Table 3:
Variable Description | Preferred strategy | T1a N0 | T1a N1 | T1a N2 | T1b-T2 N0 | T1b-T2 N1 | T1b-T2 N2 | Population-level model |
---|---|---|---|---|---|---|---|---|
SLNB | $13-$96,593 | $13-$52,000 | NA2 | |||||
SLNB | 0.005–0.10 | 0.005–0.10 | NA2 | |||||
SLNB | 0.4–0.99 | 0.5–0.99 | NA2 | |||||
SLNB | 0.001 −0.20 | 0.001 −0.20 | NA2 | |||||
SLNB | NA1 | 6.0–20 | 1–20 | NA1 | 4.4–20 | 7.7–20 | NA2 | |
SLNB | NA1 | 1.7–20 | 2.9–20 | NA1 | 1.4–20 | 2.4–20 | NA2 | |
SLNB | 0.2–0.9 | NA2 | ||||||
SLNB | 0.2–0.9 | NA2 | ||||||
SLNB | NA3 | NA3 | NA3 | NA3 | NA3 | NA3 | ||
SLNB | NA3 | NA3 | NA3 | NA3 | NA3 | NA3 | ||
SLNB | $50,000-$150,000 | $65,000-$150,000 |
Key variables were presented based on their clinical relevance and notable impact on the model (variables not included in the figure did not have a significant impact on model results). Results of key 1-way sensitivity analyses shown above: each input variable varied within the range of values specified in Table 1, keeping all other variables at their baseline value. In the green cells, all input values listed resulted in NMB observation > NMB SLNB, i.e., observation was superior to SLNB. In the red cells, all input values listed resulted in NMB observation < NMB SLNB, i.e., SLNB was superior to observation. For a majority of variables, the conclusion was consistent: observation after negative AUS is the optimal strategy for axillary staging.
NA1: Multipliers for breast cancer recurrence given unrecognized nodal disease (false-negative AUS or SLNB) were not applicable to N0 models.
NA2: Variables in the stage-specific models were not used in the population-level model, and therefore not applicable for sensitivity analyses at the population level.
NA3: The false-negative rates of axillary ultrasound were used only in the population-level model, and therefore not applicable for sensitivity analyses in the stage-specific models.
NMB: Net monetary benefit, SLNB: sentinel lymph node biopsy, AUS: axillary ultrasound, $: US dollars
NMB Observation > NMB SLNB (Observation preferred) for the range of values listed
NMB Observation < NMB SLNB (SLNB preferred) for the range of values listed