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Are NCCN Resource-Stratified Guidelines for Breast Cancer Systemic Therapy Achievable? A Population-Based Study of
Brooke E Wilson1,2, Susannah Jacob1, Viet Do1,3
1Collaboration for Cancer Outcomes, Research and Evaluation, South West Clinical School, University of New South Wales, Liverpool, New South Wales, Australia.
Purpose:
Resource-stratified guidelines (RSG) for cancer provide a hierarchy of interventions, based on resource availability. We quantify treatment need and cost if National Comprehensive Cancer Network (NCCN) RSGs for breast cancer (BC) are adopted globally.
Methods:
We developed decision trees for first-course systemic therapy, merged with SEER and Global Cancer Observatory 2018 incidence data to estimate treatment need and cost if NCCN RSG are implemented globally based on country-level income. Simulations were used to quantify need and cost of globally scaling up services to Maximal.
Results:
Based on NCCN RSG, first-course chemotherapy is indicated in 0% (Basic), 87% (Core), and 86% (Enhanced) but declined to 50% (Maximal) because of incorporation of genomic profiling. First-course endocrine therapy (ET) is indicated in 80% in all settings. In 2018, treatment need was 1.4 million people for chemotherapy, 183,943 for human epidermal growth factor receptor 2 (HER2) therapies and 1.6 million for ET. The cost per person for chemotherapy or HER2 or immunotherapy increased by 17-fold from Core to Maximal ($1,278-$22,313 Australian dollars [AUD]). The cost of ET per person rose eight-fold from Basic to Maximal ($1,236-$9,809 AUD). If all patients with BC globally were treated with Maximal resources, the need for chemotherapy would decline by 28%, whereas cost of first-course treatment would rise by 1.8-fold ($21-$37 billion AUD) because of more costly therapies.
Conclusion:
NCCN RSGs for BC could result in chemotherapy overtreatment in Core and Enhanced settings. The absence of chemotherapy in Basic settings should be reconsidered, and future iterations of RSG should perform cross-tumor comparisons to ensure equitable resource distribution and maximize population-level outcomes. Our model is flexible and can be tailored to the costs, population attributes, and resource availability of any institution or country for health-services planning.
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