Paolo Emilio Puddu1, Paolo Piras2, Alessandro Menotti3. 1. Department of Cardiovascular, Respiratory, Nephrological, Anesthesiological and Geriatric Sciences, Sapienza University of Rome, Rome, Italy. Electronic address: paoloemilio.puddu@uniroma1.it. 2. Department of Cardiovascular, Respiratory, Nephrological, Anesthesiological and Geriatric Sciences, Sapienza University of Rome, Rome, Italy. 3. Association for Cardiac Research, Rome, Italy.
Abstract
OBJECTIVES: To study coronary heart disease (CHD) incidence versus other cause of death using the cumulative incidence function and the competing risks procedures to disentangle the differential role of risk factors for different end-points. MATERIAL AND METHODS: We compared standard Cox and Fine-Gray models among 1677 middle aged men of an Italian population study of cardiovascular diseases that reached 50years of follow-up with the quasi extinction of the population. The incidence of either fatal or non-fatal cases in 50years was used as primary event, while deaths from any other cause, mutually exclusive from the primary events, were considered as secondary events. We considered 10 selected risk factors. RESULTS: The main result was that cholesterol was significantly and positively related to incidence of CHD contrasted with deaths from any other cause. On the other hand, when the primary events were deaths from any other cause and the competing events were CHD, cholesterol was inversely and age positively related. This outcome did not exclude the predictive role of other risk factors, such as age, cigarettes, arm circumference (protective), systolic blood pressure, vital capacity (protective), cholesterol, corneal arcus and diabetes, documented by the Cox model, that had common roles for both end-points. CONCLUSIONS: Fine-Gray model, initially proposed to handle adequately cumulative incidence function may thus prevent overestimation of risks related to the Kaplan-Meier based methods such as Cox model and identify the specific risk factors for defined end-points.
OBJECTIVES: To study coronary heart disease (CHD) incidence versus other cause of death using the cumulative incidence function and the competing risks procedures to disentangle the differential role of risk factors for different end-points. MATERIAL AND METHODS: We compared standard Cox and Fine-Gray models among 1677 middle aged men of an Italian population study of cardiovascular diseases that reached 50years of follow-up with the quasi extinction of the population. The incidence of either fatal or non-fatal cases in 50years was used as primary event, while deaths from any other cause, mutually exclusive from the primary events, were considered as secondary events. We considered 10 selected risk factors. RESULTS: The main result was that cholesterol was significantly and positively related to incidence of CHD contrasted with deaths from any other cause. On the other hand, when the primary events were deaths from any other cause and the competing events were CHD, cholesterol was inversely and age positively related. This outcome did not exclude the predictive role of other risk factors, such as age, cigarettes, arm circumference (protective), systolic blood pressure, vital capacity (protective), cholesterol, corneal arcus and diabetes, documented by the Cox model, that had common roles for both end-points. CONCLUSIONS: Fine-Gray model, initially proposed to handle adequately cumulative incidence function may thus prevent overestimation of risks related to the Kaplan-Meier based methods such as Cox model and identify the specific risk factors for defined end-points.