BACKGROUND: The cost-effectiveness acceptability curve (CEAC) graphically depicts the joint uncertainty in a probabilistic model by transforming the incremental cost-effectiveness ratio into a net-benefit framework to represent the probability that a strategy is cost-effective over a range of willingness-to-pay (WTP) thresholds. By characterizing the joint distribution of costs and effects for all model parameters, the CEAC simplifies the presentation of uncertainty compared to deterministic one-way and multi-way sensitivity analyses and allows decision makers to identify the preferred strategy based on their WTP threshold. However, in some instances presenting only the joint uncertainty may be a limitation of the CEAC. METHODS: We propose a method to graphically present the uncertainty contributed by a single parameter within a probabilistic model called the cost-effectiveness sensitivity curve (CESC). Like the CEAC, the y-axis of the CESC represents the probability that a strategy is cost-effective. However, instead of WTP, the x-axis represents a specified range of values for a single model parameter. The CESC is generated by varying the chosen parameter over the specified range of values and calculating the net-benefit at each value for each simulation based on the sampled values of the remaining model parameters without resampling (note: to effect the net-benefit transformation the CESC is based on a single WTP threshold). Computationally, the CESC requires an additional series of calculations for each simulation corresponding to the desired number of points on the curve. The advantage of the CESC is that it probabilistically describes the effect of uncertainty of a single model parameter on cost-effectiveness. This is particularly useful for ex-ante pricing decisions and for early phase go/no-go decisions based on an anticipated range of effectiveness. CONCLUSIONS: The CESC is a useful tool in specific decision making contexts for quantifying the contribution of a single model parameter to uncertainty within a probabilistic model.