Individualized breast cancer survival prediction in clinical practice: a SEER-derived interactive web tool integrating molecular and anatomical factors.

Background

Accurate patient-level risk prediction supports treatment decisions in breast cancer. Using the U.S. Surveillance, Epidemiology, and End Results (SEER) registry, we developed and internally validated an interactive web-based survival calculator integrating molecular and anatomical predictors.

Methods

We analysed 1 742 998 women diagnosed with breast cancer in SEER between 2010 and 2020, when human epidermal growth factor receptor 2 (HER2) ascertainment was reliable. Predictors included age at diagnosis, HER2, oestrogen/progesterone receptor (ER/PR) status, and American Joint Committee on Cancer (AJCC) 6th-edition tumour, node, metastasis (TNM) staging. HER2 was recoded to separate equivocal from unknown/untested cases. A multivariable Cox model was fitted and assessed on a held-out 30% sample using discrimination and calibration. Robustness was evaluated using stratified Cox, Royston-Parmar flexible parametric, and restricted mean survival time (RMST) analyses.

Results

Discrimination was good (Harrell C-index 0.72; time-dependent area under the time-dependent receiver operating characteristic (ROC) curve 0.76-0.78 at 12-120 months) with close calibration. Older age, distant metastasis, advanced T stage, nodal involvement, and ER/PR-negative status independently increased mortality. HER2-positive disease showed lower risk, whereas equivocal and unknown HER2 had higher risk. Findings remained stable across sensitivity analyses; RMST showed ~ 61 fewer restricted-mean survival months for M1 disease.

Conclusion

The tool provides individualized survival probabilities from routine clinical and molecular inputs. It is prognostic, not predictive, and should complement rather than replace clinical judgement alone.