For patients with early-stage breast cancer, predicting the response to chemotherapy and risk of recurrence is crucial. Genomic testing for early breast cancer is a reliable tool for decision making for treatment. For adjuvant systemic therapy in patients with non-metastatic, ER/PR positive, HER2 negative, and N0-1 breast cancers, the 70-gene MMP test is recommended as evidence of category 1 in the 2022 NCCN guidelines.[9] Moreover, the St. Gallen Consensus Conference, American Society of Clinical Oncology (ASCO), and European Commission Initiative on Breast Cancer recommended use of the 70-gene signature in women with high clinical risk factors.[7, 11, 12] Therefore, the 70-gene signature test is increasingly known for its usefulness in determining candidates for adjuvant chemotherapy. Although there is evidence for the usefulness of MMP in certain subsets of patients, clinicians hesitate to recommend this test because of the cost and long duration to obtain test results.
In this retrospective cohort study, which aimed to validate a nomogram that can predict the probability of a low risk of MammaPrint results in women with clinically high-risk breast cancer, we found out the AUC was 0.73 (95% CI, 0.77 to 0.87). Kaplan–Meier analysis of the two groups divided by a nomogram score of 183 showed a relevant difference in OS (p = 0.056), DFS (p = 0.008) and BCSS (p = 0.002). The nomogram in our previous study helped clinicians promptly predict a low MMP risk, using only four simple clinicopathologic factors (age, nuclear grade, progesterone receptor status, and Ki-67). Other studies have also attempted to predict the MMP score by using the MR imaging radiomics signature or other clinicopathologic data.[13, 14] However, in this study, we decided that the easiest way to make a quick estimation is by nomogram which is ran by simple four simple factors.[10] On top of it we added user-friendly interfaced calculator that can calculate the MMP score in a second.
On closely inspecting the cohort profiles of 1,835 patients at AMC from 2010 to 2013, we found that no patient in the group with TP\(\ge\)183 had histologic grade III, while the group with TP<183 had 257(38.3%) patients with grade III. In addition, the groups with TP\(\ge\)183 and TP < 183, had 103 (8.9%) and 3 (0.4%) breast cancer patients with grade I, respectively. Since it was first demonstrated in 1991[15], the histologic grade is a well-known prognostic factor in breast cancer. Consensus and recommendations for good practice in determining the tumor grade set by pathology in breast cancer[16] render the tumor grade a simple and accurate determinant in decision making regarding adjuvant therapy. Despite developments in new molecular technology, tumor grade determination remains a validated method for assessing patient prognosis when alternative molecular testing is not available.[17]
Age at diagnosis plays a key role in our model; younger patients (< 50 years) are unlikely to have 95% or higher low genomic risk probability according to the nomogram calculator.[10] In our study, there was a considerable difference in the mean age at diagnosis in the external validation group (44.7 ± 9.0 years in the high-risk group and 50.6 ± 9.2 years in the low-risk group). Most recently updated results of the MINDACT trial, with a median follow-up of 8.7 years, reveal that in clinically high/genomic low risk patients, women aged 50 years or younger have a relevant difference in 8-year distant metastasis-free survival, based on the type of adjuvant therapy administered.[18] The absolute difference in the 8-year distant metastasis-free survival in the chemotherapy and no-chemotherapy groups were 5.0 and 0.2 percentage point respectively, and this result might be the consequence of ovarian function suppression effect of chemotherapy which only affect premenopausal women. Our study result corresponds with up-to-date interest in age at diagnosis, which is considered crucial prognostic factor in the selection of adjuvant treatment options.
In terms of disease-free survival, the TP\(\ge\)183 group showed significantly superior outcome over the TP<183 group (p = 0.008). HR+ and HER2- breast cancers are reported to have 20% likelihood of tumor recurrence in the first 10 years after surgery, although many patients do not experience recurrence.[19] During the first few years of adjuvant endocrine therapy,[20] patients with a high clinical risk and/or pathologic features have a higher risk of disease recurrence. According to the monarchE phase III trial, distant metastasis accounts for more than 75% of early recurrences during endocrine therapy.[21] Therefore, optimizing adjuvant therapy according to patient specific risk is important for improving invasive disease-free survival. After reviewing the limitations of our previous study, the nomogram was constructed based on the MMP result, but we did not consider the treatment outcome of a patient who received adjuvant therapy. This study aimed to provide evidence of the possibility that the nomogram could help distinguish the groups with favorable and worse outcomes. Moreover, by validating the nomogram using an external patient cohort from another time period, this study strengthens the usability of the nomogram.
There are some limitations that could be found into this study. First, this study is based on a retrospective analysis of patient datasets and, therefore, there might have been selection bias in selecting the patient cohort. Moreover, the patient cohort that underwent the MMP test had few ER-PR, negative, or weak positive patients, leading to inaccurate predictions in the ER-PR negative or weak positive groups. However, this aspect can also be a strong point of this study, because in real-world clinical settings, most ER-PR negative or weak positive patients are omitted from MMP tests. In addition, as Ki-67 levels may vary between institutions, there can be issues with reproducibility in other institutions. Therefore, further validation studies using cohorts from other institution may help confirm the usability of this nomogram. Mistranslation of the nomogram results into overall prognosis of individual patients by other clinicians is also a concerning issue. Due to its retrospective nature, this study is incapable of showing the predictive value of this test.
In conclusion, for decision making regarding treatment in HR+/HER2- and node positive, clinically high-risk patients, our nomogram is useful for quick prediction of low genomic risk patients who can be spared MMP testing. In addition, the two groups distinguished by the nomogram score differed in the 5-year DFS and BCSS, and OS. Further studies are needed to validate this model in international cohorts and large prospective cohorts from other institutions.