Nomograms for the prognosis prediction model of early-stage triple-negative breast cancer - based on SEER database

AIMS: Triple-negative breast cancer (TNBC) is aggressive and unresponsive to hormone therapy, drawing widespread attention to its treatment and prognosis. This study aimed to summarize the prognosis of early-stage TNBC and construct nomograms to accurately predict survival and improve treatment strategies. PATIENTS & METHODS: The modeling group comprised early-stage TNBC patients from the SEER database. Prognostic factors were identified via Cox regression, and nomograms were developed using R software. A validating group with identical screening criteria was assembled from Sun Yat-sen University Cancer Center. Validation involved the Concordance index, Receiver Operating Characteristic curves, and calibration curves. RESULTS: The modeling group included 14,389 patients and the validating group 1,146. Age and seven other factors were independent predictors (P < 0.05) and were incorporated into the nomograms. The C-indices for disease-free survival were 0.884 (95% CI: 0.876-0.892) in the modeling group and 0.686 (95% CI: 0.653-0.719) in the validating group. For overall survival, C-indices were 0.873 (95% CI: 0.863-0.883) and 0.741 (95% CI: 0.702-0.780), respectively. CONCLUSIONS: The constructed nomograms demonstrated good predictive performance and may serve as practical tools for risk stratification in early-stage TNBC. However, given the observational nature of the data, the associations between treatment-related factors and survival should be interpreted with caution and warrant confirmation in prospective studies.