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. 2023 Feb 24:14:1119105.
doi: 10.3389/fendo.2023.1119105. eCollection 2023.

A novel conditional survival nomogram for monitoring real-time prognosis of non-metastatic triple-negative breast cancer

Xiangdi Meng  1 , Yuanyuan Cai  1 , Xiaolong Chang  1 , Yinghua Guo  1
Affiliations

A novel conditional survival nomogram for monitoring real-time prognosis of non-metastatic triple-negative breast cancer

Xiangdi Meng et al. Front Endocrinol (Lausanne). .

Abstract

Background: Conditional survival (CS) is defined as the possibility of further survival after patients have survived for several years since diagnosis. This may be highly valuable for real-time prognostic monitoring, especially when considering individualized factors. Such prediction tools were lacking for non-metastatic triple-negative breast cancer (TNBC). Therefore, this study estimated CS and developed a novel CS-nomogram for real-time prediction of 10-year survival.

Methods: We recruited 32,836 non-metastatic TNBC patients from the Surveillance, Epidemiology, and End Results (SEER) database (2010-2019), who were divided into training and validation groups according to a 7:3 ratio. The Kaplan-Meier method estimated overall survival (OS), and the CS was calculated using the formula CS(y|x) =OS(y+x)/OS(x), where OS(x) and OS(y+x) were the survival of x- and (x+y)-years, respectively. The least absolute shrinkage and selection operator (LASSO) regression identified predictors to develop the CS-nomogram.

Results: CS analysis reported gradual improvement in real-time survival over time since diagnosis, with 10-year OS updated annually from an initial 69.9% to 72.8%, 78.1%, 83.0%, 87.0%, 90.3%, 93.0%, 95.0%, 97.0%, and 98.9% (after 1-9 years of survival, respectively). The LASSO regression identified age, marriage, race, T status, N status, chemotherapy, surgery, and radiotherapy as predictors of CS-nomogram development. This model had a satisfactory predictive performance with a stable 10-year time-dependent area under the curves (AUCs) between 0.75 and 0.86.

Conclusions: Survival of non-metastatic TNBC survivors improved dynamically and non-linearly with survival time. The study developed a CS-nomogram that provided more accurate prognostic data than traditional nomograms, aiding clinical decision-making and reducing patient anxiety.

Keywords: conditional survival; nomogram; overall survival; prognostic factor; triple-negative breast cancer.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow chart for screening patients with non-metastatic triple-negative breast cancer.
Figure 2
Figure 2
Survival analysis of non-metastatic triple-negative breast cancer. (A) Kaplan–Meier curves estimating real-time survival after surviving for 0-9 years; (B) CS(1|x) curve showing the probability of survival another year after surviving for x years since diagnosis and 10-year CS curve showing the 10th year of survival after surviving for x years since diagnosis; (C) Annual hazard rate curve. CS, conditional survival.
Figure 3
Figure 3
Predictor screening. (A) The least absolute shrinkage and selection operator (LASSO) regression and (B) 10-fold cross-validation.
Figure 4
Figure 4
Conditional survival nomogram (CS-nomogram) predicting 5- and 10-year overall survival (OS) and 10-year conditional survival (CS) for non-metastatic triple-negative breast cancer. AJCC-8th, American Joint Committee on Cancer (8th Edition); BCS, breast conservation surgery.
Figure 5
Figure 5
Model evaluation and validation. (A-B) Calibration plots, (C) Time-dependent area under curve (AUC) curves, and (D-E) decision curve analysis (DCA) curves for assessing the accuracy, discrimination and clinical usefulness of the conditional survival nomogram (CS-nomogram).
See this image and copyright information in PMC

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