7-Gene Test Significantly Reduces Unnecessary Radiation in Breast Cancer

Chirag Shah, MD

A 7-gene predictive score significantly changed treatment recommendations for patients with breast ductal carcinoma in situ (DCIS) breast cancer, specifically reducing the use of unnecessary radiation therapy while still recommending it for those who might benefit most, according to findings from the PREDICT study (NCT03448926).¹

In the prospective, multi-institutional trial, patients with DCIS who received DCISionRT testing as part of their routine care were enrolled and had a median age of 62 years, with 32% having grade 3 tumors and 10% having tumors larger than 2.5 cm. After using the DCISionRT test, the recommendation for radiation therapy changed for 38% of patients (P <.001). This resulted in a 20% reduction in the number of patients recommended for radiation (P <.001).

The DCISionRT score had the greatest influence on radiation recommendations compared with other factors like patient preference, breast cancer characteristics, or physician specialty. Higher scores (4-10) were significantly associated with increased odds of receiving radiation vs lower scores (0-2). Patient preference was the second most important factor influencing radiation therapy decisions after the DCISionRT score.

Among those who continued to be recommended for radiation after the test, the type of radiation changed in 34% of cases. Patients with higher scores received more intensive radiation (P <.001), while those with lower scores received less intensive treatment.

These findings suggest that the DCISionRT test can help tailor treatment for patients with DCIS, preventing both overtreatment and undertreatment.

In an interview with Targeted Oncology^TM, Chirag Shah, MD, radiation oncologist at Cleveland Clinic, codirector of the comprehensive breast cancer program, and director of breast radiation oncology, discussed PREDICT study which looked at DCISionRT testing for patients with DCIS.

Breast Cancer Cells: © LASZLO- stock.adobe.com

Targeted Oncology: What is the background and the rationale of the PREDICT study?

Shah: The PREDICT study is a prospective, multi-institutional, observational registry. What we really wanted to understand is what happened when patients had decision [radiation therapy] testing in terms of radiation recommendations. The primary end point of the study was to look and see what recommendations were before and after and to identify the percentage of patients whose testing led to a change in radiation and recommendations after the use of this testing.

What were some of the challenges in predicting the risk of local recurrence in patients with ductal carcinoma in situ?

Radiation therapy for patients with DCIS is a controversial topic. There have been lots of clinical trials that have shown that radiation in this situation reduces the risk of local recurrence, meaning a cancer coming back in the breast, but it has no impact on survival. For several decades, we have looked to see if we can use traditional factors, like patient factors or factors in the pathology report when they have surgery, to identify patients that benefit and do not benefit from radiation therapy. Unfortunately, what we have seen is these studies still have high rates of recurrence. What led to the DCISionRT was to use the patient's own tumor, along with some clinical and pathologic features, to identify the patients that do and do not benefit from radiation therapy.

What was the process of collecting data for this study? How were patients selected for testing?

Patients were selected for testing based on being at a center that was enrolled in this study, and then they could then be offered this study to participate if they were diagnosed with DCIS and planning a lumpectomy. In terms of the data collected, we collected data on what was the recommendation for radiation before and after the testing, as well as things like clinical and pathologic features, and how that was a function of things, as well as patient preference as well.

What were the factors considered in this analysis? Why were they chosen?

The biggest factor for the primary end point was the recommendation for radiation. This was chosen because this is the thing that we struggle with most clinically: identifying which patients benefit and which patients don't benefit from radiation. We also looked at clinical factors such as age, which is a common factor associated with radiation usage and recommendations, as well as things like grade or how aggressive the DCIS looks under the microscope, because these are things that we have traditionally used to help decide who benefits from radiation and who does not.

What were the findings from this study?

The most important finding of this study, in my opinion, is that the use of this testing led to a 38% change in radiation recommendations. Importantly, those changes went both ways. There were some patients who were initially recommended for radiation therapy who were subsequently not recommended to receive radiation. Conversely, there were patients who were not recommended radiation before testing who were then recommended radiation after testing based on finding an elevated risk.

Overall, this led to a net 20% reduction in the recommendation for radiation therapy. Additionally, the strongest factor associated with radiation decision making was the use of this test or the test results. This test was driving therapy for these patients with DCIS following breast conserving surgery.

What the study shows is that the use of the DCISionRT 7-gene biosignature is the factor that has the most significant impact on decision making. It is key for patients working with their clinicians and having an informed discussion about the benefits of radiation therapy.

Were there any findings that were surprising or unexpected?

The biggest thing that is probably surprising to some folks is that it really does not matter how you slice the case, whether it looks high-risk on paper or low-risk on paper, but the test is driving recommendations. Regardless of what we as clinicians may think, the test is allowing us to think through and understand each patient's case individually, and then make recommendations based on it.

What are the implications of these findings?

The biggest thing to take away from this research in conjunction with the research that's been shown on the clinical side, is kind of 2-fold. Number 1, the use of DCISionRT testing based on a couple of publications has shown that for patients who have low-risk DCIS it that there is no benefit to radiation therapy, whereas patients with elevated risk DCIS are to benefit from radiation. These findings, coupled with the current results, will show that use of the test changes the recommendations so that this test, as part of informed decision making, is a part of the standard of care for women with DCIS undergoing breast conserving surgery at this time.

How might the integration of the DCISionRT testing into clinical decision-making processes impact the future for these patients with breast cancer?

I think you're starting to see that today. First, we should be considering it for every patient with DCIS in our clinic. I certainly think we should at least be considering and discussing it with patients who are undergoing lumpectomies for DCIS. I think the next step is moving forward is how to incorporate this in the current clinical guidelines and research protocols that are evolved for these patients as well. I think that is something we expect to see in the years to come.

REFERENCE:

Shah CS, Whitworth PW, Shiver S, et al. Impact on radiation therapy recommendation and treatment modality for patients with ductal carcinoma in situ using the 7Gene biosignature: analysis of the PREDICT study. International Journal of Radiation Oncology. 2023;177 (1):e206. doi:10.1016/j.ijrobp.2023.06.1089