Survival of the Patients With Breast Cancer Who Underwent Oncotype DX Recurrence Score Testing: Long‐Term Survival Update of a Prospective Multicenter Study in Türkiye According to Different Cut‐Offs

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 Türkiye 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.