OBJECTIVES: The determination of coronary calcium score allows to identify individuals for which primary prevention with statins may be unnecessary. In this study it is shown that the presence of risk factors for developing diabetes interacts with the benefits of this identification. METHODS: A Markov model was used to estimate the evolution of two cohorts with elevated C-reactive protein and low LDL cholesterol: one without risk factors for developing diabetes and another with those risk factors. The progression of both cohorts was simulated assuming four alternative strategies: “no treatment”, “treat if score>100”, “treat if score>0” and “treat all”. RESULTS: For individuals without risk factors for diabetes, the “treat all” strategy is the most expensive but allows to achieve better clinical outcomes, with a cost per QALY of 24,164€ vs. the strategy “treat if score>0”. For those with risk factors for diabetes, the strategy “treat all” remains the most expensive, but the decrease in coronary events does not compensate the increase in diabetes incidence, whereby the strategy “treat all” is dominated by “treat if score> 0”. The cost per QALY of this latter strategy in comparison to “treat if score>100” is 36,034€. Deterministic and probabilistic sensitivity analysis show that results are robust. CONCLUSIONS: The presence of risk factors for diabetes affects the cost-effectiveness of using coronary calcium score as a guide to implement primary prevention in this population.