Modeling Cost-Effectiveness of On-Demand Treatment for Hereditary Angioedema Attacks.

BACKGROUND: Hereditary angioedema (HAE) is a rare C1-inhibitor (C1-INH) deficiency disease. Low levels of functional C1-INH can lead to recurrent attacks of severe swelling occurring in areas such as the limbs, face, gastrointestinal tract, and throat. These attacks are both painful and disabling and, if not treated promptly and effectively, can result in hospitalization or death. Agents targeting the specific physiologic pathway of HAE attacks can offer improved outcomes with limited side effects compared with nonspecific therapies. However, these treatments display varying efficacy in HAE patients, including the need to redose or seek additional care if the treatment does not resolve symptoms effectively. OBJECTIVE: To analyze the expected cost and utility per HAE attack when treated on-demand with HAE therapies indicated for the treatment of acute attacks. METHODS: A decision-tree model was developed using TreeAge Pro software. Four on-demand HAE treatments were included: ecallantide, icatibant, plasma-derived (pd)C1-INH, and recombinant human (rh)C1-INH. The model uses probabilities for redosing, self-administration versus health care provider administration, and risk of hospitalization. Costs within the model consisted of the HAE treatments and associated health care system expenses. Nonattack baseline utility and attack utility were implemented for effectiveness calculations; time to attack resolution was considered as well. Effectiveness and overall costs per attack were calculated and used to estimate cost per quality-adjusted life-year (QALY). Variability and ranges in cost-effectiveness were determined using probabilistic sensitivity analyses. Finally, a budget impact model for a health plan with 1 million covered lives was also developed. RESULTS: The base case model outputs show costs and calculated effectiveness per attack at $12,905 and 0.806 for rhC1-INH, $14,806 and 0.765 for icatibant, $14,668 and 0.769 for pdC1-INH, and $21,068 and 0.792 for ecallantide, respectively. Cost per QALY was calculated using 26.9 attacks per person-year, leading to results of $420,941 for rhC1-INH, $488,349 for icatibant, $483,892 for pdC1-INH, and $689,773 for ecallantide. Sensitivity analyses demonstrate that redose rates (from 3% for rhC1-INH to 44% for icatibant) are a primary driver of variability in cost-effectiveness. Annual health plan costs from the budget impact model are calculated as $6.94 million for rhC1-INH, $7.97 million for icatibant, $7.90 million for pdC1-INH, and $11.33 million for ecallantide. CONCLUSIONS: Accounting for patient well-being and additional cost components of HAE attacks generates a better estimation of cost-effectiveness than drug cost alone. Results from this model indicate that rhC1-INH is the dominant treatment option with lower expected costs and higher calculated effectiveness than comparators. Further analyses reinforce the idea that low redose rates contribute to improved cost-effectiveness. DISCLOSURES: Funding support was contributed by Pharming Healthcare. Relan and Adams are employed by Pharming Healthcare. Tyson and Magar are employed by AHRM, which received fees to perform the analysis and develop the manuscript. Bernstein reports grants, personal fees, and nonfinancial support from Shire, CSL Behring, and Pharming Healthcare; grants and personal fees from Biocryst; and nonfinancial support from HAEA, unrelated to this study.

A Predictive Model to Estimate Cost Savings of a Novel Diagnostic Blood Panel for Diagnosis of Diarrhea-predominant Irritable Bowel Syndrome.

PURPOSE: A high incidence of irritable bowel syndrome (IBS) is associated with significant medical costs. Diarrhea-predominant IBS (IBS-D) is diagnosed on the basis of clinical presentation and diagnostic test results and procedures that exclude other conditions. This study was conducted to estimate the potential cost savings of a novel IBS diagnostic blood panel that tests for the presence of antibodies to cytolethal distending toxin B and anti-vinculin associated with IBS-D. METHODS: A cost-minimization (CM) decision tree model was used to compare the costs of a novel IBS diagnostic blood panel pathway versus an exclusionary diagnostic pathway (ie, standard of care). The probability that patients proceed to treatment was modeled as a function of sensitivity, specificity, and likelihood ratios of the individual biomarker tests. One-way sensitivity analyses were performed for key variables, and a break-even analysis was performed for the pretest probability of IBS-D. Budget impact analysis of the CM model was extrapolated to a health plan with 1 million covered lives. FINDINGS: The CM model (base-case) predicted $509 cost savings for the novel IBS diagnostic blood panel versus the exclusionary diagnostic pathway because of the avoidance of downstream testing (eg, colonoscopy, computed tomography scans). Sensitivity analysis indicated that an increase in both positive likelihood ratios modestly increased cost savings. Break-even analysis estimated that the pretest probability of disease would be 0.451 to attain cost neutrality. The budget impact analysis predicted a cost savings of $3,634,006 ($0.30 per member per month). IMPLICATIONS: The novel IBS diagnostic blood panel may yield significant cost savings by allowing patients to proceed to treatment earlier, thereby avoiding unnecessary testing.