OBJECTIVES:   Budgetary impact modeling often occurs early, amidst uncertainty surrounding the eligible patient population or the final price of a new intervention. Uncertainty can be characterized using per-member per-month (PMPM) iso-curves that graphically depict the net budgetary impact at different prices and population sizes. The objective of this study is to examine the use of PMPM budgetary impact (PMPMBI) iso-curves to represent budgetary uncertainty for products prior to regulatory approval, using denosumab as an example. METHODS:   A 3-year Markov cohort budgetary impact model (BIM) was developed for denosumab in the treatment of postmenopausal osteoporosis in a hypothetical US managed care plan. The model incorporates current market shares and persistence on osteoporosis treatments, and calculates the net impact of adding denosumab to the health plan. Direct costs include drug costs and medical cost offsets due to reductions in osteoporotic fractures. The model was used to construct PMPMBI iso-curves for each of the 3 model years by systematically varying the price of denosumab and the number of patients receiving treatment while holding all other parameters constant. RESULTS:   In year 1, the PMPMBI iso-curves ranged from $-0.06 to $0.08 using the lower and upper limits of price and population size assumptions. The lower iso-curves occur at lower prices and/or population sizes and vice versa. Budget impact is insensitive to the size of the patient population when the price of denosumab is equal to the weighted average price of all other interventions. CONCLUSIONS:   Iso-curves can be used to concisely report BIM results over a wide range of price and population size assumptions. The budgetary impact of denosumab can easily be interpolated once price and population size are known, allowing decision-makers to estimate PMPM costs soon after product approval.