Prognostication and treatment predictions for estrogen receptor positive early-stage breast cancer: incorporating the 70-gene signature into the PREDICT prognostication model

Abstract

Background: The 70-gene signature (70-GS) has been shown to identify women at low-risk of distant recurrence who can safely forgo adjuvant chemotherapy. Incorporating this GS into the well-validated and widely used PREDICT breast cancer model could improve the model's ability to estimate breast cancer prognosis, and thereby further reduce overtreatment and its long-term impact on patients' quality of life. We incorporated the 70-GS into PREDICT-v2.3 and assessed the new PREDICT-GS model's ability to predict 5-year risk of breast cancer death.

Methods: Data from the MINDACT trial (N = 5920) was used to estimate the 70-GS's prognostic effect (coefficient = 0.70), which was then incorporated into PREDICT-v2.3. Netherlands Cancer Registry (NCR) data (N = 3323) was used to assess PREDICT-GS's discrimination (area under curve (AUC)), calibration and clinical utility.

Results: Compared to PREDICT-v2.3 (AUC: 0.71 (95 % CI: 0.63-0.79)), PREDICT-GS (AUC: 0.76 (95 % CI: 0.69-0.83)) had better discrimination. Both models tended to overestimate the 5-year risk of breast cancer death in the NCR cohort, but the absolute overestimation was smaller for PREDICT-GS. Regarding clinical utility, only at the 10 % decision threshold did we find modest improvement: four extra patients per 1000 tests were correctly classified as not needing chemotherapy by PREDICT-GS compared to PREDICT-v2.3.

Conclusion: Extending PREDICT-v2.3 with 70-GS led to modest improvement in its ability to predict 5-year risk of breast cancer death. Future research should focus on assessing the added value of the 70-GS for longer-term prediction of recurrence and death with the incorporation of quality of life in risk prediction tools.

Keywords: 70-Gene signature; Model extension; PREDICT for breast cancer model; Prognostication; Validation.