The importance of data: Monitoring variables in causal inference with medical imaging

Background and objectives

In scientific studies with medical imaging, it is important that the process involved in selecting the explanatory variables is closely monitored, as this can lead to significant confounding biases in its methodology. The aim of this paper is to explore whether it is feasible to use criteria for causation (such as those outlined by Bradford Hill) when selecting variables in articles published in the journal RADIOLOGÍA.

Material and methods

We selected the July-August issue of Radiología, issue 4 of 2023. Four original articles with sample sizes of at least 100 patients were chosen and their follow-up of causation was analysed.

Results

The criteria of temporality, consistency, coherence, plausibility and analogy were observed. The criteria of specificity, experiment, strength and biological gradient were not consistently applied. The methodological robustness and quality of these studies was also noted.

Conclusion

Bradford Hill's criteria for causation are useful for the selection of variables in medical imaging studies. The most relevant criteria in medical imaging are temporality, consistency, coherence, plausibility and analogy.