Abstract
BackgroundUsing two large datasets from Dorset, we previously reported an internally validated multivariable risk model for predicting the risk of GI malignancy in IDA—the IDIOM score. The aim of this retrospective observational study was to validate the IDIOM model using two independent external datasets.MethodsThe external validation datasets were collected, in a secondary care setting, by different investigators from cohorts in Oxford and Sheffield derived under different circumstances, comprising 1117 and 474 patients with confirmed IDA respectively. The data were anonymised prior to analysis. The predictive performance of the original model was evaluated by estimating measures of calibration, discrimination and clinical utility using the validation datasets.ResultsThe discrimination of the original model using the external validation data was 70% (95% CI 65, 75) for the Oxford dataset and 70% (95% CI 61, 79) for the Sheffield dataset. The analysis of mean, weak, flexible and across the risk groups’ calibration showed no tendency for under or over-estimated risks in the combined validation data. Decision curve analysis demonstrated the clinical value of the IDIOM model with a net benefit that is higher than ‘investigate all’ and ‘investigate no-one’ strategies up to a threshold of 18% in the combined validation data, using a risk cut-off of around 1.2% to categorise patients into the very low risk group showed that none of the patients stratified in this risk group proved to have GI cancer on investigation in the validation datasets.ConclusionThis external validation exercise has shown promising results for the IDIOM model in predicting the risk of underlying GI malignancy in independent IDA datasets collected in different clinical settings.
Highlights
Using two large datasets from Dorset, we previously reported an internally validated multivariable risk model for predicting the risk of GI malignancy in iron deficiency anaemia (IDA)—the Iron deficiency as an indicator of malignancy (IDIOM) score
With the aim of risk stratification, we have previously built and internally validated a binary multivariable logistic model to predict the risk of GI cancer in patients with confirmed IDA, based on four simple variables: age, sex, haemoglobin concentration (Hb) and mean cell volume (MCV)—the IDIOM model [4]
Before importing the coefficients of the full IDIOM model to predict the risk of GI cancer in the validation data, least absolute shrinkage and selection operator (Lasso) was applied to regulate the model
Summary
Using two large datasets from Dorset, we previously reported an internally validated multivariable risk model for predicting the risk of GI malignancy in IDA—the IDIOM score. The aim of this retrospective observational study was to validate the IDIOM model using two independent external datasets. With the aim of risk stratification, we have previously built and internally validated a binary multivariable logistic model to predict the risk of GI cancer in patients with confirmed IDA, based on four simple variables: age, sex, haemoglobin concentration (Hb) and mean cell volume (MCV)—the IDIOM model (iron deficiency as an indicator of malignancy) [4]. Due to informed patient preference, concurrent illness or major co-morbidity, about 10% of IDA patients usually fail to undergo GI investigation for IDA [3, 8]
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