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Published on: July 3, 2020
Differences in Incremental Cost-Effectiveness Ratios for Common Versus Rare Conditions: A Case from Oncology
Kavisha Jayasundara1, Murray Krahn2,3,4, Muhammad Mamdani2,5,4
1Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada. Kavisha.jayasundara@mail.utoronto.ca.
Background:
Incremental cost-effectiveness ratios (ICERs) are used to assess the value for money of new drugs. Many believe that ICERs for drugs that treat rare diseases are much higher than those of common drugs. Our objective was to compare the proportion of ICERs that are cost effective for rare and common cancers.
Methods:
We used the Tufts Medical Center Cost-Effectiveness Analysis (CEA) Registry to identify cost-effectiveness studies of pharmaceutical interventions for cancers. Studies that assessed FDA-approved 'orphan drugs' were categorized as assessing rare cancers. The proportion of common and rare cancer drugs that were cost effective at various ICER thresholds were compared along with study characteristics. Logistic regressions were conducted to assess important predictors of cost effectiveness.
Results:
We identified 303 studies that reported 701 ICERs. Seventy nine percent (n = 240) of studies evaluated drugs for common cancers. At a threshold of US$50,000/QALY, 58% (n = 321) of ICERs for drugs treating common cancers and 64% (n = 94) of ICERs for drugs treating rare cancers were cost effective (p = 0.23). At US$100,000/QALY, 74% (n = 409) of ICERs for common cancers and 78% (n = 115) of ICERs for rare cancers were cost effective (p = 0.35). Results from the logistic regressions demonstrated that rarity was not a statistically significant predictor of cost effectiveness at both thresholds with publication year, study sponsorship, and cancer type as covariates.
Conclusions:
The proportion of ICERs that were cost effective at both thresholds does not appear to be significantly different between the two groups. Rarity is not statistically significantly associated with cost effectiveness, even when adjusted for important covariates.
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