Abstract
Background
As treatment for cardiovascular disease (CVD) has improved substantially over the last decades, more patients survive acute CVD manifestations and are at risk for developing cancer as well as recurrent CVD. Due to similar risk factors, including smoking and obesity, patients with established CVD are at higher risk for cancer.
Objectives
The aim of this study was to develop and externally validate prediction models for the estimation of 10-year and lifetime risk for total, colorectal, and lung cancer in patients with established CVD.
Methods
Data from patients with established CVD from the UCC-SMART prospective cohort study (N=7,280) were used for model development, and data from the CANTOS trial (N=9,322) were used for model validation. Predictors were selected based on previously published cancer risk prediction models or cancer risk factors, easy clinical availability, and availability in the derivation dataset (UCC-SMART cohort). A Fine and Gray competing risk-adjusted lifetime model was developed for total, colorectal, and lung cancer.
Results
Selected predictors were age, sex, smoking status, weight, height, alcohol use, antiplatelet use, diabetes mellitus, and C-reactive protein. External calibration for 4-year risks of the total cancer, colorectal cancer, and lung cancer models was good (Figure 1), and C-statistics were 0.63–0.74 in the CANTOS trial population. Median predicted lifetime risks in CANTOS were 26% (range 1%-52%) for total cancer, 4% (range 0%-13%) for colorectal cancer, and 5% (range 0%-37%) for lung cancer.
Conclusions
Lifetime and 10-year risk of cancer can be estimated with easy to measure variables in patients with established CVD, showing a wide distribution of predicted lifetime risks for total cancer and lung cancer. Using these lifetime models in clinical practice could increase understanding of cancer risk and aid in emphasizing healthy lifestyle changes.
Figure 1. Calibration plots of cancer models
Funding Acknowledgement
Type of funding source: Public hospital(s). Main funding source(s): University Medical Center; Additional funding: CANTOS trial was funded by Novartis Pharmaceuticals.
Inhalation delivery of Telmisartan enhances intratumoral distribution of nanoparticles in lung cancer models
