Background: Cancer is a known prognostic factor in patients with acute coronary syndrome (ACS), but few risk assessments of cancer development after ACS have been established.
Methods and results: Of the 573 consecutive ACS admissions between January 2015 and March 2018 in Nobeoka City, Japan, 552 were analyzed. Prevalent cancer was defined as a treatment history of cancer, and incident cancer as post-discharge cancer incidence. The primary endpoint was post-discharge cancer incidence, and the secondary endpoint was all-cause death during follow-up. All-cause death occurred in 9 (23.1%) patients with prevalent cancer, and in 17 (3.5%) without cancer. In the multivariable analysis, prevalent cancer was associated with all-cause death. To develop the prediction model for cancer incidence, 21 patients with incident cancer and 492 without cancer were analyzed. We compared the performance of D-dimer with that of the prediction model, which added age (≥65 years), smoking history, and high red blood cell distribution width to albumin ratio (RAR) to D-dimer. The areas under the receiver-operating characteristics curves of D-dimer and the prediction model were 0.619 (95% confidence interval: 0.512-0.725) and 0.774 (0.676-0.873), respectively. Decision curve analysis showed superior net benefits of the prediction model.
Conclusions: By adding elderly, smoking, and high RAR to D-dimer to the prediction model it became clinically useful for predicting cancer incidence after ACS.
Keywords: Acute coronary syndrome; Cancer; Cardio-oncology; Prediction model.