Resilience index improves prediction of 1-year decreased quality of life in breast cancer.

Abstract

Resilience is important in cancer survivorship and has great potential to predict long-term quality of life (QoL) in breast cancer. The study was designed to develop a new prediction model to estimate pretest probability (PTP) of 1-year decreased QoL combing Resilience Index (RI) and conventional risk factors. RI was extracted from 10-item Resilience Scale Specific to Cancer (RS-SC-10) based on the Principal Component Analysis (PCA). Patients were enrolled from Be Resilient to Breast Cancer (BRBC) and the prediction model was developed based on a sample of 506 consecutive patients and validated in an internal cohort (N1 = 314) and two external cohorts (N2 = 223 and N3 = 189). Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) were utilized to estimate the incremental value of RI. RI improved prediction above conventional risk factors. AUC increased from 0.745 to 0.862 while IDI and NRI were 8.39% and 18.44% respectively (P < 0.0001 for all). Five predictors were included in the final model: RI, age, N stage, M stage, and baseline QoL. The new model demonstrated good calibration ability in the internal and external cohorts resulting in C-indexes of 0.862 (95%CI, 0.815-0.909), 0.828 (95%CI, 0.745-0.910), 0.880 (95%CI, 0.816-0.944), and 0.869 (95%CI, 0.796-0.941). RI contributed to a more accurate estimation for PTP of 1-year decreased QoL above conventional risk factors and could help optimize decision making of treatment for breast cancer. A promising prognostic indicator of RI could improve QoL-related management in Chinese patients with breast cancer.