The plasma proteome as a cardiovascular disease risk assessment tool in cancer survivors

Background

• Cardiovascular disease (CVD) is the most common cause of non-cancer death in individuals following a cancer diagnosis
• Cancer survivors have up to a 37% increased risk of incident CVD than those without cancer. This elevated risk is sustained even 20 years following cancer diagnosis
• Increased cardiovascular risk in cancer survivors is attributed to several factors:
  • cardiotoxic effects of chemotherapy and radiotherapy
  • physiologic effects of cancer such as inflammation and oxidative stress
  • common biological predisposition such as genetics
  • shared lifestyle risk factors including smoking, diabetes, and obesity
• While American and European societies of cardiology recommend screening for CVD following cancer treatment, there is currently no validated risk prediction tool to accurately assess CVD risk in adult cancer survivors (beyond ASCVD score)

Methods

• A previously validated 27-protein prognostic model to predict the four-year risk of a CV event (myocardial infarction, stroke/transient ischemic attack, heart failure hospitalization, death) was validated in two additional cohorts for this new intended use population
• BASEL VIII is a large prognostic and diagnostic study aiming to advance the non-invasive diagnosis of obstructive coronary artery disease (CAD). The dataset includes clinical data and EDTA plasma for 569 participants with a medically adjudicated prior history or active malignancy of any type of cancer
• ARIC is a multi-site prospective cohort study designed to investigate the etiology and natural history of atherosclerotic diseases. The ARIC visit 3 dataset used includes clinical data and EDTA plasma for 337 participates with a medically adjudicated prior history or active malignancy of any type of cancer
• Model discrimination in this new intended use population was assessed using 4-year area under the curve (AUC) and the time-independent C-index (calculated using all available follow-up data)
  • Model performance was assessed in the entire cohort, and separately in adults aged 40 and older with and without a history of cardiovascular disease

Results

27-protein CVD risk model can accurately stratify and discriminate patient risk in cancer survivors

The 27-protein CVD risk model accurately predicts CV event risk in adult cancer survivors regardless of cardiovascular history

• Performance of the 27-protein model was comparable between participants with no prior history of CVD (AUC: 0.71; C-Index: 0.69) and stable CVD (AUC: 0.72; C-Index: 0.69)
• Observed 4-year event rates in cancer survivors were higher than event rates in a cohort of participants with elevated CVD risk factors (10.4% vs 5.6% Low; 16.8% vs 11.2% Medium-Low; 31.5% vs 20.2% Medium-High; and 58.2% vs 43.4% High, respectively)

Alignment between 27-protein CVD risk model predictions and observed event rates

Calibration of observed vs expected event rates by risk quantile

• The 27-protein CVD risk model overpredicts risk at the high end of the range, however these participants are at very high risk for a CV event (58.2%) within the next 4 years
• Event predictions in the lower and mid-range, where accuracy is most important, are reasonably aligned with observed event rates

27-protein CVD risk model outperforms current standard of care

The 27-protein CVD risk model is superior to other risk prediction models

• Age alone does not drive CV event risk in ARIC and BASEL cancer survivors

Analyses of event type confirmed that cancer or other non-CV related deaths were not driving model performance

• The majority of participants (57%) did not die of cancer or other non-CV related deaths
• 44% of participants experienced a non-fatal CV event
• All event types were represented across risk bins

Conclusions

• Cancer survivors in this cohort were distinguished into distinct cardiovascular risk bins with 4-year CV event rates as high as 58.2%
• The 27-protein CVD risk model is superior to the current standard of care for predicting 4-year CV event risk in a cohort of cancer survivors (C-index: 0.71 vs 0.66 and AUC: 0.74 vs 0.62 for proteomic model vs ASCVD equation, respectively)
• Prognostic protein testing may provide a novel tool for CVD risk assessment in adult cancer survivors

Authors

Emma Troth¹
Matthew Ayala¹
Jessica Chadwick¹
Erin Hales¹
Michael A. Hinterberg¹
Jessica N. Kuzma¹
Clare Paterson¹
Rachel Ostroff¹
Joan E. Walter²
Christian Mueller²
Josef Coresh³

¹SomaLogic Operating Co., Inc., Boulder, CO USA
²Cardiovascular Research Institute, University of Basel, Basel 4001, Switzerland
³Johns Hopkins University, Baltimore, MD 21218, USA