(297) Assessing the Cost-Utility of Predictive Biomarkers in Oncology Treatment Compared to Traditional Approaches

Background: : The integration of predictive biomarkers into oncology has the potential to revolutionize cancer treatment by enabling personalized therapy and improving clinical outcomes. However, the economic value of these targeted strategies remains a subject of debate. This study aims to assess the cost-utility of predictive biomarker-guided treatments versus traditional, non-targeted therapies in oncology, using quality-adjusted life years (QALYs) as a measure of effectiveness.

Objective: : To assess the cost-utility of predictive biomarker-guided treatments compared to traditional, non-targeted oncology therapies using quality-adjusted life years (QALYs) as the primary measure of effectiveness.

Methods: : A systematic review and meta-analysis were conducted using data from published cost-utility analyses between 2015 and 2024. Studies were included if they compared predictive biomarker-guided cancer treatments to standard care and reported incremental cost-effectiveness ratios (ICERs) in terms of cost per QALY gained. Data were extracted on cancer type, biomarker used, treatment type, and healthcare system perspective. A pooled analysis was performed to estimate the average ICER across studies, and a subgroup analysis assessed differences by cancer type and biomarker class.

Results: : Out of 48 eligible studies, 32 met the inclusion criteria, representing biomarker applications in lung, breast, colorectal, and melanoma cancers. The pooled mean ICER for biomarker-guided therapy was $76,200/QALY, compared to $112,500/QALY for traditional treatments, indicating greater cost-effectiveness for personalized approaches. Biomarker strategies were most cost-effective in non-small cell lung cancer (NSCLC) involving EGFR and ALK mutations. Sensitivity analysis confirmed robustness across different healthcare system perspectives and willingness-to-pay thresholds.

Conclusions: : Predictive biomarker-guided therapies in oncology demonstrate superior cost-utility compared to traditional treatments, particularly in cancers with well-validated biomarkers. These findings support broader implementation of precision medicine strategies to enhance patient outcomes and healthcare system sustainability. Future research should focus on emerging biomarkers and the real-world cost-effectiveness of these biomarkers to inform clinical and policy decision-making.

Sponsorship:: Citrus Health Group