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Updated: Jun 9, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Survival Risk Score for Invasive Nonmetastatic Breast Cancer: A Real-World Analysis
Lucia Mangone1, Fortunato Morabito2, Giovanni Tripepi3
1Epidemiology Unit, Azienda USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Purpose:
This study aimed to develop a multivariable, weighted overall survival (OS) risk score (SRS) for nonmetastatic (M0) invasive breast cancer (M0-BC, SRSM0-BC).
Materials And Methods:
This study included a training (1,890 patients) and a validation cohort (850 patients) from the Reggio Emilia Cancer Registry (RE-CR). Ten traditional prognostic variables were evaluated.
Results:
In the training set, all the variables but the human epidermal growth factor receptor were significantly associated with OS at univariable analysis. A multivariable model identified an increased death risk for estrogen receptor (hazard ratio [HR], 2.0 [95% CI, 1.1 to 3.1]; P = .021), tumor stages T2-T3 (HR, 2.4 [95% CI, 1.3 to 4.7]; P = .009) and T4 (HR, 5.1 [95% CI, 2.0 to 13.0]; P < .001), and age >74 years (HR, 5.7 [95% CI, 4.0 to 8.2]; P < .001). By assigning scores according to HRs, four risk categories were generated (P for trend <.001). The HRs of death in the high- (282 patients, 15.6%), intermediate-high (275 patients, 15.2%), and intermediate-risk (349 patients, 19.2%) categories patients were, respectively, 27.3, 12.9, and 3.5 times higher, compared with the low-risk (909 patients, 50%) group. Harrell'C index was 81.1%, and the explained variation in mortality was 66.6. Internal cross-validation performed on the accrual index dates yielded a Harrell'C index ranging from 79.5% to 82.3% and an explained variation in mortality ranging from 60.3% to 69.4%. In the validation set, the same risk categories (P for trend <.001) were devised. The Harrell'C index and the explained variation in mortality were 76.1% and 53.7%, respectively, in the whole cohort, maintaining an elevated percentage according to the two accrual index dates.
Conclusion:
SRSM0-BC using the real-world RE-CR data set may represent a low-cost, accessible, globally applicable model in daily clinical practice, helping to prognostically stratify patients with invasive M0-BC.
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