PURPOSE: Gene expression profiling has been proposed as an alternative to clinical guidelines to identify high-risk patients for adjuvant chemotherapy. However, the outcomes associated with gene expression profiling are not clear, and guidelines for the appropriate use of genomic technologies have not been established. METHODS: We developed a decision analytic model to evaluate the incremental cost and quality-adjusted life years of gene expression profiling versus NIH clinical guidelines in a hypothetical cohort of premenopausal early stage breast cancer patients 44 years of age. We conducted empirical analyses and identified literature-based data to inform the model, and performed probabilistic sensitivity analyses to evaluate uncertainty in the results. We interpreted the implications of our findings for treatment guidelines and policies. RESULTS: Use of gene expression profiling resulted in an absolute 5% decrease in the proportion of cases of distant recurrence prevented, 0.21 fewer quality-adjusted life years, and a cost savings of USD 2882. The chosen test cutoff value to identify a tumor as poor prognosis and the cost of adjuvant chemotherapy were the most influential parameters in the analysis, but our findings did not change substantially in sensitivity analyses. Regardless of the test cutoff used to identify a poor prognosis tumor, the gene expression profiling assay studied in our analysis, at its current level of performance, did not attain the threshold sensitivity (95%) necessary to produce equal or greater quality-adjusted life years than NIH guidelines. CONCLUSION: Although the use of gene expression profiling in breast cancer care holds great promise, our analysis suggests additional refinement and validation are needed before use in clinical practice.
PURPOSE: Gene expression profiling has been proposed as an alternative to clinical guidelines to identify high-risk patients for adjuvant chemotherapy. However, the outcomes associated with gene expression profiling are not clear, and guidelines for the appropriate use of genomic technologies have not been established. METHODS: We developed a decision analytic model to evaluate the incremental cost and quality-adjusted life years of gene expression profiling versus NIH clinical guidelines in a hypothetical cohort of premenopausal early stage breast cancerpatients 44 years of age. We conducted empirical analyses and identified literature-based data to inform the model, and performed probabilistic sensitivity analyses to evaluate uncertainty in the results. We interpreted the implications of our findings for treatment guidelines and policies. RESULTS: Use of gene expression profiling resulted in an absolute 5% decrease in the proportion of cases of distant recurrence prevented, 0.21 fewer quality-adjusted life years, and a cost savings of USD 2882. The chosen test cutoff value to identify a tumor as poor prognosis and the cost of adjuvant chemotherapy were the most influential parameters in the analysis, but our findings did not change substantially in sensitivity analyses. Regardless of the test cutoff used to identify a poor prognosis tumor, the gene expression profiling assay studied in our analysis, at its current level of performance, did not attain the threshold sensitivity (95%) necessary to produce equal or greater quality-adjusted life years than NIH guidelines. CONCLUSION: Although the use of gene expression profiling in breast cancer care holds great promise, our analysis suggests additional refinement and validation are needed before use in clinical practice.
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