Markov Model and Cost-Effectiveness Analysis of Bevacizumab in HER2-Negative Metastatic Breast Cancer

Purpose: Metastatic breast cancer (MBC) remains an incurable disease despite advances in treatment modalities. In 2008, the FDA approved bevacizumab with paclitaxel for the initial treatment of HER2-negative MBC. The approval was then officially revoked by the FDA in November 201 L However, both the European Medicines Agency and NCCN still endorse bevacizumab for this indication. One of the greatest challenges facing health care worldwide is reconciling incremental clinical benefits with exponentially rising costs. This study aimed to assess the cost-effectiveness of bevacizumab with paclitaxel for HER2-negative MBC. Methods: A Markov decision tree using Data 3.5 (TreeAge Software Inc.) was created for decision and cost-effectiveness analyses of using bevacizumab plus paclitaxel versus paclitaxel alone as first-line chemotherapy in HER2-negative MBC using efficacy and toxicity data from the E2100 study. The model was designed from the patient and payer perspectives and sensitivity analyses were run. Results: The marginal cost between paclitaxel alone versus bevacizumab and paclitaxel was 86k with a marginal efficacy of 0.369 quality-adjusted life-years and marginal cost effectiveness of 232,720.72 USD. The expected outcome value was 1.86 for bevacizumab and paclitaxel and 1.67 for paclitaxel. alone. The combination was not cost effective and only a marginal survival advantage was observed. Conclusions: This study demonstrates that, despite a significant progression-free survival advantage, the addition of bevacizumab to paclitaxel is not cost effective for the cohort of patients with HER2-negative MBC included in our analysis. Such data could be informative to policymakers who consider the health economics and incremental cost-effectiveness of medical therapies.