Modeling the cost-effectiveness of granulocyte colony-stimulating factor use in early-stage breast cancer

To model the cost-effectiveness (CE) of granulocyte colony-stimulating factor (G-CSF) in early-stage breast cancer when its use is directed to those most in need of the medication.

A conditional CE model was developed for the use of G-CSF based on a ranking of patient need as determined by patient blood counts during the first cycle of chemotherapy. In the base case, no G-CSF was used. In the alternative case, G-CSF was used in the following manner. If the risk of a neutropenic event (as defined by a predictive model based on nadir absolute neutrophil count [ANC] and hemoglobin decrease in cycle 1) was equal to or exceeded a predetermined critical value "T," then patients would receive G-CSF in cycles 2 through 6 of chemotherapy. If the risk of an event was less than T, patients would not use G-CSF unless an event occurred, at which time G-CSF would be administered with every subsequent cycle.

A decision rule (T) that would allow the most needy 50% of early-stage breast cancer patients to receive G-CSF after the first cycle of chemotherapy resulted in a CE ratio of $34,297 dollars per life-year saved (LYS). If only the most needy 10% of patients received G-CSF, then the associated CE ratio was $23,748/LYS; if 90% of patients could receive the medication, the CE ratio would be $76,487/LYS. These estimates were relatively insensitive to inpatient hospital cost estimates (inpatient costs for fever and neutropenia of $3,090 to $7,726 per admission produced dollar per LYS figures of $34,297 to $32,415, respectively). However, the model was sensitive to assumptions about the shape of the relationship between dose reduction and disease-free survival (DFS) at 3 years.

Providing G-CSF to the neediest 50% of early-stage breast cancer patients (as defined by first-cycle blood counts) starting after the first cycle of chemotherapy is associated with a CE ratio of $34,297/LYS, which is well in the range of CE ratios for treatment of other common medical conditions. Furthermore, conditional CE studies, based on predictive models that incorporate individual patient risk, allow one to define populations for which therapy is, or is not, cost-effective. Limitations of our present understanding of the shape of the chemotherapy dose-response curve, especially at low levels of dose reductions, affect these results. Further work is required to define the shape of the dose-response curve in early-stage breast cancer.