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

Background: 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. Methods: 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. Results: 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). Conclusion: 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. Implications for cancer survivors: A promising prognostic indicator of RI could improve QoL-related management in Chinese patients with breast cancer.