Mu Zi Liang1, Ying Tang2, M Tish Knobf3, Alex Molassiotis4, Peng Chen5, Guang Yun Hu6, Zhe Sun7, Yuan Liang Yu8, Zeng Jie Ye9. 1. Guangdong Academy of Population Development, Guangzhou, 510600, Guangdong Province, China. 2. Institute of Tumor, Guangzhou University of Chinese Medicine, Guangzhou, 510006, Guangdong Province, China. 3. School of Nursing, Yale University, Orange, CT, 06477, USA. 4. School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR. 5. Basic Medical School, Guizhou University of Traditional Chinese Medicine, Guiyang, 550025, Guizhou Province, China. 6. Army Medical University, Chongqing Municipality, 400038, China. 7. The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510405, Guangdong Province, China. 8. South China University of Technology, Guangzhou, 510641, Guangdong Province, China. 9. Guangzhou University of Chinese Medicine, Guangzhou, 510006, Guangdong Province, China. zengjieye@qq.com.
Abstract
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.
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.
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