Measuring Residual Cancer Burden Could Help Improve Predictions of Breast Cancer Outcomes

Residual cancer burden, or the amount of cancer cells that remain following treatment with chemotherapy, can help physicians pinpoint accurate long-term predictions about the likelihood that a patient’s breast cancer will return, as well as the likelihood and duration that a patient will survive, according to a large meta-analysis of patients with breast cancer presented at the San Antonio Breast Cancer Symposium (SABCS).

The meta-analysis, which is a study that analyzes the results of several studies on one subject, was led by Dr. W Fraser Symmans, professor and director of research operations in the department of pathology at The University of Texas MD Anderson Cancer Center in Houston.

In the study, Symmans and his colleagues from the I-SPY Clinical Trials Consortium compiled and analyzed data that represented roughly 5,100 patients. They examined associations between residual cancer burden index and event-free survival, which is the length of time after treatment ends that the patient remains free from the complications that the treatment was intended to delay, as well as distant recurrence-free survival, or the amount of time after treatment that a patient’s disease did not return.

In a statement, Symmans explained that residual cancer burden is assessed through several factors. These include size of the primary tumor, percentage of the tumor that spreads or remains in one location and the involvement of lymph nodes. Moreover, to make more accurate predictions, patients with residual cancer burden were classified into three separate groups by severity of their burden: RCB-1 (minimal burden), RCB-2 (moderate burden) and RCB-3 (extensive burden).

“The most interesting result in my opinion is that when you look at the residual cancer burden index scores and you look at that as a function of survival, you can see a log-linear relationship,” Symmans said during a press conference at the symposium, held Dec. 10-14, in San Antonio, Texas. “The implication of this result is that you can take an individual patient’s score of how much residual cancer burden they have and calibrate that to an accurate estimate of their risk over time.”

For patients who were hormone receptor (HR)-positive and HER2-negative, 11% were classified as having a pathologic compete response, meaning they lacked all signs of cancer in tissue samples or biopsy after treatment. For HR-positive, HER2-positive patients, 38% were classified as having a pathologic compete response.

“The measurement of (residual cancer burden) index is strongly prognostic, allowing us to measure risk of recurrence with confidence,” Symmans said in a statement. “This meta-analysis of residual cancer burden provides real-world evidence of how patients are responding to neoadjuvant treatments, and calibration of (residual cancer burden) index to prognostic risk enables us to determine the most appropriate next steps for breast cancer patients.”

In patients who were HR-negative,HER2-positive, 69% were classified as having a pathologic compete response. And for patients who were HR-negative, HER2-negative, 43% were classified as having a pathologic compete response.

Residual cancer burden was also measured in these patients. According to the results, their residual cancer burden levels were as follows at the 10-year follow-up date:

• HR-positive, HER2-negative patients: 19% of the pathologic compete response group had a recurrence or died, compared with 14% in RCB-1, 31% in RCB-2, and 48% in RCB-3.
• HR-positive, HER2-positive: 9% of the pathologic compete response group had a recurrence or died, compared with 17% in RCB-1, 36% in RCB-2, and 55% in RCB-3.
• HR-negative, HER2-positive: 7% of the pathologic compete response group had a recurrence or died, compared with 15% in RCB-1, 37% in RCB-2 and 40% in RCB-3.
• HR-negative/HER-2 negative: 14% of the pathologic compete response group had recurrence or died, compared with 25% in RCB-1, 39% in RCB-2, and 75% in RCB-3.

While results suggested that these prognostic indicators could be strong and reliable, the study was limited in that it was based on data from multiple different institutions that used variation in their methods for collecting data.

“Looking ahead, if we can standardize the reporting of residual cancer burden, that will only improve its usefulness in determining long-term prognosis,” Symmans said.