Breast Cancer Research and Treatment

, Volume 139, Issue 3, pp 621–637 | Cite as

Multigene assays and molecular markers in breast cancer: systematic review of health economic analyses

  • Roman Rouzier
  • Paolo Pronzato
  • Elisabeth Chéreau
  • Josh Carlson
  • Barnaby Hunt
  • William J. ValentineEmail author
Open Access


Breast cancer is the most common female cancer and is associated with a significant clinical and economic burden. Multigene assays and molecular markers represent an opportunity to direct chemotherapy only to patients likely to have significant benefit. This systematic review examines published health economic analyses to assess the support for adjuvant therapy decision making. Literature searches of PubMed, the Cochrane Library, and congress databases were carried out to identify economic evaluations of multigene assays and molecular markers published between 2002 and 2012. After screening and data extraction, study quality was assessed using the Quality of Health Economic Studies instrument. The review identified 29 publications that reported evaluations of two assays: Oncotype DX® and MammaPrint. Studies of both tests provided evidence that their routine use was cost saving or cost-effective versus conventional approaches. Benefits were driven by optimal allocation of adjuvant chemotherapy and reduction in chemotherapy utilization. Findings were sensitive to variation in the frequency of chemotherapy prescription, chemotherapy costs, and patients’ risk profiles. Evidence suggests that multigene assays are likely cost saving or cost-effective relative to current approaches to adjuvant therapy. They should benefit decision making in early-stage breast cancer in a variety of settings worldwide.


Breast cancer Gene expression profiling Gene assay Molecular diagnostic techniques Health economics Cost-effectiveness 



Estrogen receptor


Health Technology Assessment


Lymph node


Medical subject heading


Multigene assay


National Comprehensive Cancer Network


National Institute for Health and Clinical Excellence


National Institutes of Health


Quality-adjusted life expectancy


Quality-adjusted life year


Quality of Health Economic Studies


Quality of life


San Antonio Breast Cancer


Breast cancer places a substantial burden on healthcare providers and is associated with significant mortality and reduced quality of life (QoL) [1, 2, 3, 4, 5]. Currently, following curative-intent, patients typically undergo adjuvant treatment consisting of radiotherapy, systematic treatment (if the tumor is sensitive), human-epidermal-growth-factor-receptor-2 (HER2)-directed therapy (if HER2 is overexpressed), and often chemotherapy. The aim is to avoid cancer recurrence and improve overall survival. Clinicians face difficult decisions when prescribing adjuvant therapy, particularly with regard to chemotherapy, balancing the benefit in terms of reduced risk of recurrence, and improved survival with the adverse effects of treatment. Current guidelines recommend chemotherapy in the majority of early-stage breast cancer patients.

Recent development of commercially available multigene assays (MGAs) may represent an opportunity to identify patients who will and will not benefit from chemotherapy, and adapt prescriptions accordingly. MGAs quantify the expression of genes associated with the underlying tumor biology and long-term outcomes [6, 7, 8]. Assays have proved to be prognostic and there are data supporting prediction of chemotherapy benefit [9, 10]. MGAs have been included in the major international guidelines for adjuvant breast cancer treatment in recent years [11, 12, 13, 14]. This systematic review summarizes the available evidence from health economic analyses on MGAs and molecular markers in breast cancer.

Literature search

Articles evaluating the economic impact of commercially available MGAs and protein expression profiling on prescriptions of adjuvant systemic therapy in breast cancer were identified via a literature search. The tests included were technologies under consideration by NICE in a recent scoping exercise (Oncotype DX®, MammaPrint, Blueprint, PAM50, Breast Cancer Index, Mammostrat, and NPI+) [15, 16]. The target population was considered to be all early-stage, nonmetastatic breast cancer patients who underwent curative-intent surgery.

Literature search of PubMed and the Cochrane Library used medical subject heading (MeSH) major topics and a number of “title and abstract” searches combined with Boolean operators, to identify economic evaluations of molecular diagnostic tests published between 1/1/2002 and 1/7/2012 [17]. Hand searches of PubMed identified recently published articles without assigned MeSH terms. HTA authority websites of the UK, Canada, Australia, and USA were searched for any reports containing economic models pertinent to this review. Meeting presentations between 2009 and 2012 were also searched (Appendix).

Citations were screened by title and abstract against inclusion criteria to identify publications assessing the cost-effectiveness or budget impact of prognostic MGAs and molecular markers. Full text was obtained for publications not clearly classified by abstract review. From included articles, data were extracted on the methodological characteristics and results of the publications. Methodological data included the country setting, year of analysis, modeling approach, time horizon, population, outcomes reported, and data sources used. Extracted results data were clinical outcomes, cost outcomes, and cost-effectiveness results. In addition, studies evaluating budget impact were included, defined as the estimation of the financial consequences of introducing new healthcare interventions for a defined healthcare payer or system.

The validated [18, 19] Quality of Health Economic Studies (QHES) instrument was used to evaluate the quality of economic evaluations. The QHES instrument consists of 16 criteria addressing methodological characteristics and transparency of reporting, and against which economic evaluations are compared.


