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Original Articles

Budget impact of rosuvastatin initiation in high-risk hyperlipidemic patients from a US managed care perspective

, &
Pages 907-916 | Accepted 25 Apr 2013, Published online: 23 May 2013

Figures & data

Figure 1. Model structure.

Figure 1. Model structure.

Table 1. Patient population.

Table 2. Starting doses.

Table 3. Percent reduction in LDL-C levelsCitation14.

Table 4. Treatment decision in patients failing to reach goalCitation20.

Table 5. Statin dose received by switching patientsCitation20.

Table 6. WAC for statins.

Table 7. Rebates, dispensing fees, and copaymentsCitation20,Citation34.

Table 8. Proportional distribution of CV events and associated costsCitation38,Citation39.

Figure 2. Patients reaching their LDL-C goal, by risk group.

Figure 2. Patients reaching their LDL-C goal, by risk group.

Figure 3. Net spending over 3 years, by risk group.

Figure 3. Net spending over 3 years, by risk group.

Figure 4. Sensitivity analyses. One-way sensitivity analyses were performed by varying the following model parameters by ±10% relative to the base-case value: [1] Rebate of rosuvastatin; [2] Average population LDL-C level; [3] Tier 3 copayment; [4] LDL-C goal of patients with high CV risk; [5] Proportion of patients with high CV risk; [6] Proportion of atorvastatin and simvastatin patients continuing to receive the same dose; [7] Proportion of atorvastatin and simvastatin patients switching to a different statin; [8] Tier 1 copayment; [9] Dispensing fee of rosuvastatin; [10] Proportion of atorvastatin and simvastatin patients titrating to a higher dose. Parameters directly affecting the cost of rosuvastatin ([1], [3]) have the greatest impact on the budget impact, as do the average LDL-C level of the population ([2]) and the LDL-C goal of patients with high CV risk ([4]); titration and switching decisions ([6], [7], [10]) for patients failing to reach goal have less of an impact on the model results.

Figure 4. Sensitivity analyses. One-way sensitivity analyses were performed by varying the following model parameters by ±10% relative to the base-case value: [1] Rebate of rosuvastatin; [2] Average population LDL-C level; [3] Tier 3 copayment; [4] LDL-C goal of patients with high CV risk; [5] Proportion of patients with high CV risk; [6] Proportion of atorvastatin and simvastatin patients continuing to receive the same dose; [7] Proportion of atorvastatin and simvastatin patients switching to a different statin; [8] Tier 1 copayment; [9] Dispensing fee of rosuvastatin; [10] Proportion of atorvastatin and simvastatin patients titrating to a higher dose. Parameters directly affecting the cost of rosuvastatin ([1], [3]) have the greatest impact on the budget impact, as do the average LDL-C level of the population ([2]) and the LDL-C goal of patients with high CV risk ([4]); titration and switching decisions ([6], [7], [10]) for patients failing to reach goal have less of an impact on the model results.

Figure 5. Scenario analyses. Event costs were included based on the average cost per CV eventCitation38,Citation40 and the number of patients experiencing CV events among those reaching and failing to reach their LDL-C goalCitation6,Citation38,Citation39. Real-life efficacy was estimated by decreasing the efficacy of all statin doses by 21%Citation33.

Figure 5. Scenario analyses. Event costs were included based on the average cost per CV eventCitation38,Citation40 and the number of patients experiencing CV events among those reaching and failing to reach their LDL-C goalCitation6,Citation38,Citation39. Real-life efficacy was estimated by decreasing the efficacy of all statin doses by 21%Citation33.

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