Survival of the Patients With Breast Cancer Who Underwent Oncotype DX Recurrence Score Testing: Long-Term Survival Update of a Prospective Multicenter Study in Turkiye According to Different Cut-Offs
Abstract
Background: Seventy percent of early-stage breast cancers are hormone receptor positive. In this prospectively designed study, we aim to update the long-term survival outcomes of chemotherapy decision-making according to Oncotype DX Recurrence Score (ODX-RS) and its relation with different cut-offs. Materials and methods: Ten academic centers in T & uuml;rkiye that routinely discuss all new cases at multidisciplinary tumor board participated. Consecutive patients who are pT1-3, pN0-N1mic, M0 were identified. Adjuvant treatment decisions were discussed at tumor board before and after ODX-RS results. Results: Of the 165 patients (26-76, median 48 years) with a median follow-up of 108 months, ODX-RS <= 25 had significantly better overall survival (OS) than those with ODX-RS >= 26 (p = 0.022). When evaluated by age, OS and disease-free survival (DFS) was significantly better with ODX-RS <= 15 in patients aged <= 50 years and with ODX-RS <= 25 in patients aged > 50 years (p = 0.034 and p = 0.024). ODX-RS <= 20 in patients aged <= 50 years and ODX-RS <= 25 in patients aged > 50 years had significantly better OS (p = 0.002). There was no difference in OS between those who received chemotherapy before ODX-RS and those who did not (p = 0.119). Conversely in the post-ODX-RS, ODX-RS predicted survival better and OS was lower in patients who received chemotherapy compared to those who did not (p = 0.020) meaning that ODX-RS can predict OS. The ODX-RS test significantly reduced overall chemotherapy-related costs, yielding a favorable ICER of $3787.5 per QALY gained, thus demonstrating its cost-effectiveness. Conclusions: The ODX-RS significantly influences treatment decisions resulting comparable survivals for patients who received chemotherapy and who did not. Different cut-offs have variable significant prognostic effect on survival prediction models.
