RSClin® Tool N+ gives more accurate estimates of recurrence risk and individual chemotherapy benefit in node-positive breast cancer

A new statistical tool that combines multiple clinical and pathologic factors with a patient's 21-gene Oncotype DX Breast Recurrence Score^® result provides more accurate estimates about that patient’s breast cancer prognosis and their potential benefit from chemotherapy than either the Recurrence Score^® result or clinical factors alone. 

The tool could be used in counseling patients with hormone receptor-positive (HR+), HER2-negative breast cancer that has spread to the lymph nodes, and could improve shared decision-making about treatment. The work, published in the Journal of Clinical Oncology (https://doi.org/10.1200/JCO-24-01507), was carried out by a team from the SWOG Cancer Research Network, a clinical trials group funded by the National Cancer Institute (NCI), part of the National Institutes of Health (NIH).

“Joint patient–physician decision making about administering adjuvant chemotherapy requires individualized predictions of absolute prognostic risk and absolute chemotherapy benefit,” said lead author Lajos Pusztai, MD, DPhil. 

“Aggregate clinical trial results inform about overall benefit seen in the entire study population (e.g., the improvement in median disease-free survival), but these metrics do not accurately reflect patient-level prognosis and treatment benefit. Our goal was to develop a patient-level prognostic and chemotherapy benefit predictor.” 

Dr. Pusztai is professor of medicine at Yale Cancer Center and is chair of SWOG’s breast cancer research committee.

The new tool is known as RSClin Tool N+, and the underlying model was developed using data from more than 5,000 patients, including both premenopausal and postmenopausal women, on two large breast cancer trials led by SWOG within the NCI’s National Clinical Trials Network – the S8814 trial and the S1007 RxPONDER trial. 

RSClin Tool N+ incorporates data on Recurrence Score result, tumor size, histologic grade, the number of involved lymph nodes, and the patient’s age into a multivariate statistical model. The tool can be used to provide improved estimates of recurrence risk for a patient treated with endocrine therapy alone, along with an estimate of how much this risk would decrease if that patient also underwent chemotherapy.

A personalized risk reduction estimate of this sort can help a patient come to an informed decision with their physician as to whether to add chemotherapy to their standard endocrine therapy.

To assess how accurately RSClin Tool N+ risk estimates match actual patient outcomes, the researchers validated the model against data from the Clalit Health Services registry on 573 patients with node-positive breast cancer. A high level of concordance between risk predictions and observed outcomes confirmed the model’s validity. 

The tool complements the earlier RSClin^® Tool N0, which provides similar prognostic information for patients with HR+, HER2-negative breast cancer that is lymph node negative (that is, the disease has not spread to the lymph nodes).

RSClin Tool N+ is now available to physicians in the United States, Canada, and Israel via the Exact Sciences website (portal.exactsciences.com).

This work was supported by NCI/NIH grants U10CA180888, U10CA180819, and U24CA196175 to the SWOG Cancer Research Network, and in part by Exact Sciences Corporation (through its wholly owned subsidiary Genomic Health, Inc.) and The Hope Foundation for Cancer Research.

In addition to Dr. Pusztai, authors include Jess R. Hoag, PhD, Exact Sciences Corporation; Kathy S. Albain, MD, Loyola University Chicago Stritch School of Medicine; William E. Barlow, PhD, SWOG Statistics and Data Management Center and Fred Hutch Cancer Center; Salomon M. Stemmer, MD, Tel Aviv University and Rabin Medical Center, Israel; Allison Meisner, PhD, Fred Hutch Cancer Center; Gabriel N. Hortobagyi, MD, University of Texas MD Anderson Cancer Center; Steven Shak, MD, Exact Sciences Corporation; James M. Rae, PhD, University of Michigan; Rick Baehner, MD, Exact Sciences Corporation; Priyanka Sharma, MD, University of Kansas Medical Center; and Kevin M. Kalinsky, MD, PhD, Emory University School of Medicine.

SWOG Cancer Research Network is part of the National Cancer Institute's National Clinical Trials Network and the NCI Community Oncology Research Program and is part of the oldest and largest publicly funded cancer research network in the nation. SWOG has 20,000 members in 45 states and eight other countries who design and conduct clinical trials to improve the lives of people with cancer. SWOG trials have directly led to FDA approval of 14 cancer drugs, changed more than 100 standards of cancer care, and saved more than 3 million years of human life. Learn more at swog.org, and follow us on Twitter/X at @SWOG.
 

Reference:
“Development and Validation of the RSClinN+ Tool to Predict Prognosis and Chemotherapy Benefit for Hormone Receptor–Positive, Node-Positive Breast Cancer.” J Clin Oncol, published online Dec. 2, 2024. https://doi.org/10.1200/JCO-24-01507
 

NOTE: Oncotype, Oncotype DX Breast Recurrence Score, Breast Recurrence Score, and Recurrence Score are registered trademarks of Genomic Health, Inc., a wholly owned subsidiary of Exact Sciences. Exact Sciences is a registered trademark of Exact Sciences Corporation.