Study selection

From 572 unique articles, screening identified 14 publications assessing the economic impact of using MGAs to guide adjuvant breast cancer therapy. Hand searching of PubMed identified four additional articles that had not yet been assigned MeSH terms and the congress database search yielded 14 pertinent abstracts. Of these, two studies were described in journal articles already identified and were therefore excluded. One further article was excluded following full text review because no price for the genomic-profiling test was included [20]. Consequently, the 29 studies reviewed here comprise 17 journal published manuscripts and 12 abstracts (Fig. 1). Of the identified studies, the majority compared a MGA with current practice, either Adjuvant!, St. Gallen or NCCN guidelines. Oncotype DX® was the test most commonly evaluated, with 18 cost-effectiveness analyses and four budget impact studies comparing it with current practice [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]. Of the remaining studies, four cost-effectiveness evaluations and one budget impact study compared MammaPrint with current practice, and two studies compared Oncotype DX® with MammaPrint [43, 44, 45, 46, 47, 48, 49]. Table 1 provides a brief description of Oncotype DX® and MammaPrint, the two tests with identified published economic literature for review.
Fig. 1

CONSORT flow diagram of literature review

Table 1

Description of interventions included in the review


Level of supporting clinical evidence

Description, prognostic and predictive ability

Oncotype DX®

9 studies on analytical validation

8 publications describing clinical validation, of which 7 studies provided evidence on the prognostic ability, 1 study provided data on predictive ability and 1 study provided results on both

11 publications on decision impact studies

The assay evaluates the expression of a panel of 21 genes from a tumor specimen (biopsy) using a high-throughput, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) method to measure levels of gene expression. The gene expression results from the assay are combined into a single score called the Recurrence Score, which corresponds to a point estimate of the 10-year risk of distant recurrence with a 95 % confidence interval for an individual patient (expressed as a value between 0 and 100).

Seven clinical trials have shown that Oncotype DX® provides a reliable evaluation of the risk of distant recurrence in early-stage breast cancer patients. Studies have shown that low Recurrence Score disease is associated with both a lower risk of distant recurrence (as well as little (or no) chemotherapy benefit). From a physician-patient perspective, the risk of distant recurrence (based on the Recurrence Score) may directly influence chemotherapy decision-making, with patients showing a high risk of recurrence choosing adjuvant chemotherapy. For patients with Recurrence Scores in the intermediate range (between 18 and 30), having a risk of recurrence in the upper end of the intermediate range may lead to an increased interest in choosing chemotherapy compared with having a risk of recurrence in the lower end of the intermediate range.

The ability of Oncotype DX® to predict the potential benefit of adjuvant chemotherapy has been directly validated using two prospectively designed studies of archived tumor specimens from well-controlled clinical studies. These studies provide clear evidence that patients with low Recurrence Scores derived minimal, if any, benefit from chemotherapy in addition to endocrine therapy and those with high Recurrence Scores had a substantial benefit from the addition of chemotherapy to adjuvant endocrine treatment. Further, data from two exploratory neo-adjuvant trials where complete pathological responses (Gianni et al. 2005) or complete clinical response (Chang et al. 2008) have only been seen in patients with a Recurrence Score of 25 or higher has emphasized the potential utility of the Recurrence Score in predicting chemotherapy benefits


6 publications describing analytical/clinical validation, of which publication provided data on prognostic ability (predictive ability is assumed by association)

No decision impact studies were identified

The assay utilizes microarray technology to evaluate the expression of a 70-gene panel, generated using RT-PCR, in fresh/frozen tissue from test and reference samples. After normalization of results, computer analysis is performed on the microarray results of normal and diseased tissue can be compared to identify genes that vary in their expression and also identify a pattern (profile) that may indicate a distinct class or stage of disease. Based on these results, patients are classified as at a high or low risk of 5-year distant recurrence.

One clinical study has provided evidence that the MammaPrint gene signature has the ability to identify the likelihood of distant recurrence in the first 5 years following diagnosis. Based on the observation from the Early Breast Cancer Trialists’ Collaborative Group, that adjuvant chemotherapy exerts its principal benefit in reducing early metastasis risk during the first 5 years, it is assumed that MammaPrint is predictive during the same interval over which adjuvant chemotherapy exerts the maximum benefit.

Evidence regarding the prediction of benefits from chemotherapy has not been independently demonstrated in randomized trials

Information on Oncotype DX® was derived from the Manufacturer/Sponsor Submission of Evidence on the Oncotype DX® Breast Cancer Test to NICE in 2011. Information on the MammaPrint test was taken from the product website ( accessed on August 16, 2012

Cost-effectiveness evaluations of Oncotype DX® versus usual care

A total of 18 studies were identified that evaluated the cost-effectiveness of Oncotype DX® versus current treatment in estrogen receptor positive (ER+), HER2− early breast cancer (Table 2). Of the 18 cost-effectiveness studies identified, four explicitly stated that they used the same model structure developed by Hornberger et al. in the first published cost-effectiveness evaluation on Oncotype DX® [21, 22, 23, 32, 33], while a further four used a similar modeling approach [24, 25, 26, 34]. The model developed by Hornberger et al. [21] utilized a decision tree approach to model which adjuvant therapies patients received before and after Oncotype DX® testing. Outcomes were then simulated based on data from landmark trials using a Markov model consisting of four states; no recurrence, recurrence with no metastatic progression, recurrence with metastatic progression, and death. The impact of chemotherapy (in terms of reduced risk of distant recurrence, decreased QoL, and increased costs) was estimated in the Markov model, depending on the treatment allocated in the decision tree. Conceptually, a similar approach was used in all of the Oncotype DX® cost-effectiveness modeling studies identified in this review (i.e., estimates of long-term outcomes in a population with and without Oncotype DX® testing).
Table 2

