Cost and Cost-Effectiveness of Treating Human Epidermal Growth Factor Receptor 2–Low Metastatic Breast Cancer
Abstract
PURPOSE Creating value-aligned treatment pathways in breast cancer requires understanding the cost and cost-effectiveness of new therapies. To address uncertainty in the optimal treatment sequence, we developed a decision model to assess the cost-effectiveness of various treatment sequences for patients with human epidermal growth factor receptor 2 (HER2)–low metastatic breast cancer who are eligible for trastuzumab deruxtecan (T-DXd) and sacituzumab govitecan (SG) under current US Food and Drug Administration labeling. METHODS We derived disease progression and therapy data from the Destiny-Breast04 trial and sourced cost and quality-of-life data from the published literature. Our simulation modeled 57-year-old women with HER2-low, endocrine refractory, and triple-negative metastatic breast cancer eligible for third-line treatment. We evaluated four sequences: chemotherapy (chemo) → chemo, T-DXd → chemo, chemo → T-DXd, and T-DXd → SG. Outcomes included quality-adjusted life years (QALYs), total lifetime costs (2020 US dollars [USD], 3% annual discount), and incremental cost-effectiveness ratios. Sequences that cost <$150,000 USD to gain an additional QALY were considered cost effective. RESULTS Chemo → chemo has the lowest cost at $176,000 (USD) per patient and yields 0.82 QALYs. T-DXd → chemo costs $282,000 (USD) and yields 1.08 QALYs, with an incremental cost-effectiveness ratio of $408,000 (USD) per QALY gained. T-DXd → SG costs $304,000 (USD) and yields 1.09 QALYs, with an incremental cost-effectiveness ratio of $2,200,000 (USD) per QALY gained. Drug cost drives the cost differences between each strategy. For T-DXd → chemo to be cost effective at the $150,000 (USD) per QALY threshold, we estimate that a 41% price reduction for T-DXd is needed. CONCLUSION At its current price, T-DXd is not cost effective for HER2-low metastatic breast cancer. Price reductions can make this drug cost effective. Optimal value-based sequencing in this patient population uses a single antibody-drug conjugate rather than back-to-back conjugates.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (9)
James C. Dickerson
James C. Dickerson, MD, MS, Jennifer L. Caswell-Jin, MD, and Fauzia Riaz, MD, MHS, Department of Medicine (Hematology and Oncology), Stanford University, Stanford, CA; and Jeremy D. Goldhaber-Fiebert, PhD, and Fernando Alarid-Escudero, PhD, Department of Health Policy, Stanford University, Stanford, CA
Marcus T. Moen
Department of Management Science and Engineering, Stanford University, Stanford, CA
Perry Nielsen
Department of Health Policy, Stanford University, Stanford, CA
Fauzia Riaz
Stanford Cancer Institute, Stanford, CA
Edward Tran
Department of Management Science and Engineering, Stanford University, Stanford, CA
Jennifer L. Caswell-Jin
Wesley Suen
Department of Health Policy, Stanford University, Stanford, CA
Jeremy D. Goldhaber-Fiebert
James C. Dickerson, MD, MS, Jennifer L. Caswell-Jin, MD, and Fauzia Riaz, MD, MHS, Department of Medicine (Hematology and Oncology), Stanford University, Stanford, CA; and Jeremy D. Goldhaber-Fiebert, PhD, and Fernando Alarid-Escudero, PhD, Department of Health Policy, Stanford University, Stanford, CA
Fernando Alarid-Escudero
James C. Dickerson, MD, MS, Jennifer L. Caswell-Jin, MD, and Fauzia Riaz, MD, MHS, Department of Medicine (Hematology and Oncology), Stanford University, Stanford, CA; and Jeremy D. Goldhaber-Fiebert, PhD, and Fernando Alarid-Escudero, PhD, Department of Health Policy, Stanford University, Stanford, CA