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. 2024 Feb 24;10(5):e27072.
doi: 10.1016/j.heliyon.2024.e27072. eCollection 2024 Mar 15.

A prognostic nomogram for predicting breast cancer survival based on mammography and AJCC staging

Zi-Han Yu  1   2 , Yun Lin  1 , Pei-Shan Wu  1 , Chao-Hsien Lee  3 , Chen-Pin Chou  1   4   5
Affiliations

A prognostic nomogram for predicting breast cancer survival based on mammography and AJCC staging

Zi-Han Yu et al. Heliyon. .

Abstract

Rationale and objectives: To develop a prognostic nomogram using mammography data and AJCC staging to predict breast cancer survival.

Materials and methods: A prognostic nomogram was created using data from 1000 women diagnosed with breast cancer at a medical cancer center in Taiwan between 2011 and 2015. The variables included age at diagnosis (≤60 or > 60 years), mammography purpose (screening or diagnostic), mammography modality (digital mammogram or digital breast tomosynthesis), and the 7th American Joint Committee on Cancer (AJCC) stage. The outcome predicted was breast cancer-related mortality. The nomogram utilized Kaplan-Meier analysis for all subsets and Cox proportional hazards regression analysis for prediction. The nomogram's accuracy was internally validated using the concordance index and receiver operating characteristic (ROC) curve analysis, focusing on 3-year and 5-year survival predictions.

Results: Participants' mean age at breast cancer diagnosis was 54 years (SD = 11.2 years). The 1-year, 3-year, and 5-year overall survival (OS) rates were found to be 99.7%, 95.3%, and 91.4%, respectively. The bootstrap-corrected concordance indices indicated the following: nomogram, 0.807 and AJCC, 0.759. A significant difference was observed between the nomogram's area under the curve (AUC) and the AJCC stage in predicting the probability of 5-year survival (p = 0.005). A nomogram, constructed based on mammography and AJCC, demonstrated excellent calibration through internal validation using bootstrapping.

Conclusion: The utilization of a nomogram that incorporates mammography data and the AJCC registry data has been demonstrated to be a reliable predictor of breast cancer survival.

Keywords: AJCC staging; Breast cancer; Breast cancer survival; Mammography; Nomogram.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Flowchart of the model selection process.
Fig. 2
Fig. 2
The figure displays Kaplan-Meier (K–M) curves that demonstrate the overall survival (OS) rates for various pathological stages according to the 7th edition of the American Joint Committee on Cancer (AJCC) staging system.
Fig. 3
Fig. 3
A nomogram predicts 3- and 5-year survival rates for breast cancer patients, utilizing vertical lines from each factor to the corresponding point score.
Fig. 4
Fig. 4
Calibration curves for the nomogram model predict survival rates in breast cancer patients at 3 years (A) and 5 years (B). The nomogram-predicted probability of overall survival is plotted on the x-axis, and the actual overall survival estimated by the Kaplan-Meier method is plotted on the y-axis. The closer the points are to the 45-degree line, the higher the prediction accuracy.
Fig. 5
Fig. 5
Comparisons of prediction performance using receiver operating characteristic (ROC) curves. (A) Model accuracy in predicting 3-year and 5-year survival rates using a nomogram. (B) Model accuracy in predicting 5-year survival rates using a nomogram and the 7th edition of the American Joint Committee on Cancer (AJCC) staging system. The x-axis represents 1-Specificity, while the y-axis represents Sensitivity.
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