Summary of results of published cost-effectiveness analyses

Study (reference)

QHES score

Country setting


Clinical results

Cost results

Cost-effectiveness and key drivers

Oncotype DX® cost-effectiveness evaluations

 Hornberger et al. [21]



LN−, ER+

8.6 QALYs gained per 100 patients

USD 202,828 decrease in cost per 100 patients

Versus NCCN guidelines: Oncotype DX® dominates

Test increases costs if <50 % of patients receiving chemotherapy under NCCN guidelines are spared treatment

Cost-effectiveness increases when chemotherapy costs are higher

 Lyman et al. [22]



LN−, ER+

Versus tamoxifen: 0.97 QALYs gained

Versus tamoxifen: USD 4,272 increase in direct costs

Versus tamoxifen: USD 4,432 per QALY gained

Versus tamoxifen plus chemotherapy: 1.71 QALYs gained

Versus tamoxifen plus chemotherapy: USD 2,256 decrease in direct costs

Versus tamoxifen plus chemotherapy: Oncotype DX® dominates

Benefit over tamoxifen driven by additional life years saved as a result of prescribing chemotherapy to those will benefit

Benefit over tamoxifen plus chemotherapy driven by cost savings as a result of avoided chemotherapy. This benefit increases as more costly chemotherapy regimens are used

 Kondo et al. [23]



LN−, ER+

Versus NCCN: 0.097 QALYs gained

Versus NCCN: JPY 289,355 increase in direct cost

Versus NCCN: JPY 2,997,495 per QALY gained

Versus St. Gallen: 0.237 QALYs gained

Versus St. Gallen: JPY 293,211 increase in direct cost

Versus St. Gallen: JPY 1,239,055 per QALY gained

Budget impact: JPY 2,638 million to JPY 3,225 million increase in direct costs

Results most sensitive to changes in the price of the assay and frequency of chemotherapy prescription in standard care

Greater cost-effectiveness versus St. Gallen, compared to NCCN, is due to improved outcomes in terms of recurrence, not avoided chemotherapy

 Cosler and Lyman [24]



LN−, ER+

Versus tamoxifen: 2.2 life years gained

Versus tamoxifen: USD 4,272 increase in direct costs

Versus tamoxifen: USD 1,944 per life year gained

Versus tamoxifen plus chemotherapy: Oncotype DX® dominates

Versus tamoxifen plus chemotherapy: No significant difference

Versus tamoxifen plus chemotherapy: USD 2,256 decrease in direct costs

Benefit over tamoxifen driven by additional life years saved as a result of prescribing chemotherapy to those will benefit

Benefit over tamoxifen plus chemotherapy driven by cost savings as a result of avoided chemotherapy. This benefit increases as more costly chemotherapy regimens are used

 de Lima Lopes et al. [25]



LN−, ER+

Direct cost saving of SGD 2,942, SGD 1,077, SGD 169 and SGD 1,340 due to reduced chemotherapy, supportive care, management of adverse events, and administration, respectively

Versus current practice: Oncotype DX® cost saving

Indirect cost savings of SGD 468

Cost saving driven chiefly by reduced chemotherapy drug costs

 Klang et al. [26]



LN−, ER+

0.170 QALYs gained

USD 1,828 per patient increase in direct costs

Versus traditional treatment: USD 10,770 per QALY gained

Patients receiving chemotherapy reduced from 56 to 28 %


Cost savings were driven chiefly by reduced expenditure on chemotherapy

Clinical benefits were driven by avoided quality of life decrement associated with chemotherapy in patients previously prescribed chemotherapy who were spared, and lower risk of recurrence in patients previously not receiving chemotherapy who were treated

 O’Leary et al. [27]



LN− and LN+

0.098 QALYs gained

AUD 974 increase in direct costs

Versus conventional treatment: AUD 9,986 per QALY gained

Cost savings were driven chiefly by avoided chemotherapy costs

Quality of life benefit was driven by avoiding chemotherapy in patients who would show no benefit, and avoidance of recurrence in patients switching to chemotherapy

 Tsoi et al. [28]



LN−, ER+, HER2−

0.065 QALYs gained

CAD 4,102 increase in direct costs

Versus Adjuvant!: CAD 63,064 per QALY gained

Assay more cost-effective in younger patients

Cost difference was largely driven by the cost of the assay

 de Lima Lopes et al. [29]



LN−, ER+

0.12 QALYs gained through avoidance of chemotherapy

Direct cost saving of SGD 2,735, SGD 1,001, SGD 157 and SGD 1,245 due to reduced chemotherapy, supportive care, management of adverse events, and administration, respectively

Versus current practice: Oncotype DX® cost saving and improves clinical outcomes

0.15 QALYs gained by prevention of future recurrence

Indirect cost savings of SGD 468

Cost savings driven by reduced expenditure on chemotherapy drugs

Clinical benefits driven by avoided recurrence and avoided reduced quality of life during chemotherapy

