Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review

Background and objective This review compares non-laboratory-based and laboratory-based cardiovascular disease (CVD) risk prediction equations in populations targeted for primary prevention.Design Systematic review.Methods We searched five databases until 12 March 2024 and used prediction study risk...

Full description

Saved in:
Bibliographic Details
Main Authors: Yihun Mulugeta Alemu, Sisay Mulugeta Alemu, Dan Chateau, Nasser Bagheri, Kinley Wangdi
Format: Article
Language:English
Published: BMJ Publishing Group 2025-02-01
Series:Open Heart
Online Access:https://openheart.bmj.com/content/12/1/e003147.full
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1823859043373940736
author Yihun Mulugeta Alemu
Sisay Mulugeta Alemu
Dan Chateau
Nasser Bagheri
Kinley Wangdi
author_facet Yihun Mulugeta Alemu
Sisay Mulugeta Alemu
Dan Chateau
Nasser Bagheri
Kinley Wangdi
author_sort Yihun Mulugeta Alemu
collection DOAJ
description Background and objective This review compares non-laboratory-based and laboratory-based cardiovascular disease (CVD) risk prediction equations in populations targeted for primary prevention.Design Systematic review.Methods We searched five databases until 12 March 2024 and used prediction study risk of bias assessment tool to assess bias. Data on hazard ratios (HRs), discrimination (paired c-statistics) and calibration were extracted. Differences in c-statistics and HRs were analysed. Protocol: PROSPERO (CRD42021291936).Results Nine studies (1 238 562 participants, 46 cohorts) identified six unique CVD risk equations. Laboratory predictors (eg, cholesterol and diabetes) had strong HRs, while body mass index in non-laboratory models showed limited effect. Median c-statistics were 0.74 for both models (IQR: lab 0.77–0.72; non-lab 0.76–0.70), with a median absolute difference of 0.01. Calibration measures between laboratory-based and non-laboratory-based equations were similar, although non-calibrated equations often overestimated risk.Conclusion The discrimination and calibration measures between laboratory-based and non-laboratory-based models show minimal differences, demonstrating the insensitivity of c-statistics and calibration metrics to the inclusion of additional predictors. However, in most reviewed studies, the HRs for these additional predictors were substantial, significantly altering predicted risk, particularly for individuals with higher or lower levels of these predictors compared with the average.
format Article
id doaj-art-57592376cfe1453090fefa5974fe8a36
institution Kabale University
issn 2053-3624
language English
publishDate 2025-02-01
publisher BMJ Publishing Group
record_format Article
series Open Heart
spelling doaj-art-57592376cfe1453090fefa5974fe8a362025-02-11T09:20:10ZengBMJ Publishing GroupOpen Heart2053-36242025-02-0112110.1136/openhrt-2024-003147Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic reviewYihun Mulugeta Alemu0Sisay Mulugeta Alemu1Dan Chateau2Nasser Bagheri3Kinley Wangdi4National Centre for Epidemiology and Population Health, College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, AustraliaDepartment of Health Science, University of Groningen, Groningen, The NetherlandsNational Centre for Epidemiology and Population Health, College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, AustraliaNational Centre for Epidemiology and Population Health, College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, AustraliaNational Centre for Epidemiology and Population Health, College of Health and Medicine, Australian National University, Canberra, Australian Capital Territory, AustraliaBackground and objective This review compares non-laboratory-based and laboratory-based cardiovascular disease (CVD) risk prediction equations in populations targeted for primary prevention.Design Systematic review.Methods We searched five databases until 12 March 2024 and used prediction study risk of bias assessment tool to assess bias. Data on hazard ratios (HRs), discrimination (paired c-statistics) and calibration were extracted. Differences in c-statistics and HRs were analysed. Protocol: PROSPERO (CRD42021291936).Results Nine studies (1 238 562 participants, 46 cohorts) identified six unique CVD risk equations. Laboratory predictors (eg, cholesterol and diabetes) had strong HRs, while body mass index in non-laboratory models showed limited effect. Median c-statistics were 0.74 for both models (IQR: lab 0.77–0.72; non-lab 0.76–0.70), with a median absolute difference of 0.01. Calibration measures between laboratory-based and non-laboratory-based equations were similar, although non-calibrated equations often overestimated risk.Conclusion The discrimination and calibration measures between laboratory-based and non-laboratory-based models show minimal differences, demonstrating the insensitivity of c-statistics and calibration metrics to the inclusion of additional predictors. However, in most reviewed studies, the HRs for these additional predictors were substantial, significantly altering predicted risk, particularly for individuals with higher or lower levels of these predictors compared with the average.https://openheart.bmj.com/content/12/1/e003147.full
spellingShingle Yihun Mulugeta Alemu
Sisay Mulugeta Alemu
Dan Chateau
Nasser Bagheri
Kinley Wangdi
Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review
Open Heart
title Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review
title_full Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review
title_fullStr Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review
title_full_unstemmed Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review
title_short Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review
title_sort discrimination and calibration performances of non laboratory based and laboratory based cardiovascular risk predictions a systematic review
url https://openheart.bmj.com/content/12/1/e003147.full
work_keys_str_mv AT yihunmulugetaalemu discriminationandcalibrationperformancesofnonlaboratorybasedandlaboratorybasedcardiovascularriskpredictionsasystematicreview
AT sisaymulugetaalemu discriminationandcalibrationperformancesofnonlaboratorybasedandlaboratorybasedcardiovascularriskpredictionsasystematicreview
AT danchateau discriminationandcalibrationperformancesofnonlaboratorybasedandlaboratorybasedcardiovascularriskpredictionsasystematicreview
AT nasserbagheri discriminationandcalibrationperformancesofnonlaboratorybasedandlaboratorybasedcardiovascularriskpredictionsasystematicreview
AT kinleywangdi discriminationandcalibrationperformancesofnonlaboratorybasedandlaboratorybasedcardiovascularriskpredictionsasystematicreview