How to predict a CVD patient’s risk of total, colorectal and lung cancer

Data from patients with established cardiovascular disease (CVD) can be used to predict their lifetime and 10-year risk of multiple cancers, according to new findings presented at ESC Congress 2020.

The study, published in JACC: CardioOncology, focused on prediction models for total cancer, colorectal cancer and lung cancer.

“Estimating individualized probabilities could help in patients’ and clinicians’ understanding of cancer risk,” wrote lead author Cilie C. van’t Klooster, MD, Utrecht University in the Netherlands, and colleagues. “As several modifiable risk factors are related to cancer as well as to CVD, discussing these cancer risks with patients could potentially aid in emphasizing healthy lifestyle changes, such as smoking cessation or weight loss.”

They authors used data from more than 7,000 patients with established CVD to develop the prediction models, validating them with data from another 9,322 patients. The selected predictors were age, sex, smoking, weight, height, alcohol use, antiplatelet use, diabetes and C-reactive protein.

Overall, the authors found that the lifetime and 10-year risk of total cancer, colorectal cancer and lung cancer could be “estimated reasonably well with easy clinically available predictors in patients with established CVD.”

The median predicted absolute 10-year risks were 16% for total cancer, 2% for colorectal cancer and 2% for lung cancer in the development cohort. The median predicted absolute 10-year risks were 13% for total cancer, 2% for colorectal cancer and 2% for lung cancer in validation cohort.

Meanwhile, the median predicted absolute lifetime risks were 35% for total cancer, 5% for colorectal cancer and 7% for lung cancer in development cohort. The median predicted absolute lifetime risks were 26% for total cancer, 4% for colorectal cancer and 5% for lung cancer in the validation cohort.

“Given the wide distribution of predicted lifetime risks for total cancer and lung cancer, these models can enable the identification of patients at the highest risk for cancer,” the authors concluded.

ESC Congress 2020 is completely digital due to the ongoing COVID-19 pandemic. More information from the European Society of Cardiology is available here.

The full JACC: CardioOncology analysis can be read here.

Michael Walter
Michael Walter, Managing Editor

Michael has more than 16 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.

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