 Hall et al. [30]



LN+, ER+

0.16 QALYs gained

GBP 860 increase in direct cost

Versus current practice: GBP 5,529 per QALY gained

61 % probability of cost-effectiveness at willingness to pay threshold of GBP 30,000

Oncotype DX® becomes more cost-effective when more costly chemotherapy regimens are used

Oncotype DX® is dominated when the recurrence score cut off for chemotherapy increases

Oncotype DX® is cost saving to the NHS provided that the proportion of patients classified as low risk (and therefore avoid chemotherapy) is >40 %

 Holt et al. [31]



LN 0–3, ER+

0.14 QALYs gained

GBP 888 increase in direct cost

Versus current clinical practice: GBP 6,232 per QALY gained

99.6 % probability of being cost-effective at a willingness to pay threshold of GBP 20,000 per QALY gained

More cost-effective in younger patients

More cost-effective as chemotherapy use in standard care increases

 Hornberger et al. [32]



LN−, ER+

0.162 QALYs gained

USD 1,103,874 decrease in cost to insurer over 2 million plans

Versus NCCN guidelines: Oncotype DX® dominates

81 % probability of being cost saving

Cost savings were driven chiefly by reduced supportive care costs

Cost savings increase as chemotherapy use in standard care increases

Quality of life increase was driven by avoided chemotherapy in low risk patients

 Kondo et al. [33]



LN−, ER+

LN−: 0.63 QALYs gained

LN−: JPY 240,683 increase in direct cost

LN−, versus St. Gallen: JPY 384,828 per QALY gained

LN− and LN+, ER+

All patients: 0.47 QALYs gained

All patients: JPY 270,035 increase in direct cost

All patients, versus St. Gallen: JPY 568,533 per QALY gained

Increased ICER in LN+ patients due to the higher rate of recurrence

Clinical benefit of the assay driven by identifying patients who would have missed adjuvant therapy, despite being at high risk of recurrence

 Lacey et al. [34]



LN−, ER+

0.12 QALYs gained

EUR 1,139 increase in direct costs

Versus current practice: EUR 9,462 per QALY gained

74.2 % probability of being cost-effective at a willingness to pay threshold of EUR 20,000 per QALY gained

Results most sensitive to changes in price of the assay

 Paulden et al. [35]



LN−, ER+

Not stated

Not stated

Low Adjuvant! risk: CAD 29,000 per QALY gained

High Adjuvant! risk: Oncotype DX® dominates

Oncotype DX® is cost-effective in all early-stage breast cancer patients, irrespective of risk of recurrence as determined by Adjuvant!

 Vanderlaan et al. [36]



LN1–3, ER+

0.127 QALYs gained

USD 384 decrease in direct costs

Versus current practice: Oncotype DX® dominates

Cost savings driven by reduced chemotherapy expenditure

Cost only increased when chemotherapy costs were 25 % lower than in the base case and when the assay reduced chemotherapy by only 15 %, but QALE remained increased in these two scenarios

 Lamond et al. [37] (also reported in Lamond et al. 2011)




LN−: 0.27 QALYs gained

LN−: CAD 2,585 increase in direct costs

LN− versus current practice: CAD 9,591 per QALY gained


LN+: 0.06 QALYS gained

LN+: CAD 864 increase in direct costs

LN+: CAD 14,844 per QALY gained

Mixed cohort (40 % LN+)

Mixed cohort: 0.18 QALYs gained

Mixed: CAD 1,852 increase in direct costs

Mixed: CAD 10,316 per QALY gained

Results most sensitive to chemotherapy utilization following the assay

 Madaras et al. [38]



LN−, ER+

Not stated

Not stated

Versus current practice: EUR 6,871 per QALY gained

Cost-effectiveness increases when more aggressive treatment is used

Oncotype DX® budget impact studies

 Wilson et al. [39]



LN−, ER+, HER2−

EUR 666,844 cost saving if chemotherapy only given to high-risk patients, over the 140 patients included in this analysis

Versus current practice: Oncotype DX® will result in cost savings in European health systems

Only the cost of chemotherapy and the assay were included in this analysis

 Hassan et al. [40]



LN−, ER+, HER2−

Cost saving of CAD 34.5 million

Oncotype DX® is cost saving

Cost savings driven by reduced chemotherapy drug costs

 Lacey and Hornberger [41]




0.4 % increase in direct cost

Versus current practice: adoption of Oncotype DX®is approximately cost neutral

47 % probability of being cost saving

Main driver was reduction in chemotherapy expenditure

 Ragaz et al. [42]


Canada and USA

LN− and LN+, ER+

Cost saving of USD 330.8 million in USA

Oncotype DX® is cost saving in both USA and Canada

Cost saving of USD 46.2 million in Canada

Cost savings are driven by reduced expenditure on chemotherapy

MammaPrint cost-effectiveness evaluations

 Oestreicher et al. [43]



LN− and LN+ (approximately equal proportion), ER+

0.21 decrease in QALYs

USD 2,882 fall in direct and indirect costs

Versus NIH guidelines: reduced cost and reduced quality-adjusted life expectancy

NIH guidelines identified 96 % of patients as high risk, while MammaPrint identified 61 % as high risk, lowering the expenditure on adjuvant chemotherapy

