Noushin Fahimfar, Sareh Eghtesad, Hossein Poustchi, Karim Kohansal, Sadaf G Sepanlou, Afshin Ostovar, Ali Esmaeili-Nadimi, Ehsan Bahramali, Farhad Pourfarzi, Samad Ghaffari, Azim Nejatizadeh, Farhad Moradpour, Ali Mousavizadeh, Farahnaz Joukar, Saeid Bitaraf, Vahid Mohammadkarimi, Farid Najafi, Seyed Vahid Hosseini, Ali Gohari, Arsalan Khaledifar, Motahareh Kheradmand, Kamal Khademvatani, Mohammad Hasan Lotfi, Alireza Ansari-Moghaddam, Reza Malekzadeh, Davood Khalili
{"title":"Stepwise approach to screen high-risk individuals using the non-laboratory-based and laboratory-based CVD risk scoring.","authors":"Noushin Fahimfar, Sareh Eghtesad, Hossein Poustchi, Karim Kohansal, Sadaf G Sepanlou, Afshin Ostovar, Ali Esmaeili-Nadimi, Ehsan Bahramali, Farhad Pourfarzi, Samad Ghaffari, Azim Nejatizadeh, Farhad Moradpour, Ali Mousavizadeh, Farahnaz Joukar, Saeid Bitaraf, Vahid Mohammadkarimi, Farid Najafi, Seyed Vahid Hosseini, Ali Gohari, Arsalan Khaledifar, Motahareh Kheradmand, Kamal Khademvatani, Mohammad Hasan Lotfi, Alireza Ansari-Moghaddam, Reza Malekzadeh, Davood Khalili","doi":"10.1093/pubmed/fdaf037","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>We compared non-laboratory models' efficacy with standard laboratory-based model in identifying high-risk populations for cardiovascular disease (CVD) in resource-limited settings.</p><p><strong>Methods: </strong>A national sample of 121 672 individuals aged 40-70 from the PERSIAN cohort was analyzed. Non-laboratory models, including the World Health Organization (WHO) and Iranian pooled-cohort CVD mortality models, were compared with the WHO laboratory-based model. Intra-class correlation coefficient (ICC) and concordance correlation coefficient (CCC) were utilized. Sensitivity and specificity of non-laboratory models were evaluated against the laboratory-based one at various risk thresholds. The number of reduced tests in the stepwise approach was calculated considering the Iranian census.</p><p><strong>Results: </strong>Both non-laboratory and laboratory-based models showed similar trends in predicting CVD risks across age groups. Strong correlations and concordance were observed in both men (ICC: 94.4%, CCC:0.893) and women (ICC: 93.8%, CCC:0.883). Utilizing a 5% risk threshold for WHO non-laboratory and 2% for the Iranian pooled-cohort CVD mortality model as the initial step achieved high sensitivity (99.6%) and moderate specificity (52%) for identifying candidates for the second-step laboratory test. This approach effectively reduced the number of tests by 16 807 982.</p><p><strong>Conclusion: </strong>Non-laboratory models, in a stepwise approach, offer a promising strategy to alleviate strain on financial resources and enhance healthcare system efficiency in resource-limited countries.</p>","PeriodicalId":94107,"journal":{"name":"Journal of public health (Oxford, England)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of public health (Oxford, England)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/pubmed/fdaf037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: We compared non-laboratory models' efficacy with standard laboratory-based model in identifying high-risk populations for cardiovascular disease (CVD) in resource-limited settings.
Methods: A national sample of 121 672 individuals aged 40-70 from the PERSIAN cohort was analyzed. Non-laboratory models, including the World Health Organization (WHO) and Iranian pooled-cohort CVD mortality models, were compared with the WHO laboratory-based model. Intra-class correlation coefficient (ICC) and concordance correlation coefficient (CCC) were utilized. Sensitivity and specificity of non-laboratory models were evaluated against the laboratory-based one at various risk thresholds. The number of reduced tests in the stepwise approach was calculated considering the Iranian census.
Results: Both non-laboratory and laboratory-based models showed similar trends in predicting CVD risks across age groups. Strong correlations and concordance were observed in both men (ICC: 94.4%, CCC:0.893) and women (ICC: 93.8%, CCC:0.883). Utilizing a 5% risk threshold for WHO non-laboratory and 2% for the Iranian pooled-cohort CVD mortality model as the initial step achieved high sensitivity (99.6%) and moderate specificity (52%) for identifying candidates for the second-step laboratory test. This approach effectively reduced the number of tests by 16 807 982.
Conclusion: Non-laboratory models, in a stepwise approach, offer a promising strategy to alleviate strain on financial resources and enhance healthcare system efficiency in resource-limited countries.