara
Robert W Tipping
Ronan Roussel
Eric J Brunner
Wolfgang Koenig
Masaru Sakurai
Jelena Pavlovic
Ron T Gansevoort
Dorothea Nagel
Uri Goldbourt
Elizabeth L M Barr
Luigi Palmieri
Inger Njølstad
Shinichi Sato
W M Monique Verschuren
Cherian V Varghese
Ian Graham
Oyere Onuma
Philip Greenland
Mark Woodward
Majid Ezzati
Bruce M Psaty
Naveed Sattar
Rod Jackson
Paul M Ridker
Nancy R Cook
Ralph B D'Agostino
Simon G Thompson
John Danesh
Emanuele Di Angelantonio
Published in European heart journal
Volume 40
Issue 7
Pages 621-631
ISSN 1522-9645
Publication year 2019
Published at Institute of Medicine, School of Public Health and Community Medicine
Institute of Medicine, Department of Molecular and Clinical Medicine
Pages 621-631
Language en
Subject categories Clinical Medicine


There is debate about the optimum algorithm for cardiovascular disease (CVD) risk estimation. We conducted head-to-head comparisons of four algorithms recommended by primary prevention guidelines, before and after 'recalibration', a method that adapts risk algorithms to take account of differences in the risk characteristics of the populations being studied.Using individual-participant data on 360 737 participants without CVD at baseline in 86 prospective studies from 22 countries, we compared the Framingham risk score (FRS), Systematic COronary Risk Evaluation (SCORE), pooled cohort equations (PCE), and Reynolds risk score (RRS). We calculated measures of risk discrimination and calibration, and modelled clinical implications of initiating statin therapy in people judged to be at 'high' 10 year CVD risk. Original risk algorithms were recalibrated using the risk factor profile and CVD incidence of target populations. The four algorithms had similar risk discrimination. Before recalibration, FRS, SCORE, and PCE over-predicted CVD risk on average by 10%, 52%, and 41%, respectively, whereas RRS under-predicted by 10%. Original versions of algorithms classified 29-39% of individuals aged ≥40 years as high risk. By contrast, recalibration reduced this proportion to 22-24% for every algorithm. We estimated that to prevent one CVD event, it would be necessary to initiate statin therapy in 44-51 such individuals using original algorithms, in contrast to 37-39 individuals with recalibrated algorithms.Before recalibration, the clinical performance of four widely used CVD risk algorithms varied substantially. By contrast, simple recalibration nearly equalized their performance and improved modelled targeting of preventive action to clinical need.

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