Since MammaPrint was assumed to have a sensitivity of 84 %, distant recurrence rates increased, driving a reduction in QALE

Sensitivity of 95 % (with specificity of 51 % kept constant) to increase QALE over NIH

 Chen et al. [44]



LN−, ER+, HER2−

Overall population: 0.15 QALYs gained

Overall population: USD 1,440 per patient increase in direct cost

Versus St. Gallen, overall population: USD 9,428 per QALY gained

LN−, ER−, HER2−

ER+: 0.23 QALYs gained

ER+: USD 1,332 per patient increase in direct cost

Versus St. Gallen, ER+: USD 6,167 per QALY gained

Mixed population

ER−: 0.098 QALYs lost

ER−: USD 1,811 per patient increase in direct cost

Versus St. Gallen, ER−: MammaPrint dominated

SEER registry population

SEER registry patients: 0.571 QALYs gained

SEER registry patients: USD 401 per patient increase in direct cost

Versus St. Gallen, SEER registry patients: USD 716 per QALY gained

Results were highly sensitive to the proportion of patients the assay classed as high risk, with an increase in high-risk patients reducing cost-effectiveness

 Retèl et al. [45]



LN−, ER+

Versus St. Gallen: 1.20 QALYs gained

Versus St. Gallen: EUR 7,430 decrease in direct costs

Versus St. Gallen: MammaPrint dominates

Versus Adjuvant!: 0.24 QALYs gained

Versus Adjuvant!: EUR 1,130 increase in direct costs

Versus Adjuvant!: EUR 4,614 per QALY gained

Cost savings driven by avoided chemotherapy, which was greater versus St. Gallen and resulted in dominance

 Kondo et al. [46]



LN−, ER+, HER2−

0.048 years gained versus St. Gallen

Societal costs were JPY 231,385 per patient higher with MammaPrint than with St. Gallen

JPY 4,820,813 per life year gained versus St. Gallen

55-year-old patients from a Japanese cancer registry

0.060 QALYs gained versus St. Gallen


JPY 3,873,922 per QALY gained versus St. Gallen (willingness to pay threshold from a societal perspective is JPY 5,000,000 (approx. USD 55,000) per QALY gained)

Results were sensitive to changes in assumptions on risk classification (low versus high) and distant recurrence rates

MammaPrint budget impact studies

 Zarca et al. [47]



LN 1–2

Cost savings of EUR 9,043 per 100 patients per year

Versus current practice: MammaPrint is cost saving

Cost saving driven by reduced chemotherapy expenditure

Results are sensitive to the relative use of St. Gallen and Adjuvant!

MammaPrint versus Oncotype DX® cost-effectiveness studies

 Retèl et al. [48]



Two populations evaluated based on data previously collected by Thomassen et al. and Fan et al.

Thomassen: MammaPrint increased QALYs by 0.08 over Oncotype DX®

Thomassen: Oncotype DX® increased direct cost by EUR 1,475

Thomassen: MammaPrint dominates Oncotype DX®

Fan: MammaPrint increased QALYs by 0.31 over Oncotype DX®

Fan: Oncotype DX® increased direct cost by EUR 3,941

Fan: MammaPrint dominates Oncotype DX® Uncertainty around these outcomes is high

 Yang et al. [49]



LN−, ER+

MammaPrint increased QALYs by 0.097 over Oncotype DX®

Oncotype DX® increased direct cost by USD 6,284

MammaPrint dominates Oncotype DX®

Drivers of outcomes are not stated

ER− estrogen receptor negative, ER+ estrogen receptor positive, HER2− human epidermal growth factor receptor 2 negative, LN− lymph node negative, LN+ lymph node positive, N/A not applicable, NCCN National Comprehensive Cancer Network, NICE National Institute for Health and Clinical Excellence, NIH National Institute for Health, QALE quality-adjusted life expectancy, QALY quality-adjusted life year, QHES Quality of Health Economic Studies, AUD Australian dollars, CAD Canadian dollars, EUR Euros, GBP Pounds, JPY Japanese Yen, SGD Singapore dollars, USD US dollars

The results of the published cost-effectiveness analyses were broadly consistent across the countries investigated (including Australia, Canada (n = 5), Hungary, Ireland (n = 3), Israel, Japan (n = 2), Singapore (n = 2), UK (n = 2), and USA (n = 6)), indicating that Oncotype DX® testing is likely to improve outcomes, reduce the proportion of patients treated with chemotherapy, and be cost-effective from a healthcare payer perspective according to commonly accepted cost-effectiveness thresholds. Results were different in the USA where Oncotype DX® not only improved outcomes, but was also cost saving (i.e., dominant to the current standard of care), an effect driven largely by the fact that chemotherapy is more frequently recommended and more expensive in the USA. This was reflected in the recent analysis by Hornberger et al. [32] based on chemotherapy utilization data from a meta-analysis of decision impact studies, which suggested that Oncotype DX® guided decision making dominated chemotherapy decision making based on NCCN guidelines. Other studies based on real-life chemotherapy prescribing rates have shown Oncotype DX® to be cost-effective relative to usual care in four difference countries [26, 31, 34, 37]. In the published analyses, where costs have been accounted from a societal perspective, Oncotype DX® has been found to be cost saving [25, 29].

