Transferring MINDACT to Daily Routine: Implementation of the 70-Gene Signature in Luminal Early Breast Cancer - Results from a Prospective Registry of the Austrian Group Medical Tumor Therapy (AGMT)

Background

For hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer (EBC), adjuvant chemotherapy (ACT) is recommended in the case of high-risk features only. The MINDACT trial showed that patients with high clinical risk (CR) but low genomic risk (GR) defined by the 70-gene signature (MammaPrint®; 70-GS) did not benefit from ACT. In this registry, we investigated the frequency and feasibility of 70-GS and concurrent 80-gene subtyping (BluePrint®) use in HR-positive, HER2-negative EBC. Furthermore, we recorded the frequency of ACT recommendation and the adherence to it when the "MINDACT strategy" was used.

Methods

This prospective registry included patients from 2 Austrian cancer centers. Similar to MINDACT, a modified version of Adjuvant!Online was used to determine CR, and 70-GC was used to determine GR in high-CR patients. ACT was recommended to patients with high CR and high GR.

Results

Of 224 enrolled patients, 76 (33.9%) had high CR and 67 (88.2%) received genomic testing. Of those, 43 (64.2%) were classified as low and 24 (35.8%) as high GR, respectively. All 24 patients with high CR and GR (10.7% of all patients) received the recommendation for ACT, but ACT was started in only 15 patients (62.5%). The median time from surgery to the start of ACT was 45 days (range 32-68), and the median time from test decision to the test result was 15 days (range 9-56).

Conclusion

We showed that the results of the MINDACT trial are reproducible in an Austrian population. Incorporating 70-GS into the daily clinical routine is feasible and mostly accepted by physicians for the guidance of treatment recommendations.

Prognostic models for breast cancer: a systematic review

BACKGROUND

Breast cancer is the most common cancer in women worldwide, with a great diversity in outcomes among individual patients. The ability to accurately predict a breast cancer outcome is important to patients, physicians, researchers, and policy makers. Many models have been developed and tested in different settings. We systematically reviewed the prognostic models developed and/or validated for patients with breast cancer.

METHODS

We conducted a systematic search in four electronic databases and some oncology websites, and a manual search in the bibliographies of the included studies. We identified original studies that were published prior to 1st January 2017, and presented the development and/or validation of models based mainly on clinico-pathological factors to predict mortality and/or recurrence in female breast cancer patients.

RESULTS

From the 96 articles selected from 4095 citations found, we identified 58 models, which predicted mortality (n = 28), recurrence (n = 23), or both (n = 7). The most frequently used predictors were nodal status (n = 49), tumour size (n = 42), tumour grade (n = 29), age at diagnosis (n = 24), and oestrogen receptor status (n = 21). Models were developed in Europe (n = 25), Asia (n = 13), North America (n = 12), and Australia (n = 1) between 1982 and 2016. Models were validated in the development cohorts (n = 43) and/or independent populations (n = 17), by comparing the predicted outcomes with the observed outcomes (n = 55) and/or with the outcomes estimated by other models (n = 32), or the outcomes estimated by individual prognostic factors (n = 8). The most commonly used methods were: Cox proportional hazards regression for model development (n = 32); the absolute differences between the predicted and observed outcomes (n = 30) for calibration; and C-index/AUC (n = 44) for discrimination. Overall, the models performed well in the development cohorts but less accurately in some independent populations, particularly in patients with high risk and young and elderly patients. An exception is the Nottingham Prognostic Index, which retains its predicting ability in most independent populations.

CONCLUSIONS

Many prognostic models have been developed for breast cancer, but only a few have been validated widely in different settings. Importantly, their performance was suboptimal in independent populations, particularly in patients with high risk and in young and elderly patients.

Personalized treatment of women with early breast cancer: a risk-group specific cost-effectiveness analysis of adjuvant chemotherapy accounting for companion prognostic tests OncotypeDX and Adjuvant!Online

BACKGROUND

Due to high survival rates and the relatively small benefit of adjuvant therapy, the application of personalized medicine (PM) through risk stratification is particularly beneficial in early breast cancer (BC) to avoid unnecessary harms from treatment. The new 21-gene assay (OncotypeDX, ODX) is a promising prognostic score for risk stratification that can be applied in conjunction with Adjuvant!Online (AO) to guide personalized chemotherapy decisions for early BC patients. Our goal was to evaluate risk-group specific cost effectiveness of adjuvant chemotherapy for women with early stage BC in Austria based on AO and ODX risk stratification.

METHODS

A previously validated discrete event simulation model was applied to a hypothetical cohort of 50-year-old women over a lifetime horizon. We simulated twelve risk groups derived from the joint application of ODX and AO and included respective additional costs. The primary outcomes of interest were life-years gained, quality-adjusted life-years (QALYs), costs and incremental cost-effectiveness (ICER). The robustness of results and decisions derived were tested in sensitivity analyses. A cross-country comparison of results was performed.

RESULTS

Chemotherapy is dominated (i.e., less effective and more costly) for patients with 1) low ODX risk independent of AO classification; and 2) low AO risk and intermediate ODX risk. For patients with an intermediate or high AO risk and an intermediate or high ODX risk, the ICER is below 15,000 EUR/QALY (potentially cost effective depending on the willingness-to-pay). Applying the AO risk classification alone would miss risk groups where chemotherapy is dominated and thus should not be considered. These results are sensitive to changes in the probabilities of distant recurrence but not to changes in the costs of chemotherapy or the ODX test.

CONCLUSIONS

Based on our modeling study, chemotherapy is effective and cost effective for Austrian patients with an intermediate or high AO risk and an intermediate or high ODX risk. In other words, low ODX risk suggests chemotherapy should not be considered but low AO risk may benefit from chemotherapy if ODX risk is high. Our analysis suggests that risk-group specific cost-effectiveness analysis, which includes companion prognostic tests are essential in PM.