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Online Tool Refines Individual Risks in Breast Cancer

<ѻý class="mpt-content-deck">— RSClin incorporates 21-gene recurrence score with tumor grade, size, and more
MedpageToday

SAN ANTONIO -- An online tool, which incorporates clinicopathological data and the results of the 21-gene recurrent score, was able to estimate risk of distant recurrence (DR) and adjuvant chemotherapy benefit in certain patients with breast cancer, a researcher reported.

The RSClin tool integrates the recurrence score (RS) with tumor grade, tumor size, and age using a patient-specific meta-analysis that included 10,004 women with hormone receptor-positive, HER2-negative, and node-negative breast cancer who received endocrine therapy alone in the trial, or with chemotherapy in the trial, explained Joseph Sparano, MD, of Montefiore Medical Center and the Albert Einstein College of Medicine in New York City, at the San Antonio Breast Cancer Symposium virtual meeting. The study was simultaneously published in the.

"In external validation, the RSClin risk estimate was prognostic for disease recurrence risk in the Clalit registry (P<0.001) and the estimated risk closely approximated the observed 10-year risk (Lin concordance 0.962)," Sparano and colleagues wrote, adding that the estimated risk calculated significantly correlated with risk of DR (hazard ratio 1.73, 95% CI 1.40-2.15, P<0.001).

In addition, "RSClin provides more prognostic information (likelihood ratio x) for DR than RS or clinical-pathological factors alone (both P<0.001, likelihood ratio test)," they stated. "The absolute chemotherapy benefit estimate ranges from 0% to 15% as the RS ranges from 11 to 50 using RSClin in a 55 year-old woman with a 1.5-cm intermediate-grade tumor."

Sparano's group concluded that "The RSClin tool integrates clinical-pathological and genomic risk to guide adjuvant chemotherapy in node-negative breast cancer and provides more individualized information than clinical-pathological or genomic data alone."

In an in the journal, Dawn L. Hershman, MD, and Katherine D. Crew, MD, both of Columbia University in New York City, noted that the RSClin tool is "further refining results from tumor molecular assays by adding back clinical-pathological features to provide more accurate estimates of breast cancer recurrence.

They also praised the authors for reanalyzing "the data to report the risk of distant recurrence, an outcome that is increasingly important for decision making."

However, they cautioned that cancer specialists cannot rely too heavily on such tools. First, because molecular assays have inherent limitations, such as the "inability to account for tumor heterogeneity, tumor sampling of multifocal disease, and varying compliance to long-term endocrine therapy," they pointed out.

Also, "molecular assays are designed to inform clinical decisions about the receipt of chemotherapy but not the type of chemotherapy regimen to administer," Hershman and Crew stated. "Along with breast cancer recurrence, other important considerations for clinical decision making about adjuvant treatment include competing comorbidities, acute and chronic toxicities from chemotherapy and long-term endocrine therapy, survivorship issues such as fertility and quality of life, and patient preferences."

"Therefore, oncologists still, and will always, need to use their clinical judgment and communication skills to engage in shared decision making to optimize care for their patients with breast cancer," they said.

Disclosures

Sparano disclosed relevant relationships with MetaStat, Genentech/Roche, Novartis, AstraZeneca, Celgene, Lilly, Celldex, Pfizer, Prescient Therapeutics, Juno Therapeutics, Merrimack, Adgero Biopharmaceuticals, Cardinal Health, GlaxoSmithKline, CStone Pharmaceuticals, Epic Sciences, Daiichi Sankyo, Prescient Therapeutics, Deciphera, Merck, Merrimack, Radius Health, Menarini Silicon Biosystems, Myriad Genetics, Pfizer, AstraZeneca, and Rhenium.

Hershman and Crew disclosed support from the American Cancer Society.

Primary Source

Journal of Clinical Oncology

Sparano J, et al "Clinical-Pathological Features to Individualize Prognosis and Prediction of ChemotherapyBenefit in Early Breast Cancer" J Clin Oncol 2020; DOI: 10.1200/JCO.20.03007.

Secondary Source

Journal of Clinical Oncology

Crew KD and Hershman DL "Better Together: Clinical and Genomic Data to Inform Shared Decision Making" J Clin Oncol 2020; DOI:10.1200/JCO.20.