Most evaluations were conducted in lymph node negative (LN−) patients (with long-term outcomes based on the NSABP B-14 study [6]) but seven studies took into account lymph node positive (LN+) patients (taking data from the SWOG 8814 study [10]), either exclusively[30, 36, 37] or in a mixed cohort [27, 31, 33, 37, 38]. The analyses suggest that, while Oncotype DX® may be more cost-effective in LN− patients, it is also cost-effective in LN+ patients and cohorts containing a mixture of LN− and LN+ patients.

Cost-effectiveness evaluations of MammaPrint versus usual care

Four studies evaluated the cost-effectiveness of MammaPrint (Table 2) [43, 44, 45, 46]. The 2010 article by Chen et al. [44] reported that MammaPrint was likely to be cost-effective in the overall population, highly cost-effective in ER+ patients, but associated with reduced survival and quality-adjusted life expectancy (QALE) in patients with estrogen receptor negative (ER−) disease in the USA. These differences were driven by the proportion determined to be at high risk by the MammaPrint assay (ER+ 52 %, ER− 94 %). In the ER− group, MammaPrint spared only 6 % of patients from receiving chemotherapy, compared with 12 % in the ER+ analysis. The fall in chemotherapy usage in ER− patients led to reduced life expectancy due to increased rates of distant recurrence [50]. The authors noted that the results were very sensitive to variation in clinical input data to the model (particularly the proportion of patients with ER− disease), as well as the cost of chemotherapy and the cost of MammaPrint. Moreover, limited data on the predictive ability of the test meant that it was assumed that the benefits of chemotherapy in both low-risk and high-risk patients were the same.

Oestreicher et al. [43] reported negative outcomes (decreased survival, decreased QALE, and lower costs) for MammaPrint versus NIH clinical guidelines in a cost-effectiveness evaluation in a mixed hypothetical population of early-stage breast cancer patients in the US setting. Poorer survival in the MammaPrint arm was driven by the sensitivity of the test, modeled as 84 % in the base case analysis. The authors stated that a sensitivity of 95 % is required, with specificity maintained at the current value, for MammaPrint to improve clinical outcomes. However, the analysis is subject to several notable limitations, including that the low risk/high assignation of patients using MammaPrint was assumed based on other studies (sensitivity and specificity estimates used to do this appear low) and that the analysis failed to distinguish between ER+ and ER− patients.

In contrast, a more recent economic evaluation in the Netherlands (Retèl et al. [45]), showed improved survival and quality-adjusted survival for MammaPrint over both St. Gallen guidelines and Adjuvant!, and decreased costs over an approach based on St. Gallen guidelines. The analysis reported 20-year costs and outcomes for a hypothetical cohort of patients with ER+, LN− disease, based on a Markov model populated with sensitivity and specificity data derived from a pooled analysis of 305 tumor samples from three previously reported validation studies of MammaPrint. Benefits were driven by fewer patients receiving unnecessary chemotherapy following MammaPrint testing compared with St. Gallen and Adjuvant! approaches to adjuvant therapy decision making. Similar findings were reported in the Japanese setting, where Kondo et al. [46] investigated the cost-effectiveness of MammaPrint versus St. Gallen criteria from a societal perspective using an adaptation of a model previously used to evaluate the cost-effectiveness of Oncotype DX®. Projecting 10-year outcomes for a cohort of patients with ER+, LN− disease, aged 55 years at baseline from a Japanese cancer registry, MammaPrint was associated with an improvement in QALE of 0.06 QALYs and an additional cost of JPY 231,385 per patient, leading to an ICER of ~JPY 3.9 million (USD 43,000) per QALY gained. Results were sensitive to changing assumptions around risk classification (low or high) and rates of distant recurrence.

Cost-effectiveness studies comparing Oncotype DX® and MammaPrint

Despite the lack of head-to-head clinical trial data or decision impact studies, two studies directly compared the cost-effectiveness of Oncotype DX® with MammaPrint, (Table 2) [48, 49]. Neither of these studies used the commercially available assays, but instead assayed expression of the same genes as in the commercial assays using their own methodologies. The authors acknowledge that there is significant uncertainty around the results and that the analyses should be repeated in the future, using a mixed treatment comparison approach or, ideally, data from a head-to-head trial of the two gene expression-profiling tests.

In the study by Yang et al. [49], MammaPrint was found to dominate Oncotype DX®, both in terms of improving outcomes and reducing costs. There is, however, a lack of transparency regarding outcome drivers because only the final cost and QALE outcomes are reported. In the model, instead of modeling the two tests directly against each other, the two tests were individually compared with Adjuvant! and then outcomes compared. Furthermore, the cohorts used in the two analyses were neither the same nor comparable. In the Oncotype DX® versus Adjuvant! analysis, 47 % of patients were classified as high risk, while in the MammaPrint versus Adjuvant! analysis, 74 % of patients were considered at high risk. Therefore, one would expect that more MammaPrint patients than Oncotype DX® patients would receive chemotherapy, and subsequently the MammaPrint patients would accrue higher costs than patients receiving Oncotype DX®. The costs in the MammaPrint arm are, though, unexpectedly lower [51]. Moreover, Oncotype DX® patients with intermediate and high Recurrence Scores were spuriously grouped together to form a “high risk” group (as data suggests only around 50 % of intermediate Recurrence Score patients receive chemotherapy). The noncomparable populations and the lack of transparency make the results and validity of this analysis difficult to interpret.

