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Risk factor-targeted abdominal aortic aneurysm screening: systematic review of risk prediction for abdominal aortic aneurysm
Abstract Background This systematic review aimed to investigate the current state of risk prediction for abdominal aortic aneurysm in the literature, identifying and comparing published models and describing their performance and applicability to a population-based targeted screening strategy. Metho...
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Published in: | British journal of surgery 2024-09, Vol.111 (9) |
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creator | Musto, Liam Smith, Aiden Pepper, Coral Bujkiewicz, Sylwia Bown, Matthew |
description | Abstract
Background
This systematic review aimed to investigate the current state of risk prediction for abdominal aortic aneurysm in the literature, identifying and comparing published models and describing their performance and applicability to a population-based targeted screening strategy.
Methods
Electronic databases MEDLINE (via Ovid), Embase (via Ovid), MedRxiv, Web of Science, and the Cochrane Library were searched for papers reporting or validating risk prediction models for abdominal aortic aneurysm. Studies were included only if they were developed on a cohort or study group derived from the general population and used multiple variables with at least one modifiable risk factor. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool. A synthesis and comparison of the identified models was undertaken.
Results
The search identified 4813 articles. After full-text review, 37 prediction models were identified, of which 4 were unique predictive models that were reported in full. Applicability was poor when considering targeted screening strategies using electronic health record-based populations. Common risk factors used for the predictive models were explored across all 37 models; the most common risk factors in predictive models for abdominal aortic aneurysm were: age, sex, biometrics (such as height, weight, or BMI), smoking, hypertension, hypercholesterolaemia, and history of heart disease. Few models had undergone standardized model development, adequate external validation, or impact evaluation.
Conclusion
This study identified four risk models that can be replicated and used to predict abdominal aortic aneurysm with acceptable levels of discrimination. None of the models have been validated externally.
Lay Summary
Men in the UK are offered screening for abdominal aortic aneurysm (AAA) when they are 65 years old. Increasing costs in health services and the fact that AAA is becoming rarer mean that the future of screening is uncertain. One possible future of screening is to screen using a predictive model. This is called targeted screening. A predictive model can tell who is most likely to have an AAA. The aim of this study was to explore models in the literature and the main risk factors for AAA that these models identified. A systematic literature review was conducted to identify all relevant models. The initial search identified 4813 scientific articles. After title, abstract, and full-text screening, 37 models were |
doi_str_mv | 10.1093/bjs/znae239 |
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fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11406543</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><oup_id>10.1093/bjs/znae239</oup_id><sourcerecordid>3106458330</sourcerecordid><originalsourceid>FETCH-LOGICAL-o228t-39adc5c73836102c22410861b01967a5d59d88e4168a5e83f505f30f8b702a613</originalsourceid><addsrcrecordid>eNp1kUFv1DAQhS0EarelJ-7IJ9RL6NgTJ04vqKooIFVCqsrZcpzJ4pLEW9tptYgfT1ZdKjhwmsN7-p7ePMbeCHgvoMGz9i6d_ZwsSWxesJXAShVSVPolWwFAXQiUeMiOUroDEAhKHrBDbKSuy0au2K8bn37w3rocYpFtXFOmjtu2C6Of7MBtiNk7biea4zaNPLlINPlpfc7TNmUa7U6O9ODpkYeexx1uE6nzLvsw8T7E_9Nes1e9HRKd7O8x-3b18fbyc3H99dOXy4vrIkipc4GN7ZxyNWqsBEgnZSlAV6IF0VS1VZ1qOq2pXEpbRRp7BapH6HVbg7SVwGP24Ym7mduROkdTjnYwm-hHG7cmWG_-VSb_3azDgxGihEqVuBBO94QY7mdK2Yw-ORqGpUqYk0EBVak0IizWt3-HPaf8-fliePdkCPPmWRVgdmOaZUyzHxN_A66pk7g</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3106458330</pqid></control><display><type>article</type><title>Risk factor-targeted abdominal aortic aneurysm screening: systematic review of risk prediction for abdominal aortic aneurysm</title><source>Oxford Journals Online</source><creator>Musto, Liam ; Smith, Aiden ; Pepper, Coral ; Bujkiewicz, Sylwia ; Bown, Matthew</creator><creatorcontrib>Musto, Liam ; Smith, Aiden ; Pepper, Coral ; Bujkiewicz, Sylwia ; Bown, Matthew</creatorcontrib><description>Abstract
Background
This systematic review aimed to investigate the current state of risk prediction for abdominal aortic aneurysm in the literature, identifying and comparing published models and describing their performance and applicability to a population-based targeted screening strategy.
