On Counterfactual Explanations of Cardiovascular Risk in Adolescent and Young Adult Breast Cancer Survivors

Cancer treatments might lead to several long-term effects. In this work we investigate their causal role on ischemic heart disease and their potential precursors (i.e. hypertension and dyslipidemia) of the ovarian suppression therapy in adolescent and young adult (AYA) breast cancer (BC) survivors. Additionally, we assess the external validity of our findings through comparative analysis of regional data. We take advantage of a causal network model that leverage on observational data on 1-year AYA BC survivors living the Lombardy region in Italy. Using a structural causal model (SCM) and counterfactual analysis within Pearl’s causal inference framework, we estimate the Average Causal Effect (ACE), Probability of Necessity (PN), and Probability of Sufficiency (PS) for the cause-effect relationships. Data of a regional cohort of AYA BC patients living in the Veneto region were used to externally validate results. Ovarian suppression was found to be a necessary but not sufficient cause for ischemic heart disease (PN > 97.8%; PS < 1.97%). While PN is high for both hypertension and dyslipidemia, PS varied suggesting ovarian suppression alone could induce hypertension in about 30% of cases but was rarely sufficient for dyslipidemia onset. External validation confirmed the robustness of findings across regions. Our experimental results may be of interest for clinicians who aim at personalizing the follow-up of AYA BC survivors, with particular attention to be paid in monitoring the hypertension onset or in its prevention. The study demonstrates the value of counterfactual reasoning and causal inference when working with real-world data.