Identifying a Single Optimal Integrated Cervical Cancer Prevention Policy in Norway: A Cost-Effectiveness Analysis

Background Interventions targeting the same disease but at different points along the disease continuum (e.g., screening and vaccination to prevent cervical cancer [CC]) are often evaluated in isolation, which can affect cost-effectiveness profiles and policy conclusions. We evaluated nonavalent human papillomavirus (HPV) vaccine (9vHPV) compared with bivalent HPV vaccine (2vHPV) alongside deintensified screening intervals for a vaccinated birth cohort to inform a single optimal integrated CC prevention policy. Methods Using a multimodeling approach, we evaluated the health and economic impacts of alternative CC screening strategies for a Norwegian birth cohort eligible for HPV vaccination in 2021 assuming they received 1) 2vHPV or 2) 9vHPV. We conducted 1) a restricted analysis that evaluated the optimal HPV vaccine under current screening guidelines; and 2) a comprehensive analysis including alternative screening and vaccination strategy combinations. We calculated incremental cost-effectiveness ratios (ICERs) and evaluated them according to different cost-effectiveness thresholds. Results Assuming a cost-effectiveness threshold of $40,000 per quality-adjusted life year (QALY) gained, we found that, while holding screening intensity fixed, switching the routine vaccination program in Norway from 2vHPV to 9vHPV would not be considered cost-effective (ICER of $132,700 per QALY gained). However, when allowing for varying intensities of CC screening, we found that switching to 9vHPV would be cost-effective compared with 2vHPV under an alternative threshold of $55,000 per QALY gained, if coupled with reductions in the number of lifetime screens. Conclusions Our analysis highlights the importance of evaluating the full potential policy landscape for country-level decision makers considering policy adoption, including nonindependent primary and secondary prevention efforts, to draw appropriate conclusions and avoid sub-optimal outcomes.