Prognostic nomogram based on immune scores for breast cancer patients

BACKGROUND: Increased attention has been focused on cancer immunity gene signature. However, the threshold of immune scores to predict disease‐free survival (DFS) and overall survival (OS) in breast cancer has not yet been defined. This study aimed to explore the association of immune scores with prognosis and build a clinical nomogram to predict the survival of patients with breast cancer. METHODS: A total of 986 subjects were analyzed, and clinicopathological characteristics and immune scores were obtained from the TCGA database. Cox proportional hazards regression model was used to estimate the adjusted hazard ratios (HRs). Based on results of multivariate analysis, nomograms were built. The models were subjected to bootstrap internal validation. The predictive accuracy and discriminative ability were measured by concordance index (C‐index) and the calibration curve. RESULTS: The patients were divided into three subgroups according to their immune scores. We found that compared with patients with low immune scores, those with intermediate and high immune scores had significantly improved DFS (HR and 95% confidence interval [CI]: 0.439 [0.242‐0.799], 0.541 [0.343‐0.855], respectively), whereas only intermediate immune scores significantly indicated better OS (HR and 95% CI: 0.385 [0.163‐0.910]). The C‐index for DFS and OS prediction was 0.723 (95% CI, 0.661‐0.785) and 0.800 (95% CI, 0.724‐0.877), respectively. The calibration curves for probability of 3‐ and 5‐year DFS showed significant agreement between nomogram predictions and the actual observations. CONCLUSIONS: High and/or intermediate immune scores are significantly correlated with better DFS and OS in patients with breast cancer. Moreover, the nomograms for predicting prognosis may help to estimate the survival of patients.