Methods
Electronic databases MEDLINE (via Ovid), Embase (via Ovid), MedRxiv, Web of Science, and the Cochrane Library were searched for papers reporting or validating risk prediction models for abdominal aortic aneurysm. Studies were included only if they were developed on a cohort or study group derived from the general population and used multiple variables with at least one modifiable risk factor. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool. A synthesis and comparison of the identified models was undertaken.
Results
The search identified 4813 articles. After full-text review, 37 prediction models were identified, of which 4 were unique predictive models that were reported in full. Applicability was poor when considering targeted screening strategies using electronic health record-based populations. Common risk factors used for the predictive models were explored across all 37 models; the most common risk factors in predictive models for abdominal aortic aneurysm were: age, sex, biometrics (such as height, weight, or BMI), smoking, hypertension, hypercholesterolaemia, and history of heart disease. Few models had undergone standardized model development, adequate external validation, or impact evaluation.
Conclusion
This study identified four risk models that can be replicated and used to predict abdominal aortic aneurysm with acceptable levels of discrimination. None of the models have been validated externally.
Lay Summary
Men in the UK are offered screening for abdominal aortic aneurysm (AAA) when they are 65 years old. Increasing costs in health services and the fact that AAA is becoming rarer mean that the future of screening is uncertain. One possible future of screening is to screen using a predictive model. This is called targeted screening. A predictive model can tell who is most likely to have an AAA. The aim of this study was to explore models in the literature and the main risk factors for AAA that these models identified. A systematic literature review was conducted to identify all relevant models. The initial search identified 4813 scientific articles. After title, abstract, and full-text screening, 37 models were found. The 37 models were analysed to identify the most common factors used to predict AAA. The factors age, sex, height and weight, smoking, high blood pressure, and heart disease were found to be the best predictors of developing an AAA. Only four of the studies reported the model in full, making them suitable for use in targeted screening. None of the four models had been tested based on data external to where they were developed, which limits their validity for use in screening programmes.
This systematic review aimed to identify the current state and effectiveness of existing risk prediction models published for abdominal aortic aneurysm. The review identified 4 unique predictive models reported in full with acceptable levels of discrimination, and 33 additional predictive models not reported in full. None of the models had been validated externally. Common risk factors used across all models were identified, and applicability to targeted screening using electronic health records explored.</description><identifier>ISSN: 0007-1323</identifier><identifier>ISSN: 1365-2168</identifier><identifier>EISSN: 1365-2168</identifier><identifier>DOI: 10.1093/bjs/znae239</identifier><identifier>PMID: 39287492</identifier><language>eng</language><publisher>UK: Oxford University Press</publisher><subject>Aortic Aneurysm, Abdominal - diagnosis ; Aortic Aneurysm, Abdominal - epidemiology ; Humans ; Mass Screening - methods ; Risk Assessment - methods ; Risk Factors ; Systematic Review</subject><ispartof>British journal of surgery, 2024-09, Vol.111 (9)</ispartof><rights>The Author(s) 2024. Published by Oxford University Press on behalf of BJS Foundation Ltd. 2024</rights><rights>The Author(s) 2024. Published by Oxford University Press on behalf of BJS Foundation Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0003-1149-8150 ; 0000-0002-7559-0063 ; 0000-0002-6180-3611</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39287492$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Musto, Liam</creatorcontrib><creatorcontrib>Smith, Aiden</creatorcontrib><creatorcontrib>Pepper, Coral</creatorcontrib><creatorcontrib>Bujkiewicz, Sylwia</creatorcontrib><creatorcontrib>Bown, Matthew</creatorcontrib><title>Risk factor-targeted abdominal aortic aneurysm screening: systematic review of risk prediction for abdominal aortic aneurysm</title><title>British journal of surgery</title><addtitle>Br J Surg</addtitle><description>Abstract
Background
This systematic review aimed to investigate the current state of risk prediction for abdominal aortic aneurysm in the literature, identifying and comparing published models and describing their performance and applicability to a population-based targeted screening strategy.
Methods
Electronic databases MEDLINE (via Ovid), Embase (via Ovid), MedRxiv, Web of Science, and the Cochrane Library were searched for papers reporting or validating risk prediction models for abdominal aortic aneurysm. Studies were included only if they were developed on a cohort or study group derived from the general population and used multiple variables with at least one modifiable risk factor. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool. A synthesis and comparison of the identified models was undertaken.
