Background: Gene expression tests can inform decisions on whether to recommend or omit chemotherapy for patients with early HR+, HER2− breast cancer. The benefit of these tests is well established and fully reimbursed by sickness funds for lymph node-negative (pN0) patients in Germany. A budget impact model was built to evaluate the effect of using the Oncotype DX Breast Recurrence Score® test also for node-positive (pN1: 1–3 positive lymph nodes) patients. Methods: The prospective randomized clinical trial, RxPONDER, defined conditions (Recurrence Score result 0–25 for postmenopausal patients with 1–3 positive lymph nodes) under which omitting chemotherapy does not significantly impact invasive disease-free survival with results currently reported for 5-year follow-up. The present budget impact model calculates average total cost per node-positive patient versus no testing from a sickness funds perspective, taking into account not only the budgetary impact of avoiding chemotherapy and associated side effects, but also the costs of treating those patients who develop distant metastasis. The stability of the results was investigated by probabilistic multivariate sensitivity analysis. Results: After deducting testing cost, applying the Oncotype DX Breast Recurrence Score test yielded an average savings per node-positive patient of EUR 4,272. Without the test costs, the greatest savings resulted from reductions in direct treatment costs and costs arising from the treatment of chemotherapy-related side effects, which together averaged EUR 6,677. The targeted use of chemotherapy after testing also resulted in slightly lower costs for treatment of distant metastasis, if it did occur. The multivariate sensitivity analysis also almost exclusively resulted in cost savings. Conclusion: Analogous to the pN0 situation, this budget impact model demonstrates that the Oncotype DX Breast Recurrence Score test can also reduce healthcare costs in Germany in treatment of node-positive (pN1: 1–3 positive lymph nodes) patients by minimizing both unnecessary chemotherapy and undertreatment. Additional benefits to patients would include reduced morbidity and improved quality of life for those patients who can safely avoid chemotherapy or undertreatment.

Breast cancer is the most frequent type of cancer; approximately 70,000 women are diagnosed in Germany every year [1, 2]. Besides surgery and radiotherapy, treatment options for patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2−) early breast cancer include endocrine or endocrine-based therapy and, for some patients, chemotherapy. According to the annual evaluation of the certified breast cancer centers in Germany, 63% of node-positive patients received chemotherapy in 2019 [3]. Gene expression tests can support decisions on whether or not to recommend chemotherapy and whether or not there is a benefit for this group of patients. Guidelines recommend the use for therapeutic decisions in the context of clinical-pathological criteria (tumor size, nodal involvement, grade, Ki-67 antigen, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2) [4]. Since chemotherapy is associated with short- and long-term side effects that affect quality of life, only those patients for whom it is actually proven to be beneficial should receive chemotherapy (avoiding overtreatment). On the other hand, it must be ensured that patients likely to benefit from chemotherapy actually receive it in order not to increase the risk of mortality (avoiding undertreatment). The benefit of the tests has been established for node-negative patients, and they are reimbursed in standard care in Germany, but not for node-positive patients so far. However, new data became available for node-positive patients in 2021, so that there is now clinical evidence from a large prospective randomized controlled trial for this special patient population [5].

The prospective randomized clinical trial, RxPONDER [5], defined conditions (Recurrence Score® [RS] result 0–25 for postmenopausal patients) for patients with 1–3 positive lymph nodes (pN1) under which omitting chemotherapy does not significantly impact invasive disease-free survival (IDFS) with results currently reported for 5-year follow-up. The study included over 5,000 patients from 632 sites in 9 countries worldwide (USA, Canada, Mexico, Colombia, Ireland, France, Spain, South Korea, and Saudi Arabia) and can be considered transferrable to Germany, especially regarding the need for supporting the chemotherapy decision, patient characteristics such as menopausal status and key tumor parameters and treatment of nodal positive disease of the control arm. Major results of the RxPONDER study were that among postmenopausal women, IDFS at 5 years was 91.9% in the endocrine-only group and 91.3% in the chemo-endocrine group. The results demonstrated that postmenopausal women with 1–3 positive lymph nodes (pN1) and an RS result of 0–25 do not benefit from adjuvant chemotherapy and can spare the treatment without compromising IDFS and distant relapse-free survival. However, premenopausal women with 1–3 positive lymph nodes (pN1) – even with a low RS result – had a significant benefit in IDFS from chemotherapy [5]. A budget impact model was built to evaluate the effect of using the Oncotype DX Breast Recurrence Score® test in node-positive (pN1: 1–3 positive lymph nodes) patients.

