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The Economic Impact of Genomic Testing in Breast Cancer

Dinan, Michaela A. PhD

doi: 10.1097/01.COT.0000559641.38121.c4
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Few medical tests have had such a large impact on personalized oncology care in the genomic era than that of the Oncotype DX (ODX) 21-gene recurrence score assay. Prior to the introduction of ODX, oncologists were presented with a dilemma in the management of women with localized, hormone receptor-positive breast cancers. The challenge was that some women, despite optimal surgery and radiation therapy, would still succumb to distant metastatic disease years after their initial diagnosis. The only effective means to reduce the incidence of these events was to treat all but the smallest tumors with adjuvant chemotherapy, because they were unable to identify which women could safely forgo chemotherapy despite repeated attempts to identify such a subgroup.

In 2004, ODX was prospectively validated as a means of predicting the risk of distant metastatic disease at 10 years (N Engl J Med 2004;351(27):2817-2826). In 2006, a study demonstrated that ODX could predict that only women with high genomic risk score (RS) would experience a benefit from chemotherapy, and roughly half of all women tested who had low RSs did not benefit from chemotherapy (J Clin Oncol 2006;24(23):3726-3734).

This concept initiated a wave of excitement in the oncology community due to the idea that, unlike most additive medical technologies, ODX might be able to reduce the receipt of unnecessary treatment. More exciting still was the idea that ODX could both improve quality and decrease costs at the same time.

ODX Testing Costs

Many studies investigated the economic impact of ODX testing. Although there are too many to describe in detail, what perhaps is most noteworthy is the substantial variability between study results. A systematic analysis in the Journal of Clinical Oncology showed a wide range of predicted ODX economic impact of ODX testing (2018; doi:10.1200/JCO.2017.76.5941).

Some analyses reported that ODX was cost-saving, while others suggested the test to be merely cost-effective. What remained clear was that these modeling studies involved many subjective parameter estimates that could dramatically impact the extent to which ODX appeared to be cost-saving or cost-effective.

Given the inherent difficulties and inconsistencies observed between these models of ODX use, other methods are also needed to investigate the true impact of ODX testing on the overall breast cancer patient population within the U.S. Dinan et al, conducted one such analysis published in JNCCN—Journal of the National Comprehensive Cancer Network (2019;17(3):245-254).

In this study, researchers set out to assess what the real-world impact of ODX testing was in everyday practice with respect to chemotherapy costs. To do this they conducted a SEER-Medicare data analysis, which contains cancer registry data from the SEER (Surveillance, Epidemiology, and End Results) registry matched with Medicare claims for beneficiaries aged 66 and older.

Patient clinical variables (tumor size, lymph node status, hormone receptor status, etc.) were derived from the SEER-registry data and additional information on treatment and costs (chemotherapy, surgery, radiation, inpatient/outpatient, etc.) were derived from linked Medicare claims. Costs were derived from Medicare payments and did not take into account lost wages or other societal costs.

The final study population included approximately 30,000 women with localized, hormone receptor-positive breast cancer with mean 1-year total all-cause medical costs of $36,000. As expected, women with high-risk tumors such as tumor size and the presence of lymph nodes were associated with higher costs. The average 1-year costs for women were $51,100 for high-risk, $33,200 for intermediate-risk, and $26,700 for low-risk disease. Total chemotherapy costs followed similar trends.

The initial hypothesis of the study was that receipt of ODX would be associated with overall lower costs of medical care due to decreased use and associated cost of chemotherapy. However, the authors found that only high-risk patients (i.e., lymph node-positive) showed a clear association with receipt of ODX and decreased chemotherapy costs. In these high-risk patients, receipt of ODX was associated with a 12 percent relative reduction in total costs, or an average absolute reduction of $6,600.

The team did not observe lower costs associated with ODX receipt in low- and intermediate-risk patients (i.e., lymph node-negative, hormone receptor-positive tumors). In fact, receipt of ODX in these patients was associated with higher overall costs. However, this appeared to speak more to the overall increased costs of non-chemotherapy related medical care. In other words, in patients with low or intermediate-risk disease, receipt of ODX testing was also associated with other, non-chemotherapy related medical testing or treatment.

The primary contribution of this study is that it provides some of the first data on real-world oncology practices and the association of ODX with medical costs. Although ODX testing was associated with higher overall costs in intermediate-risk and low-risk disease, these costs were almost entirely attributable to higher non-cancer costs with no differences in mean chemotherapy costs.

Key Takeaways

There are three key take-home points from this study. The first is that in response to the direct question investigated, the authors found that receipt of ODX was only associated with decreased costs in high-risk patients. Second, at a population level, the overall impact of ODX testing on chemotherapy costs is strongly influenced by the use of chemo in the absence of testing (i.e., the utilization of chemo that would occur without ODX).

In other words, the overall economic benefit of introducing ODX testing is critically dependent on what proportion of patients received chemotherapy prior to the introduction ODX. This means that introduction of ODX would be most likely to reduce chemotherapy rates when introduced into a region with high chemotherapy utilization rates, such as those that are younger in age, otherwise healthier, or counterintuitively could also include regions or populations faced with low screening rates or barriers to regular health care access.

Lastly, receipt of ODX is also associated with other increased, non-chemotherapy related costs. Another way to phrase this is to say that, in general, patients who underwent ODX testing were also more likely to undergo other testing and medical care (e.g., imaging, hospitalization, etc.). This point is important in considering the impact of any adopted test or medical technology and provides an important caveat to the oncologic community when trying to retrospectively assess the impact of new treatments or tests.

Limitations & Future Directions

The key limitations of this study are the retrospective nature of the analysis and that only direct Medicare payments were used to calculate costs, which did not include lost wages or other more holistic social examinations (i.e., caretaker costs).

Lastly, it should be noted that this study was limited to Medicare beneficiaries and therefore all patients had to be at least 65 years old to be included. Because chemotherapy is less likely to be used women, this study likely underestimates the potential impact of ODX on reducing chemotherapy use in the overall population and especially younger women.

Taken together, our results support the ability of ODX testing to reduce chemotherapy costs in real-world practice among patients for whom receipt of chemotherapy is the default treatment paradigm. However, blanket use of ODX testing outside recommended settings, for example, in those with low-risk disease (tumors < 0.5 cm), should be cautioned that such use may actually increase health care utilization and costs.

Further research is warranted to fully understand the impact of ODX and other genomic testing in real-world practice.

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Michaela A. Dinan, PhD
Michaela A. Dinan, PhD:
MICHAELA A. DINAN, PHD, is Assistant Professor in Population Health Sciences and Assistant Professor in Medicine at Duke University.
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