Key result
A systematic review identified four unique risk prediction models for abdominal aortic aneurysm with acceptable discrimination, though none have been externally validated.
Why the study?
The current state, performance, and applicability of published multivariable risk prediction models for abdominal aortic aneurysm to population-based targeted screening were not well established.
What is the current state of risk prediction models for abdominal aortic aneurysm in the general population?
Systematic Review
What is the current state of risk prediction models for abdominal aortic aneurysm in the general population?
While several risk prediction models for abdominal aortic aneurysm exist with acceptable discrimination, their clinical utility is currently limited by a lack of external validation and poor applicability to EHR-based targeted screening.
Four replicable AAA risk models show acceptable discrimination; leaves open targeted screening use pending external validation and impact assessment.
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.
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Musto et al. (2024) conducted a systematic review in abdominal aortic aneurysm. Risk prediction models was evaluated on Identification and performance of risk prediction models. A systematic review identified four unique risk prediction models for abdominal aortic aneurysm with acceptable discrimination, though none have been externally validated.
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