In the presented budget impact model, average total costs per node-positive patient (pN1) versus no testing were calculated from a sickness funds perspective, taking into account not only the budgetary impact of avoiding chemotherapy and associated side effects, but also the costs of treating those patients who develop distant metastasis. As premenopausal women with 1–3 positive lymph nodes (pN1) – even with a low RS result – had a significant benefit from chemotherapy in the RxPONDER study [5], those patients were assumed to receive chemotherapy without performing a test. The stability of the results was investigated by probabilistic multivariate sensitivity analysis. Figure 1 shows the model structure in overview.

Fig. 1.

Schematic overview of the model structure.

Fig. 1.

Schematic overview of the model structure.

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Test costs as well as costs for chemotherapy, side effects, and metastases were considered. This approach aims to quantify the costs of chemotherapy in cases where beneficial as well as where not improving outcomes: cost of chemotherapy [6] and the treatment of its side effects were based on cost data from Lux et al. (2018) [7], updated and complemented with data from a structured literature search to reflect the status as of July 2023 [8, 9]. To avoid a bias in favor of “no treatment,” the authors deemed important to also consider potential undertreatments. To do so, long-term outcomes were taken from Kalinsky et al. [5] and metastases were considered from a cost-perspective in the model over a time horizon of up to 10 years. The costs for treating metastases were obtained by a structured literature search, aligned with the results of recent rulings of the German joint federal committee (G-BA): based on yearly costs listed between EUR 2,082 and EUR 56,917 yearly [10] and considering sick fund data reporting EUR 33,237 costs in the last 11 months before death [9], average costs for metastasis of EUR 67,787 were estimated. Table 1 summarizes the key cost inputs in the model.

Table 1.

Key cost inputs

TopicCost, EURSource
Costs of gene expression test 
Oncotype DX 2,727 German national tariff (EBM 19506; July 2023)1 
Costs of chemotherapy 
Chemotherapeutics 6,224 Epirubicin, cyclophosphamide, and paclitaxel based on [7] and on [10
Supportive therapy with chemotherapy 4,035 From [7] with 50% dose-dense chemotherapy assumed and 49.6% G-CSF in standard therapy 
Hospital fee for preparation of cytostatics 1,620 Reimbursement rules, as in [10
Hospital outpatient fee 207 [7
Monitoring costs 784 German national tariff (EBM July 2023) [7
Rehabilitation costs 97 [9
Transportation costs (for sick funds) 77 [7
Sick leave pay 2,891 Own calculation based on Destatis average payment, [8] and [7
Sum of chemotherapy costs 15,935  
Costs of treating side effects (direct costs only) 1,862 Updated to 2023, values from [7
TopicCost, EURSource
Costs of gene expression test 
Oncotype DX 2,727 German national tariff (EBM 19506; July 2023)1 
Costs of chemotherapy 
Chemotherapeutics 6,224 Epirubicin, cyclophosphamide, and paclitaxel based on [7] and on [10
Supportive therapy with chemotherapy 4,035 From [7] with 50% dose-dense chemotherapy assumed and 49.6% G-CSF in standard therapy 
Hospital fee for preparation of cytostatics 1,620 Reimbursement rules, as in [10
Hospital outpatient fee 207 [7
Monitoring costs 784 German national tariff (EBM July 2023) [7
Rehabilitation costs 97 [9
Transportation costs (for sick funds) 77 [7
Sick leave pay 2,891 Own calculation based on Destatis average payment, [8] and [7
Sum of chemotherapy costs 15,935  
Costs of treating side effects (direct costs only) 1,862 Updated to 2023, values from [7

1Reimbursed tariff for Oncotype DX Breast Recurrence Score test in node-negative patients.

To account for the real-world treatment practice, the model assumed that 63.1% of nodal positive patients receive a chemotherapy in Germany, based on the yearly report (DKG) of certified breast cancer centers [3]. This includes those patients, who chose to not receive chemotherapy as well as those, who did not receive a recommendation for chemotherapy. Analogously, for Oncotype DX testing, the model assumed that 16.2% of patients would not follow a chemotherapy recommendation despite a high RS by Oncotype DX testing (2,085 of 2,511 patients accepted treatment in chemotherapy arm of Kalinsky et al. [5]).

