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Fig. 3 | BMC Medical Informatics and Decision Making

Fig. 3

From: From algorithms to action: improving patient care requires causality

Fig. 3

Simplified Directed Acyclic Graph for the decision between surgery and radiotherapy for overall survival in lung cancer patients. As an example, consider a hypothetical study in early-stage lung cancer where researchers investigate whether the relative effectiveness of surgery versus radiotherapy for overall survival depends on a certain single-nucleotide polymorphism (SNP). The SNP assay was performed for the study only so this information did not affect the treatment decision. A DAG with four variables for this study is presented in this Figure. In this DAG, the variables age and SNP both have arrows to overall survival, but only age influences the treatment decision as older patients are less likely to get surgery. This DAG indicates that unconfoundedness holds when age is conditioned on in the analysis, as age is the only confounder between the treatment and the outcome [17]

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