Broad external validation of a multivariable risk prediction model for gastrointestinal malignancy in iron deficiency...

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.

The 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.

The 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.

This 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.