OBJECTIVES: Several new interventions have become available recently for the adjuvant treatment of early breast cancer (EBC) which are effective in reducing the incidence of disease relapse. Our objective was to develop a model to evaluate the cost-effectiveness and cost-utility of such interventions in the USA. The model was demonstrated for the comparison of docetaxel (75mg/m2), doxorubicin (50mg/m2), and cyclophosphamide (500mg/m2) (TAC, 6 cycles) with fluorouracil (500mg/m2) , doxorubicin (50mg/m2) , and cyclophosphamide (500mg/m2) (FAC, 6 cycles) in node-positive EBC patients.
METHODS: A combined decision tree and Markov model estimated costs and outcomes from initiation of adjuvant chemotherapy to death. Parametric survival functions were fitted to patient-level data from trial BCIRG 001 and time-dependent transition probabilities for disease relapse were estimated. Costs were estimated from US databases (Pharmetrics claims database and Premier hospital database) and a published retrospective analysis of linked SEER-Medicare data for 1580 EBC patients with disease recurrence (cost year 2008). Utility weights were estimated from EORTC QLQ-C30 data collected in trial BCIRG 001 using a published algorithm, and from published literature. Probabilistic and univariate sensitivity analysis (varying all parameters by +/- 50% of base-case values) were performed. Alternative scenarios were programmed to explore uncertainty beyond the trial follow-up period.
RESULTS: Mean total expected lifetime costs and outcomes were significantly higher for the TAC cohort. Incremental costs were $19,732 (95% CIs $15,869-$31,441); life years were 0.93 (0.87-0.97) and QALYs were 0.74 (0.44-0.91). Incremental cost-effectiveness ratios for TAC versus FAC were $21,318 per life year saved ($16,953-$33,856) and $26,654 per QALY ($18,553-$50,554). In univariate sensitivity analysis, results were most sensitive to the utility weight for remission postchemotherapy. The incremental cost per QALY remained below $50,000 for all plausible parameter estimates, and all extrapolation scenarios.
CONCLUSIONS: The model provides a robust framework for estimating cost-effectiveness, allowing exploration of critical areas of uncertainty.
