By: Jeff Minerd
Online calculators, composite scores, and genetic assays can all inform treatment decisions
Premenopausal women with hormone receptor-positive, early-stage breast cancer often present with more complex disease. They tend to require multimodality therapy and have inferior survival outcomes compared with postmenopausal women, noted Ines Vaz-Luis, MD, PhD, of Institut Gustave Roussy in Villejuif, France, and co-authors, writing in a review in the 2021 ASCO Educational Book.
However, tools are available to help clinicians more precisely predict risk and determine the prognosis for these patients. Such tools can also inform treatment decisions, including about chemotherapy and endocrine therapy, and whether or not novel strategies will be effective. “Risk stratification strategies, including classic clinicopathologic features and newer gene expression assays, can assist in treatment decisions, including adjuvant chemotherapy use and type or duration of endocrine therapy,” the authors wrote.
In the following interview, Vaz-Luis elaborated on the workings of some of these currently available tools.
What are some of the most useful online risk calculators available, and what kinds of decisions can they help inform?
Vaz-Luis: Common tools include the National Health Service Predict tool, based on a U.K. cancer registry database, and CancerMath, derived from the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program.
Such tools can help providers balance the benefit of adding up different treatment modalities by giving an individual patient’s risk of breast cancer recurrence and death in the different treatment scenarios.
Your review also covered composite scores. What are these, and how can they be used?
Vaz-Luis: These tools aggregate several individual biomarkers and can be used to inform treatment decisions. Clinical Treatment Score post-5 years predicts the risk of late distant recurrence after 5 years of endocrine therapy. This one is actually available as an online calculator and can be quite informative for extension of adjuvant endocrine therapy discussions.
Immunohistochemistry 4 is based on standard laboratory evaluations of estrogen receptor, progesterone receptor, HER2, and Ki-67. This score is prognostic for outcome, but not predictive for the choice of endocrine therapy. One concern that limits the use of this score is that Ki-67 is not always used in clinical practice.
Multi-parameter gene expression assays are another type of risk assessment tool. What can you advise clinicians about these?
Vaz-Luis: These assays add to classical clinical pathological information, providing information that in some cases is prognostic and in some cases even predictive of response to systemic treatments. Examples include Oncotype DX and Mammaprint.
There are clinical scenarios where these can be very informative regarding the addition of chemotherapy to endocrine therapy. For example, for premenopausal patients with low clinical risk and who are node negative, a low Oncotype score (i.e., less than 15) can inform the decision to forgo chemotherapy.
Are there any new risk-prediction tools in development that may soon be available to aid oncologists?
Vaz-Luis: I’m not sure if we have any emergent tools different from the ones we mentioned, but I think we are moving to tools that will also be incorporating the risk of toxicities of treatments, as in this study in the CANcer TOxicity (CANTO) cohort.
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