Results
The search identified 4813 articles. After full-text review, 37 prediction models were identified, of which 4 were unique predictive models that were reported in full. Applicability was poor when considering targeted screening strategies using electronic health record-based populations. Common risk factors used for the predictive models were explored across all 37 models; the most common risk factors in predictive models for abdominal aortic aneurysm were: age, sex, biometrics (such as height, weight, or BMI), smoking, hypertension, hypercholesterolaemia, and history of heart disease. Few models had undergone standardized model development, adequate external validation, or impact evaluation.
Conclusion
This study identified four risk models that can be replicated and used to predict abdominal aortic aneurysm with acceptable levels of discrimination. None of the models have been validated externally.
Lay Summary
Men in the UK are offered screening for abdominal aortic aneurysm (AAA) when they are 65 years old. Increasing costs in health services and the fact that AAA is becoming rarer mean that the future of screening is uncertain. One possible future of screening is to screen using a predictive model. This is called targeted screening. A predictive model can tell who is most likely to have an AAA. The aim of this study was to explore models in the literature and the main risk factors for AAA that these models identified. A systematic literature review was conducted to identify all relevant models. The initial search identified 4813 scientific articles. After title, abstract, and full-text screening, 37 models were found. The 37 models were analysed to identify the most common factors used to predict AAA. The factors age, sex, height and weight, smoking, high blood pressure, and heart disease were found to be the best predictors of developing an AAA. Only four of the studies reported the model in full, making them suitable for use in targeted screening. None of the four models had been tested based on data external to where they were developed, which limits their validity for use in screening programmes.
This systematic review aimed to identify the current state and effectiveness of existing risk prediction models published for abdominal aortic aneurysm. The review identified 4 unique predictive models reported in full with acceptable levels of discrimination, and 33 additional predictive models not reported in full. None of the models had been validated externally. Common risk factors used across all models were identified, and applicability to targeted screening using electronic health records explored.</description><subject>Aortic Aneurysm, Abdominal - diagnosis</subject><subject>Aortic Aneurysm, Abdominal - epidemiology</subject><subject>Humans</subject><subject>Mass Screening - methods</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Systematic Review</subject><issn>0007-1323</issn><issn>1365-2168</issn><issn>1365-2168</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNp1kUFv1DAQhS0EarelJ-7IJ9RL6NgTJ04vqKooIFVCqsrZcpzJ4pLEW9tptYgfT1ZdKjhwmsN7-p7ePMbeCHgvoMGz9i6d_ZwsSWxesJXAShVSVPolWwFAXQiUeMiOUroDEAhKHrBDbKSuy0au2K8bn37w3rocYpFtXFOmjtu2C6Of7MBtiNk7biea4zaNPLlINPlpfc7TNmUa7U6O9ODpkYeexx1uE6nzLvsw8T7E_9Nes1e9HRKd7O8x-3b18fbyc3H99dOXy4vrIkipc4GN7ZxyNWqsBEgnZSlAV6IF0VS1VZ1qOq2pXEpbRRp7BapH6HVbg7SVwGP24Ym7mduROkdTjnYwm-hHG7cmWG_-VSb_3azDgxGihEqVuBBO94QY7mdK2Yw-ORqGpUqYk0EBVak0IizWt3-HPaf8-fliePdkCPPmWRVgdmOaZUyzHxN_A66pk7g</recordid><startdate>20240917</startdate><enddate>20240917</enddate><creator>Musto, Liam</creator><creator>Smith, Aiden</creator><creator>Pepper, Coral</creator><creator>Bujkiewicz, Sylwia</creator><creator>Bown, Matthew</creator><general>Oxford University Press</general><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-1149-8150</orcidid><orcidid>https://orcid.org/0000-0002-7559-0063</orcidid><orcidid>https://orcid.org/0000-0002-6180-3611</orcidid></search><sort><creationdate>20240917</creationdate><title>Risk factor-targeted abdominal aortic aneurysm screening: systematic review of risk prediction for abdominal aortic aneurysm</title><author>Musto, Liam ; Smith, Aiden ; Pepper, Coral ; Bujkiewicz, Sylwia ; Bown, Matthew</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-o228t-39adc5c73836102c22410861b01967a5d59d88e4168a5e83f505f30f8b702a613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aortic Aneurysm, Abdominal - diagnosis</topic><topic>Aortic Aneurysm, Abdominal - epidemiology</topic><topic>Humans</topic><topic>Mass Screening - methods</topic><topic>Risk Assessment - methods</topic><topic>Risk Factors</topic><topic>Systematic Review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Musto, Liam</creatorcontrib><creatorcontrib>Smith, Aiden</creatorcontrib><creatorcontrib>Pepper, Coral</creatorcontrib><creatorcontrib>Bujkiewicz, Sylwia</creatorcontrib><creatorcontrib>Bown, Matthew</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>British journal of surgery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Musto, Liam</au><au>Smith, Aiden</au><au>Pepper, Coral</au><au>Bujkiewicz, Sylwia</au><au>Bown, Matthew</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Risk factor-targeted abdominal aortic aneurysm screening: systematic review of risk prediction for abdominal aortic aneurysm</atitle><jtitle>British journal of surgery</jtitle><addtitle>Br J Surg</addtitle><date>2024-09-17</date><risdate>2024</risdate><volume>111</volume><issue>9</issue><issn>0007-1323</issn><issn>1365-2168</issn><eissn>1365-2168</eissn><abstract>Abstract