Retèl et al. [48] used retrospective data from two analyses of the sensitivity and specificity of a number of MGAs. In this study, the outcome measured influenced the method deemed most cost-effective. If the cost per QALY gained is the focus, then MammaPrint was most cost-effective. Concentrating, however, on the cost per life year gained, and Oncotype DX® has the highest probability of being cost-effective. Although providing more readily comparable datasets than that used in the Yang et al. study, a number of issues with this approach remain. Firstly, one retrospective study was small, containing only 26 tumor samples for assessment, taken from patients of whom few had received tamoxifen [52]. Secondly, the larger data set (295 samples) used data that was included in the development of MammaPrint; thus, increasing the likelihood that the MammaPrint predictions would be correct [53].

Budget impact studies

A total of four studies evaluated solely the budget impact of Oncotype DX® (as well as two that calculated both cost-effectiveness and budget impact) and one evaluated the budget impact of MammaPrint. The analysis by de Lima Lopes et al. [29] used the model that was later used in the 2011 cost-effectiveness analysis by the same authors;[25]; however, clinical outcomes were not calculated in the first of these studies. This study found that, on a per patient basis in Singapore, Oncotype DX® was cost saving, mainly driven by reduced need for supportive care, and administration. Analyses in Canada and the USA similarly found Oncotype DX® to be cost saving [40, 42], while two analyses in the Irish setting reported approximate cost neutrality or cost saving [39, 41]. An UK-based study found that Oncotype DX® was cost saving as long as over 40 % of the patients tested were found to be at low risk [30]. The major driver of cost savings in these budget impact analyses was the reduced number of chemotherapy prescriptions. A similar result was found in the budget impact study examining MammaPrint, where cost savings were reported in the French setting [47]. The magnitude of reduction in chemotherapy prescriptions in the budget impact analyses to date may be the key area of differentiation from the published cost-effectiveness studies (where chemotherapy sparing effects were more modest) in which MGAs appear to be generally cost-effective (but cost more than usual care). The only budget impact study in which the gene expression-profiling test was found to increase costs was a 2008 study of Oncotype DX® in the Japanese setting [23].

Evaluating study quality

The quality of the identified analyses was high. The mean score for the studies comparing MGAs with current practice were both 86/100 for the Oncotype DX® and MammaPrint assays (Fig. 2). The most common area where studies did not meet QHES criterion was explicit discussion of bias (Appendix). A number of analyses also failed to fully describe the model constructed and the assumptions used. These shortcomings, however, were relatively minor and only five studies score <80/100.
Fig. 2

Scatter plot of quality assessment of published, peer-reviewed cost-effectiveness evaluations of Oncotype DX®, and MammaPrint. (The quality of studies supporting each gene expression test was assessed using the Quality of Health Economic Studies (QHES) instrument, generating a score out of 100, where higher scores reflect higher quality. Each circle represents the QHES score from a single study)

The quality of the two studies comparing Oncotype DX® and MammaPrint was lower than those comparing with usual care, scoring 66 and 72. These two studies received lower ratings primarily as a result of the data sources used to determine the treatment effects. One study used randomized controlled trial evidence, but not from a head-to-head study of the two interventions, and the other used evidence from small retrospective studies, some of which was used to inform creation of the MammaPrint test. Moreover, chemotherapy allocation in high- and low-risk patient groups was based on assumption. These studies also received low scores as a result of limited sensitivity analyses and lack of transparency, as very limited information on the outcomes and drivers of outcomes were given.


This review has collated the existing health economic analyses examining the use of MGAs in guiding adjuvant chemotherapy treatment in early-stage breast cancer. The cost-effectiveness of only two assays, Oncotype DX® and MammaPrint, has been assessed in published literature. The majority of the economic evaluations found that using gene expression profiling to guide adjuvant therapy was cost saving or cost-effective. This was the case for all studies comparing Oncotype DX® with current treatment covering a range of populations with ER+ early-stage breast cancer across a number of different countries. The cost-effectiveness profile of MammaPrint appears to be more complex. Two studies support cost-effectiveness in ER+ populations, but in ER− patients and in a mixed (ER+, ER−) population, the clinical outcomes were poorer following MammaPrint testing than with usual care. Two evaluations directly compared the cost-effectiveness of MammaPrint with Oncotype DX®. Both analyses found MammaPrint to dominate Oncotype DX®. Both, however, are beset with methodological shortcomings and appear to be at odds with the other published studies on the cost-effectiveness of these gene-profiling tests. Budget impact analyses indicated that MGAs were likely to be cost neutral or cost saving in most settings (US, UK, Canada, Ireland, and Singapore for Oncotype DX®, France for MammaPrint); the only exception was the analysis by Kondo et al. (2011), which reported that Oncotype DX® increased costs but was highly cost-effective in Japan.

