Background: Globally in 2018,1,399,529 breast cancer patients had an indication for first-course chemotherapy using best-practice guidelines. However, these best-practice guidelines do not account for resource limitations. This study estimates global demand for first-course chemotherapy, HER-2 and endocrine therapy if treatment was delivered according to National Comprehensive Cancer Network (NCCN) resource stratified guidelines.
Methods: We developed decision trees for first-course chemotherapy, HER-2 and endocrine therapy using NCCN resource stratified guidelines. For each country, the level of income was matched to the appropriate NCCN resource stratified guideline (Basic for low income, Core for low-middle income, Enhanced for upper-middle income and Maximal for high income). The calculated utilisation rates were then merged with country level data from GLOBOCAN 2018 on breast cancer incidence.
Results: Of the 2,072,659 incident cases of breast cancer diagnosed worldwide in 2018, 67% (1,388,681) had an indication for first-course chemotherapy based on NCCN resource stratified guidelines (0 in low income, 371,343 in low-middle income, 618,792 in upper-middle income, and 403,528 in high income countries). By 2040, demand for first-course chemotherapy will rise to 1,874,661. Using the NCCN Core and Enhanced guidelines, 84% of patients have an indication for chemotherapy compared to 49% using Maximal guidelines due to the incorporation of OncotypeDx. Demand for endocrine therapy was 76% in all resource settings (1,575,220 in 2018 and 2,126,480 in 2040). According to the guidelines, HER-2 targeted therapies are only indicated in Enhanced (upper-middle) and Maximal (high income) settings. Globally, demand for HER-2 targeted therapy was 9% (186,539) in 2018 and 8% (223,840) in 2040.
Conclusion: Paradoxically, chemotherapy demands are higher at a population level using NCCN Core and Enhanced guidelines compared to Maximal. Reassessment of the guidelines to help select patients most likely to benefit from chemotherapy in low and middle-income settings would optimise the use of limited resources.