From a sickness fund perspective, the use of the Oncotype DX Breast Recurrence Score® test means that the test costs are significantly overcompensated: after taking into account testing cost, applying the Oncotype DX® test still yielded an average savings per node-positive (pN1) patient of EUR 4,272 (Fig. 2). The highest savings resulted from reductions in direct treatment costs (chemotherapy). In the group of patients without a test, 63.1% received chemotherapy, while in the group of patients with Oncotype DX® test only 25.6% had chemotherapy treatment. Accordingly, the average cost per patient for chemotherapy is EUR 4,083 for patients tested with the Oncotype DX test prior to treatment and EUR 10,061 for patients not tested. This short-term result alone generates a cost reduction of EUR 5,978 per patient. In addition, savings of EUR 699 were achieved in costs arising from the treatment of chemotherapy-related side effects. The targeted use of chemotherapy after testing also resulted in slightly lower costs (EUR 323) for treatment of distant metastasis, if it did occur. The cost of the test (EUR 2,727) must be deducted from the savings mentioned. Figure 3 summarizes the components of the average total costs per patient.

Fig. 2.

Comparison of average total costs per patient and chemotherapy costs.

Fig. 2.

Comparison of average total costs per patient and chemotherapy costs.

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Fig. 3.

Cost components of the average total costs per patient.

Fig. 3.

Cost components of the average total costs per patient.

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The results of multivariate sensitivity analysis confirm the robustness of results. For the sensitivity analysis, all relevant parameters were reproduced in 100 simulation runs. Figure 4 presents that out of 100 simulated patients, only one would have had a lower cost without using the Oncotype DX test than using the test (point below the diagonal), which means that in 99% of the simulated cases, an application of the Oncotype DX test led to a cost reduction.

Fig. 4.

Probabilistic sensitivity analysis.

Fig. 4.

Probabilistic sensitivity analysis.

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The lymph node status is still the most important prognostic parameter for HR+, HER2− early breast cancer. By this, early breast cancer patients with 1–3 positive lymph nodes (pN1) specifically are more likely treated with adjuvant chemotherapy than node-negative (pN0) patients when physicians use clinicopathological criteria alone [11, 12]. The Oncotype DX Breast Recurrence Score test can help successfully guide treatment decisions for pN1 postmenopausal patients, while clearly the decision-making process should be based on and supported by an interdisciplinary tumor conference. Premenopausal women with 1–3 positive lymph nodes (pN1) – even with a low RS result – had a significant benefit from chemotherapy in the RxPONDER study [5]: in the economic model, those patients therefore were calculated to receive chemotherapy without performing a test.

Chemotherapy is well known to reduce risks of relapse in early breast cancer, while risk prediction and absolute risk reduction based on clinic-pathologic criteria alone are extremely challenging [4]. The risk reduction by chemotherapy needs to be weighed against associated side effects like nausea, vomiting, hair loss, and myelosuppression and the reduction of quality of life. Longer term toxicities also include the risks of polyneuropathy, cardiotoxicity, or secondary malignancies associated with anthracycline chemotherapy. Thus, the decision to offer chemotherapy must take into account risk factors of the disease as well as the patient age, comorbidities, and preferences. Overall, node-positive (pN1) breast cancer patients may be more likely to receive chemotherapy as their condition is perceived as more severe than for node-negative (pN0) patients and due to existing therapeutic traditions and guidelines, which is reflected in observed higher chemotherapy rates: 45% with pN0 tumors [11] versus 70% in pN1 [12]. Therefore, the unmet need of node-positive patients is expected to be higher, and the need for tools that predict the benefit of chemotherapy is particularly high for these patients.

The randomized controlled RxPONDER study investigated whether the chemotherapy effect depends on the RS result of the Oncotype DX test and pursued the goal to determine the magnitude of chemotherapy benefit in terms of disease recurrence and survival in the RS results 0–25 range for pN1 breast cancer patients. In brief, postmenopausal women with an RS result between 0 and 25 did not benefit from adjuvant chemotherapy in terms of IDFS and distant relapse-free survival: estimates of IDFS at 5 years were 91.3% in the chemo-endocrine group and 91.9% in the endocrine-only group (hazard ratio for invasive disease recurrence, new primary cancer [breast cancer or another type], or death, 1.02; 95% CI, 0.82–1.26; p = 0.89). No subgroups derived an IDFS benefit from the addition of chemotherapy. In a per-protocol analysis, no significant chemotherapy benefit was noted (hazard ratio, 0.97; 95% CI, 0.77–1.22; p = 0.81) [5]. Thus, a majority of pN1 postmenopausal patients can be spared chemotherapy if their RS result is between 0 and 25.

