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Background: In the Netherlands, antihypertensive treatment for patients with mild hypertension is recommended if the 10-year cardiovascular disease (CVD) risk exceeds 20%. Recent evidence suggests that lifelong CVD risk estimates might be more informative than 10-year ones. In addition, the cost of antihypertensive treatment in the Netherlands has decreased during the last decade. Objective: The aim of this study is to estimate the cost-effectiveness of lowering systolic blood pressure (SBP) in patients ineligible for treatment in both a 10-year and a lifetime horizon. Methods: A Markov model was developed to assess the cost-effectiveness of SBP reduction compared with no reduction in patients with mild hypertension and low CVD risk. Modified SCORE (Systematic Coronary Risk Evaluation) risk estimates were used to predict fatal and nonfatal CVD events. We analyzed scenarios for different age groups, sexes, and SBP reductions. Specifically, SBP reductions due to hydrochlorothiazide (HCT) 25 mg and hypothetical reductions with HCT 12.5 mg-losartan 50 mg combination were assumed. Parameter uncertainty was assessed through a probabilistic sensitivity analysis. Results: In a 10-year horizon, in scenarios of SBP reduction with HCT 25 mg, the incremental cost-effectiveness ratio (ICER) estimates for men varied across different ages in the range of €6032 to €58,217 per life-year gained, whereas for women ICER estimates were in the range of €12,345 to €361,064 per life-year gained. In a lifetime horizon, the cost-effectiveness estimates were favorable for both sexes. In scenarios of hypothetical SBP reductions, more favorable ICER estimates compared with no reduction were found. A large uncertainty around the cost-effectiveness estimates was observed among all scenarios. Conclusion: Larger SBP reductions were found to be cost-effective in both a 10-year and lifetime horizon. These findings might call for more aggressive SBP reductions in patients with mild hypertension. However, a high level of uncertainty surrounds these cost-effectiveness estimates because they are based on CVD risk prediction modeling. [ABSTRACT FROM AUTHOR]