Residual cancer burden offers predictive response measure across breast cancer subtypes
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Measurement of residual cancer burden served as both an accurate and consistent indicator of prognosis across breast cancer subtypes, according to an analysis of data from the randomized I-SPY2 trial published in JAMA Oncology.
Researchers also found that use of an investigational treatment on the trial to lower residual cancer burden (RCB) was associated with a lower risk for recurrence compared with standard chemotherapy.
“The consistent take-home message is that in the setting of molecularly high-risk cancers, eradication by chemotherapy or targeted agents confers an excellent prognosis, independent of where you started, what stage of cancer,” Laura J. Esserman, MD, MBA, surgeon, breast cancer oncology specialist and director of the UCSF Breast Cancer Center at UCSF Helen Diller Family Comprehensive Cancer Center, told Healio. “Importantly, there are a lot more data on RCB than simply pathologic complete response (RCB = 0), yes or no. Having a lot of disease is much worse than having a modest amount. And having minimal disease is almost as good as complete response.”
Esserman and colleagues sought to use the data from the I-SPY2 trial — which compares, by subtype, investigational agents plus chemotherapy with chemotherapy alone among adult women with stage II or stage III breast cancer at high risk for early recurrence — to determine whether the pattern of and prognosis for RCB after neoadjuvant chemotherapy for breast cancer varied by subtype and treatment.
The analysis included 938 women (mean age, 49 years; standard deviation, 11; 80% white; 11% Black, 7% Asian) from the first 10 investigational agents. Within I-SPY2, investigational treatments graduated within a high-risk subtype of breast cancer if real-time Bayesian statistical modeling predicted an 85% or greater likelihood of increased pathologic complete response rates from a 300-patient, randomized 1:1, subtype-specific phase 3 trial, researchers wrote. They evaluated secondary endpoints from the 10 investigational agents tested from March 2000 through March 2016 and analyzed as of Sept. 9, 2020.
The analysis included comparing control and investigational treatments that graduated with those that did not graduate, in addition to modeling of RCB within subtypes defined by hormone receptor and ERBB2 status.
Median follow-up was 52 months (interquartile range, 29 months).
Results showed EFS worsened significantly per unit of RCB in every breast cancer subtype, including hormone receptor-positive/ERBB2-negative (HR = 1.75; 95% CI, 1.45-2.16), hormone receptor-positive/ERBB2-positive (HR = 1.55; 95% CI, 1.18-2.05), hormone receptor-negative/ERBB2-positive (HR = 2.39; 95% CI, 1.64-3.49), and hormone receptor-negative/ERBB2-negative (HR = 1.99; 95% CI, 1.71-2.31). In addition, researchers obtained similar prognostic information from RCB from treatments that graduated (27%; HR = 2; 95% CI, 1.57-2.55), did not graduate (52%; HR =1.87; 95% CI, 1.61-2.17), or were used in the control group (21%; HR = 1.79; 95% CI, 1.42-2.26).
In the exploratory analysis, investigational treatments significantly lowered RCB in hormone receptor-negative/ERBB2-negative (both graduated and non-graduated treatments) and ERBB2-positive subtypes (graduated treatments), with improved EFS (HR = 0.61; 95% CI, 0.41-0.93).
“The key is that the amount of disease left over can and should inform physicians about the next steps for care,” Esserman said.
Esserman added that the method also included localization of the tumor area and specific ways to cut and assess the specimen — rules that helped to standardize the method and information gained.
Investigators concluded that RCB after neoadjuvant chemotherapy, when compared with randomized treatments, is likely to be a clinically useful measure of efficacy and that the survival benefit of a specific treatment may be reflected in changes to the RCB distribution, with a larger shift implying a greater probability of efficacy.
"About 15 years ago, I heard [study co-author] William Fraser Symmans, MB, ChB, [professor in the department of pathology at The University of Texas MD Anderson Cancer Center] give his talk on RCB index for the first time at ASCO,” Esserman said. “I was running I-SPY1 at the time. The minute I saw the data, I knew that MRI volume would be predictive, too, and it could be measured over time without having to operate first.
“And all of that turned out to be true,” Esserman continued. “We are now integrating MRI volume and RCB index to get additional information-synergy.”
Esserman and colleagues called for larger randomized clinical trials to continue the research. They added that as novel regimens are evaluated in the I-SPY2 trial, RCB will be “interpreted as a co-primary endpoint and used to estimate survival benefit from novel treatments in addition to prognostic surrogacy.”
“RCB index is really important in assessing the overall benefit, not just a ‘yes’ or ‘no’ pathologic response,” Esserman told Healio. “The distribution of RCB index is what gives an even better indication of outcome. We can capture that with treatment efficacy score.”
For more information:
Laura J. Esserman, MD, MBA, can be reached at UCSF Breast Care Center, 1825 4th St., Box 1710, PCMB 3rd Floor, San Francisco, CA 94158; email: laura.esserman@ucsf.edu.
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