Performance Goals for an Adjunct Diagnostic Test to Reduce Unnecessary Biopsies After Screening Mammography: Analysis of Costs, Benefits, and Consequences.

PURPOSE: Because benign biopsies resulting from false-positive mammographic findings are a known harm of breast cancer screening, physicians and test manufacturers are searching for ways to reduce their frequency. The aim of this study was to estimate potential costs and consequences associated with using an adjunct diagnostic test for triaging women with suspicious mammographic findings before biopsy. METHODS: A decision model was developed to compare the use of an adjunct test before biopsy to the current standard of care for suspicious mammographic findings. The decision analysis was performed from the perspective of a national health payer, with a 1-year time horizon among women representative of the US screening population aged 40 to 79 years. Three primary outcomes were assessed: (1) incremental costs, (2) number of benign biopsies avoided, and (3) number of missed opportunities for diagnosing cancer per million women screened. Input parameters were obtained from the medical literature and expert opinion. Sensitivity analyses were performed to evaluate the effects of uncertainty in parameter estimates. RESULTS: The base-case analysis demonstrated that the use of an adjunct diagnostic test with 95% sensitivity, 75% specificity, and a cost of $1,000 would eliminate 8,127 unnecessary breast biopsies per million women screened. However, this would cost the US health care system an additional $6,462,977 and result in 255 missed opportunities for diagnosing cancer per million women screened. CONCLUSIONS: The addition of an adjunct test for triaging women for breast biopsy after abnormal findings on screening mammography would likely eliminate many unnecessary biopsies but also increase overall health care costs. This exploratory analysis highlights the fact that mammography remains a relatively inexpensive and effective breast cancer screening and diagnostic modality.

Economic evaluation of diagnostic localization following biochemical prostate cancer recurrence.

OBJECTIVES: The aim of this study was to assess potential cost-effectiveness of using a prostate cancer specific functional imaging technology capable of identifying residual localized disease versus small volume metastatic disease for asymptomatic men with low but detectable prostate specific antigen (PSA) elevation following radical prostatectomy. METHODS: Markov modeling was used to estimate the incremental impact on healthcare system costs (2012 USD) and quality-adjusted life-years (QALYs) of two alternative strategies: (i) using the new diagnostic to guide therapy versus (ii) current usual care-using a combination of computed tomography, magnetic resonance imaging, and bone scan to guide therapy. Costs were based on estimates from literature and Medicare reimbursement. Prostate cancer progression, survival, utilities, and background risk of all-cause mortality were obtained from literature. Base-case diagnostic sensitivity (75 percent), specificity (90 percent), and cost (USD 2,500) were provided by our industry partner GE Healthcare. RESULTS: The new diagnostic strategy provided an average gain of 1.83 (95 percent uncertainty interval [UI]: 1.24-2.64) QALYs with added costs of USD 15,595 (95 percent UI: USD -6,330-44,402) over 35 years. The resulting incremental cost-effectiveness ratio was USD 8,516/QALY (95 percent UI: USD -2,947-22,372). RESULTS were most influenced by the utility discounting rate and test performance characteristics; however, the new diagnostic provided clinical benefits over a wide range of sensitivity and specificity. CONCLUSION: This analysis suggests a diagnostic technology capable of identifying whether men with biochemical recurrence after radical prostatectomy have localized versus metastatic disease would be a cost-effective alternative to current standard work-up. The results support additional investment in development and validation of such a diagnostic.

Performance goals for an adjunct diagnostic test to reduce unnecessary biopsies after screening mammography: analysis of costs, benefits, and consequences.