Background
This systematic review aimed to investigate the current state of risk prediction for abdominal aortic aneurysm in the literature, identifying and comparing published models and describing their performance and applicability to a population-based targeted screening strategy.
Methods
Electronic databases MEDLINE (via Ovid), Embase (via Ovid), MedRxiv, Web of Science, and the Cochrane Library were searched for papers reporting or validating risk prediction models for abdominal aortic aneurysm. Studies were included only if they were developed on a cohort or study group derived from the general population and used multiple variables with at least one modifiable risk factor. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool. A synthesis and comparison of the identified models was undertaken.
Results
The search identified 4813 articles. After full-text review, 37 prediction models were identified, of which 4 were unique predictive models that were reported in full. Applicability was poor when considering targeted screening strategies using electronic health record-based populations. Common risk factors used for the predictive models were explored across all 37 models; the most common risk factors in predictive models for abdominal aortic aneurysm were: age, sex, biometrics (such as height, weight, or BMI), smoking, hypertension, hypercholesterolaemia, and history of heart disease. Few models had undergone standardized model development, adequate external validation, or impact evaluation.
Conclusion
This study identified four risk models that can be replicated and used to predict abdominal aortic aneurysm with acceptable levels of discrimination. None of the models have been validated externally.
Lay Summary
Men in the UK are offered screening for abdominal aortic aneurysm (AAA) when they are 65 years old. Increasing costs in health services and the fact that AAA is becoming rarer mean that the future of screening is uncertain. One possible future of screening is to screen using a predictive model. This is called targeted screening. A predictive model can tell who is most likely to have an AAA. The aim of this study was to explore models in the literature and the main risk factors for AAA that these models identified. A systematic literature review was conducted to identify all relevant models. The initial search identified 4813 scientific articles. After title, abstract, and full-text screening, 37 models were found. The 37 models were analysed to identify the most common factors used to predict AAA. The factors age, sex, height and weight, smoking, high blood pressure, and heart disease were found to be the best predictors of developing an AAA. Only four of the studies reported the model in full, making them suitable for use in targeted screening. None of the four models had been tested based on data external to where they were developed, which limits their validity for use in screening programmes.
This systematic review aimed to identify the current state and effectiveness of existing risk prediction models published for abdominal aortic aneurysm. The review identified 4 unique predictive models reported in full with acceptable levels of discrimination, and 33 additional predictive models not reported in full. None of the models had been validated externally. Common risk factors used across all models were identified, and applicability to targeted screening using electronic health records explored.</abstract><cop>UK</cop><pub>Oxford University Press</pub><pmid>39287492</pmid><doi>10.1093/bjs/znae239</doi><orcidid>https://orcid.org/0000-0003-1149-8150</orcidid><orcidid>https://orcid.org/0000-0002-7559-0063</orcidid><orcidid>https://orcid.org/0000-0002-6180-3611</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aortic Aneurysm, Abdominal - diagnosis Aortic Aneurysm, Abdominal - epidemiology Humans Mass Screening - methods Risk Assessment - methods Risk Factors Systematic Review |
title | Risk factor-targeted abdominal aortic aneurysm screening: systematic review of risk prediction for abdominal aortic aneurysm |
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