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Background Breast cancer mortality has decreased due to improved screening and treatment options. Nevertheless, 25–30% of patients develop disease recurrence and die from the disease dissemination. Patients who develop metastatic disease represent a heterogeneous group and management plans are dependent on molecular subtype, disease burden and metastatic site. Aim To determine predictive clinicopathological factors of disease recurrence and their impact on survival in the molecular era. Methods Consecutive patients who breast cancer developed recurrence at our tertiary referral centre between 2000 and 2015 were included. Clinicopathological and treatment data were assessed using descriptive statistics. Oncological outcome was assessed using Cox regression and Kaplan Meier analyses. Results Two hundred sixty-five consecutive patients who developed breast cancer recurrence were included; median age at metastasis was 59.3 years (range 27–87 years), and median time to recurrence (TTR) was 47.7 ± 38.5 months (range 3.0–194.3 months). Survival was 24.2% (64/265) 53.2% were luminal A (LABC) (141/265), 18.5% were luminal B (LBBC) (49/265), 18.5% were triple negative (TNBC) (49/265), and 9.8% were human epidermal growth factor receptor-2 overexpressing (HER2 +) (26/265). TTR for patients with LABC was 56.0 ± 41.3 months, LBBC was 48.4 ± 41.1 months, TNBC was 26.9 ± 28.5 months and HER2 + was 34.3 ± 21.8 months. Increased grade (P P P P (P = 0.006) predicted shorted TTR. Estrogen receptor positivity (P P = 0.010), invasive lobular carcinoma (P = 0.009) and receiving endocrine therapy (P = 0.001) predicted longer TTR. Conclusion Readily available clinicopathological factors predict risk of metastatic dissemination. Developing a tailored program to identify patients at risk of recurrence is crucial in controlling metastatic dissemination of breast cancer.

Background: OncotypeDX Recurrence Score© (RS) is a commercially available 21-gene expression assay which estimates prognosis and guides chemoendocrine prescription in early-stage estrogen-receptor positive, human epidermal growth factor receptor-2-negative (ER+/HER2−) breast cancer. Limitations of RS testing include the cost and turnaround time of several weeks. Aim: Our aim is to develop a user-friendly surrogate nomogram capable of predicting RS. Methods: Multivariable linear regression analyses were performed to determine predictors of RS and RS > 25. Receiver operating characteristic analysis produced an area under the curve (AUC) for each model, with training and test sets were composed of 70.3% (n = 315) and 29.7% (n = 133). A dynamic, user-friendly nomogram was built to predict RS using R (version 4.0.3). Results: 448 consecutive patients who underwent RS testing were included (median age: 58 years). Using multivariable regression analyses, postmenopausal status (β-Coefficient: 0.25, 95% confidence intervals (CIs): 0.03–0.48, p = 0.028), grade 3 disease (β-Coefficient: 0.28, 95% CIs: 0.03–0.52, p = 0.026), and estrogen receptor (ER) score (β-Coefficient: −0.14, 95% CIs: −0.22–−0.06, p = 0.001) all independently predicted RS, with AUC of 0.719. Using multivariable regression analyses, grade 3 disease (odds ratio (OR): 5.67, 95% CIs: 1.32–40.00, p = 0.037), decreased ER score (OR: 1.33, 95% CIs: 1.02–1.66, p = 0.050) and decreased progesterone receptor score (OR: 1.16, 95% CIs: 1.06–1.25, p = 0.002) all independently predicted RS > 25, with AUC of 0.740 for the static and dynamic online nomogram model. Conclusions: This study designed and validated an online user-friendly nomogram from routinely available clinicopathological parameters capable of predicting outcomes of the 21-gene RS expression assay.