Differences in the Selection of Health State Utility Values by Sponsorship in Published Cost-Effectiveness Analyses

Abstract

Background Health state utility values (HSUVs) are among the most influential attributes of cost-effectiveness analyses (CEAs). Our objective was to evaluate whether industry-funded studies select systematically different HSUVs as compared with studies without industry funding. Methods Among 10 diseases with high disease burden in the United States, we further identified 31 progressive health states. We then searched the Tufts Medical Center’s CEA Registry to identify studies that included HSUVs and were submitted to the registry between 2002 and 2019. Two reviewers mapped the free-text descriptions of health states onto the 31 predefined health states. We analyzed the effect of industry funding on the point estimates of these HSUVs with a beta regression. We also analyzed the difference between related health states within studies by funding source with a linear regression. Results After identifying 26,222 HSUVs from 4198 CEAs, we matched 2573 HSUVs to the 31 predefined health states. We observed large variations within each health state: 12 of 31 health states included a range of HSUVs greater than 0.5. The point estimate model showed 1 statistically significant difference of 31 comparisons between studies with any industry funding and those without. The utility difference model found 3 significant differences out of 39 comparisons between CEAs with any industry funding and those without. Limitations Inclusion of unpublished CEAs may have affected our conclusions about the effect of industry funding on selection of HSUVs. We also relied on free-text descriptions of health states available in the CEA Registry and did not include adjustment for multiple comparisons. Conclusion Limited evidence exists that industry-funded studies select different HSUVs compared to non-industry-funded studies for the health states we considered.

Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Explanation and Elaboration: A Report of the ISPOR CHEERS II Good Practices Task Force

“…Funding relationships in economic evaluation have been shown to correlate with the direction of findings. [154][155][156][157][158][159][160][161] Authors should describe any relationship of the funders to other organizations or individuals with a financial or other interest in the work including nonmonetary sources of support. If no funding or nonmonetary support was received, authors should so state.…”

Industry sponsorship bias in cost effectiveness analysis: registry based analysis

“…Model-based analyses often require inputs from multiple, heterogeneous sources to make long term extrapolations or projections. Industry sponsored studies tended to choose inputs to generate cost effectiveness results in favour of their products 1617. This highlights that systematically identifying and choosing from published data with full transparency and justification is critical to minimise the bias in conducting model-based CEAs 18…”