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

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.
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.
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.
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.