In patients with prostate cancer (PC), cardiovascular disease (CVD) causes significant morbidity and is the second leading cause of death. Both pre-existing CVD and the use of androgen deprivation therapy (ADT)-a key cornerstone of treatment for men with locally advanced or metastatic PC1,2 contribute to increased CV risk. ADT has been associated with adverse metabolic effects, including increased central adiposity, elevated low-density lipoprotein (LDL) levels, impaired glycemic control, and arterial wall remodeling and endothelial dysfunction The data demonstrates that for most patients, the status quo is insufficient6 and there remains a critical gap in the early identification of high CV-risk PC patients who may benefit most from aggressive risk mitigation strategies. Mitigation strategies, like the addition of statins as primary prevention, have shown decrease in MI/CHD death across thousands of patients. Age-related expansion of hematopoietic clones carrying recurrent somatic mutations, termed clonal hematopoiesis of indeterminate potential (CHIP) has recently been identified as a significant driver of atherosclerosis, doubling the risk of coronary heart disease. Notably, while CHIP is detectable in \~10% of persons over 70 years old, it is enriched in patients with solid malignancies, and radiotherapy exposure is among the most decisive risk factors for developing CHIP12-15. The inflammation-related metabolic signals are activated androgen signaling and exacerbated in patients with CHIP. However, the mechanistic link and clinical consequence are less understood. Therefore, it is critical to study the CV impact of CHIP and metabolic perturbations in patients with PC treated with ARSI therapy. We plan to address these critical gaps by testing our innovative hypothesis that early cardio-oncology intervention with aggressive guidelines-based CV optimization during ARPI therapy will reduce CV risk and that CHIP and metabolomics will help identify adverse metabolic remodeling to improve CV risk prediction. Robust epidemiological and clinical trial data consistently demonstrate that patients with PC are poorly optimized from a CV risk modification perspective, and existing CV risk models do not perform well in patients with cancer. The data demonstrates that for most patients, the status quo is insufficient and there remains a critical gap in the early identification of high CV-risk PC patients who may benefit most from aggressive risk mitigation strategies.
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Rate of any CV medication Initiation and/or Change
Timeframe: 3 Months Post-Intervention
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