Printer Friendly

New Tool for Predicting Recurrence Risk

October 18, 2011

Researchers have developed a new tool which uses the recurrence score (RS) from the Oncotype Dx assay plus pathological and clinical information to come up with a risk of recurrence.  In a recent article in the Journal of Clinical Oncology, researchers describe development of the RS-pathology-clinical (RSPC) model.

Dr. Gong Tang and colleagues used a meta-analytic process to combine prediction results from two models developed using data from patients with ER-positive breast cancer who received adjuvant endocrine therapy in the following trials:  the National Surgical Adjuvant Breast and Bowel Project (NSABP) B-14 study (n=647) and the Arimidex, Tamoxifen Alone or in Combination Trial (TransATAC; n=1,088).  Predictive variables in the models included tumor size, tumor grade, age, and the RS values, and the TransATAC model also included nodal status and type of endocrine therapy. The primary prediction end point was 10-year risk of distant recurrence.

Comparing the RS and RSPC tools in node-negative patients, the average risk of distant recurrence was not statistically significantly different for the low-, intermediate-, and high-risk cohorts.  However, the results suggest that the individual outcomes are more accurately predicted by the RSPC.  The RSPC classifed 63.8% of patients as having low risk while RS classified 54.2% as low risk.  Compared to RS alone, RSPC classified fewer patients as having intermediate risk (17.8% versus 26.7%).

According to the authors, "RSPC refines the assessment of distant recurrence risk and reduces the number of patients classified as intermediate risk."  However, RSPC showed a reduced ability to predict chemotherapy benefit.  This tool still needs to be independently validated in a large, randomized trial.