Assay accuracy has a large effect on cost-effectiveness, since incorrect allocation to low risk groups increases the risk of distant recurrence as a result of under treatment. Furthermore, incorrect allocation to high risk reduces QoL and increases costs due to overtreatment with chemotherapy [43]. MGAs with significant clinical data to support their use were shown in health economic evaluations, to improve outcomes both by assigning patients to chemotherapy who would not have previously received treatment, and by sparing patients from the adverse effects of chemotherapy who are unlikely to benefit. Assays were most likely to be cost-effective in settings where a high proportion of early-stage breast cancer patients received chemotherapy and where chemotherapy was costly. In these settings, assays benefit patients by reducing the number of adverse events associated with chemotherapy and payers by reducing the cost of chemotherapy and associated care. Analyses showed that the cost-effectiveness of MGAs was sensitive to the risk profile of the population. If few patients are classified as being at low risk of distant recurrence, assay costs are not offset by reduced chemotherapy. Still, the literature supports the cost-effectiveness of MGAs in both LN− and LN+ patients. Published studies examined cost-effectiveness in Asia, Europe, and North America, indicating that clinical and cost benefits may be seen in a diverse range of healthcare settings worldwide.

Therapy allocation guided by either conventional approaches or Oncotype DX® was based on real-life data in five of the published analyses [26, 31, 32, 34, 37]. This highlights a limitation of studies on Oncotype DX® and MammaPrint that assign therapy directly from validation studies (a feature of evaluations comparing the two tests). In general, studies that assumed chemotherapy prescription rates produced more positive estimates of cost-effectiveness (often being cost saving) than those who relied on real-life data. The exception was the US evaluation in 2011, which showed Oncotype DX® testing to be dominant to decision making based on NCCN guidelines [32]. The NSABP B-20 study provided data in ER+, LN− patients and the SWOG 8814 trial provided data in ER+, LN+ patients both demonstrate the prediction of chemotherapy benefit provided by Oncotype DX® [9, 10]. The clinical validity of Oncotype DX® as both a prognostic indicator and a test predictive of likely chemotherapy benefit is supported by an evidence base of consistent results from multiple studies [6, 9, 10, 54, 55]. The evidence supporting other MGAs are not currently as strong [16].

The studies identified in this review were generally of high quality, as assessed by the QHES instrument. It should be acknowledged, however, that a general instrument such as QHES might have shortcomings for the assessment of cost-effectiveness analyses (Appendix). The development of a bespoke checklist focused on cost-effectiveness evaluation of diagnostic tests may be a valuable avenue of future research.

MGAs have the potential to help physicians make more informed treatment decisions by identifying patients at high risk of distant recurrence and patients who are likely to benefit from adjuvant chemotherapy. Similarly, identifying patients at low risk of distant recurrence who can be spared chemotherapy treatment has notable benefits, including avoidance of associated adverse events both in the short-term (captured in all models) and long-term (captured in one study). This review finds a consistent body of evidence supporting the cost-effectiveness of Oncotype DX® in informing chemotherapy treatment decisions regardless of local cost and local clinical practice.

In particular, for patients with ER+ early-stage breast cancer, the benefits negate the acquisition costs of Oncotype DX® and its use in these patients is encouraged. The literature suggests that MammaPrint is also likely to be cost-effective in this patient population. The body of evidence, however, is not as extensive and before encouraging its general use further research is needed to understand the influence of local treatment practices and to what extent this test predicts chemotherapy benefit. Future studies investigating head-to-head comparisons of MGAs would provide valuable insights into how these tests influence adjuvant therapy decision making, and would provide valuable data for future economic evaluations on the relative merits of tests in clinical practice in the years ahead.



The authors would like to thank Juliette Plun-Favreau of Genomic Health International, Geneva, Switzerland for her assistance with realization of this article. The authors are also grateful to Tallal Younis of Dalhousie University, Halifax, Nova Scotia, Canada for his constructive comments and review of the article. This study was supported by funding from Genomic Health International provided to Ossian Health Economics and Communications GmbH. Only Barnaby Hunt and William Valentine, as employees of Ossian Health Economics and Communications GmbH, received financial support for their contribution to this review article. No other authors received support for this study. This review was made possible by funding provided by Genomic Health International that facilitated project management and production of this manuscript through Ossian Health Economics and Communications GmbH.

Conflict of interest

As employees of Ossian Health Economics and Communications GmbH, Barnaby Hunt and William Valentine received remuneration from Genomic Health International for their participation in this study. Paolo Pronzato and Roman Rouzier have previously received remuneration from Genomic Health International. The following authors declare that they have no conflict of interest: Elisabeth Chéreau and Josh Carlson.


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Copyright information

© The Author(s) 2013

Open AccessThis article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Authors and Affiliations

  • Roman Rouzier
    • 1
    • 2
    • 3
  • Paolo Pronzato
    • 4
  • Elisabeth Chéreau
    • 3
  • Josh Carlson
    • 5
  • Barnaby Hunt
    • 6
  • William J. Valentine
    • 6
    Email author
  1. 1.Institut CurieParis, Saint CloudFrance
  2. 2.EA 7285UVSQVersaillesFrance
  3. 3.Institut Paoli CalmetteMarseilleFrance
  4. 4.IRCCS Azienda Ospedaliera, Universitaria San MartinoGenoaItaly
  5. 5.University of WashingtonSeattleUSA
  6. 6.Ossian Health Economics and CommunicationsBaselSwitzerland

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