PURPOSE: Because benign biopsies resulting from false-positive mammographic findings are a known harm of breast cancer screening, physicians and test manufacturers are searching for ways to reduce their frequency. The aim of this study was to estimate potential costs and consequences associated with using an adjunct diagnostic test for triaging women with suspicious mammographic findings before biopsy. METHODS: A decision model was developed to compare the use of an adjunct test before biopsy to the current standard of care for suspicious mammographic findings. The decision analysis was performed from the perspective of a national health payer, with a 1-year time horizon among women representative of the US screening population aged 40 to 79 years. Three primary outcomes were assessed: (1) incremental costs, (2) number of benign biopsies avoided, and (3) number of missed opportunities for diagnosing cancer per million women screened. Input parameters were obtained from the medical literature and expert opinion. Sensitivity analyses were performed to evaluate the effects of uncertainty in parameter estimates. RESULTS: The base-case analysis demonstrated that the use of an adjunct diagnostic test with 95% sensitivity, 75% specificity, and a cost of $1,000 would eliminate 8,127 unnecessary breast biopsies per million women screened. However, this would cost the US health care system an additional $6,462,977 and result in 255 missed opportunities for diagnosing cancer per million women screened. CONCLUSIONS: The addition of an adjunct test for triaging women for breast biopsy after abnormal findings on screening mammography would likely eliminate many unnecessary biopsies but also increase overall health care costs. This exploratory analysis highlights the fact that mammography remains a relatively inexpensive and effective breast cancer screening and diagnostic modality.

Genetic testing in combination with preventive donepezil treatment for patients with amnestic mild cognitive impairment: an exploratory economic evaluation of personalized medicine.

OBJECTIVE: To evaluate the cost effectiveness of genetic screening for the apolipoprotein (APOE) ε4 allele in combination with preventive donepezil treatment in comparison with the standard of care for amnestic mild cognitive impairment (AMCI) patients in Canada. METHODS: We performed a cost-effectiveness analysis using a Markov model with a societal perspective and a time horizon of 30 years. For each strategy, we calculated quality-adjusted life-years (QALYs), using utilities from the literature. Costs were also based on the literature and, when appropriate, Ontario sources. One-way and probabilistic sensitivity analyses were performed. Expected value of perfect information (EVPI) analysis was conducted to explore the value of future research. RESULTS: The base case results in our exploratory study suggest that the combination of genetic testing and preventive donepezil treatment resulted in a gain of 0.027 QALYs and an incremental cost of $1,015 (in 2009 Canadian dollars [Can$]), compared with the standard of care. The incremental cost-effectiveness ratio (ICER) for the base case was Can$38,016 per QALY. The ICER was sensitive to the effectiveness of donepezil in slowing the rate of progression to Alzheimer's disease (AD), utility in AMCI patients, and AD and donepezil treatment costs. EVPI analysis showed that additional information on these parameters would be of value. CONCLUSION: Using presently available clinical evidence, this exploratory study illustrates that genetic testing combined with preventive donepezil treatment for AMCI patients may be economically attractive. Since our results were based on a secondary post hoc analysis, our study alone is insufficient to warrant recommending APOE genotyping in AMCI patients. Future research on the effectiveness of preventive donepezil as a targeted therapy is recommended.

A review of economic evaluations of genetic testing services and interventions (2004-2009).

To review economic evaluations of genetic interventions published between 2004 and 2009 and assess the quality of the identified studies, we searched for economic evaluations of genetic testing and interventions published between 2004 and 2009. Studies that met inclusion criteria were reviewed and their quality then assessed using a validated instrument-the Quality of Health Economic Studies. Of 54 articles identified, 26 met study criteria and were included in the review. These studies span a number of clinical indications, genetic tests, and interventions, but the majority (92%) focuses on genetic interventions for preventive screening and increasing treatment efficacy. The mean quality score for the reviewed studies was 89.8. Comparison of the quality of different study types revealed that cost-utility studies and studies that used a combined decision tree and Markov model had the highest mean quality scores. Clear statements regarding bias, funding source, and study perspective were commonly lacking in the reviewed studies. Although the reviewed studies were of fairly high quality, we found Quality of Health Economic Studies methodology for grading the quality of economic evaluations challenging and observed no statistically significant improvement in quality of studies between the periods of 1995-2004 and 2004-2009.