As the chemotherapy rate is usually higher in node-positive (pN1) patients than in node-negative (pN0) patients [11, 12], the impact of a more informed decision-making with the Oncotype DX test for pN1 patients is high: without testing, a significant proportion of patients may be exposed to chemotherapy side effects without the benefits on distant recurrence or survival. The majority of postmenopausal women – with an RS result <26 – appear to not benefit from adjuvant chemotherapy.

In the present model, the calculated cost savings refer to the perspective of the payer. Taking into account the perspective of society, the potential savings would be significantly higher by avoiding non-medical costs such as transport costs for therapy, caregiver costs, loss of work, possibly early retirement due to long-term toxicity. If these costs are taken into account, chemotherapy can result in total costs of up to EUR 90,000 per patient [7].

The presented budget impact model shows clearly that the use of the test can achieve positive effects not only for the patients, but also for the sickness funds in short time periods. Test costs and chemotherapy costs both occur in short term: by avoiding chemotherapies, which do not improve outcomes, the costs of testing are clearly overcompensated by the saved treatment costs. Taking into account that there are around 12,000 new patients with HR+, HER2−, pN1 (1–3 positive lymph nodes) early breast cancer in Germany every year, there is a total savings potential for the sickness funds of around EUR 51 million per year. Lastly, the model results – based on long-term clinical results [5] – suggest that the avoided chemotherapies do not deteriorate clinical outcomes: metastases and their treatment costs (Fig. 3) do not increase with a testing regimen.

Although the test has not yet been included in the German statutory health insurance’s catalog of services for node-positive (pN1) patients, it can still make an important contribution to reducing health insurance costs in Germany and improve the quality of life of these patients. Ultimately, this is achieved by avoiding unnecessary chemotherapies and the side effects associated with it due to informed treatment decisions based on the RS results, without negative impact on recurrence rate or survival of the tested patients. Results were robust in multivariate sensitivity analysis, but clearly model assumptions and setup limit generalizability: cost inputs were for a German year 2023 setting (see Table 1), and the model is based on the clinical results of the prospective RxPONDER study available [5]. Those data, as well as clinical practice patterns, may change in the future as evidence evolves.

To date, the Oncotype DX Breast RS test is the only gene expression test, which has prospectively proven to predict the benefit of chemotherapy in patients with HR+, HER2−, pN1 early stage breast cancer. It enables informed decision-making regarding the choice of therapy and ensures that overtreatment and undertreatment with chemotherapy can be prevented in patients with HR+, HER2−, pN1 early stage breast cancer. The budget impact model presented demonstrates that the Oncotype DX Breast RS test can reduce healthcare costs in Germany in the treatment of node-positive (pN1) patients – already within a short period of time, which is particularly important for the sickness funds – by minimizing both unnecessary chemotherapy and undertreatment. Limitations are derived from the model setup with 2023 country-specific cost data, RxPONDER clinical data, and furthers. Finally, the budget impact approach does not cover all aspects: additionally, non-monetary benefits for patients may include reduced morbidity and improved quality of life for those patients, who may – with better informed decision-making – avoid chemotherapy or undertreatment.

The work does not involve the use of human subjects; therefore, informed consent does not apply. Ethics approval by an ethics commission/IRB is not applicable: no animal or human data or tissue is involved in the study.

Michael Patrick Lux were part of advisory boards for Lilly, AstraZeneca, MSD, Novartis, Pfizer, Eisai, Exact Sciences, PharmaMar, Roche, Daiichi-Sankyo, Grünenthal, SamanTree, and Sysmex; had speaking engagements for Lilly, Roche, MSD, Novartis, Pfizer, Exact Sciences, AstraZeneca, Daiichi-Sankyo, PFM, Grünenthal, and Eisai; received travel expenses from Roche and Pfizer; and were part of the editorial board for Medac; Aljoscha Steffen Neubauer and Christof Minartz received expert fees from Exact Sciences. Harald Müller-Huesmann is an employee of Brüderkrankenhaus St. Josef and MVZ Medico; involved in advisory activity from Roche, BMS, Janssen, MSD, Boehringer Ingelheim, and Ipsen; and received expert fees from Roche, BMS, Janssen, Astra-Zeneca, Merck, Boehringer Ingelheim, and Ipsen. Mariana-Felicia Sandor received travel/congress expenses from TEVA.

Resources for data analysis (model generation) and publication were provided by Exact Sciences. This funding source had no role in the design of this study and during its execution, analyses, and interpretation of the data.

All authors contributed to the study conception and design; performed material preparation, data collection, and analysis; commented on previous versions of the manuscript; and read and approved the final manuscript. The first draft of the manuscript was written by M.P.L., C.M., S.R., and A.S.N.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

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