Lu Xing1,2, Ruiqi Chen3, Jiahui Qian4, Jianhua Ren5,6, Xue Deng7,8. 1. Department of Gynecological Nursing, West China Second University Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, Sichuan Province, China. 2. Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan Province, China. 3. Department of Neurosurgery, West China Hospital of Sichuan University, Chengdu, Sichuan Province, China. 4. West China School of Public Health, Sichuan University, Chengdu, Sichuan Province, China. 5. Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan Province, China. huaxi_rjh@126.com. 6. Department of Gynecological and Obstetric Nursing, West China Second University Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, Sichuan Province, China. huaxi_rjh@126.com. 7. Department of Gynecological Nursing, West China Second University Hospital, Sichuan University/West China School of Nursing, Sichuan University, Chengdu, Sichuan Province, China. huaxi_dx@126.com. 8. Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan Province, China. huaxi_dx@126.com.
Abstract
BACKGROUND: The study aimed to compare the predictive values of three widely used nutritional assessment methods, body mass index (BMI), Nutritional Risk Screening 2002 (NRS 2002), and the prognostic nutritional index (PNI), for different clinical prognostic indicators of ovarian cancer patients. METHODS: Patients diagnosed with ovarian cancer treated in our hospital between January 2017 and March 2019 were retrospectively included. The three nutritional assessment methods were assessed, and multivariable analysis was conducted to explore predictive factors for clinical prognoses. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUROC) were generated to evaluate the discriminative abilities of the three nutritional assessment tools. RESULTS: A total of 442 patients were recruited. Multivariable analysis revealed that the PNI value predicted 1-year death and 1-year recurrence and that both the NRS 2002 score and the PNI value predicted 30-day readmission (P < 0.05). For PNI, AUROCs were 0.834 for predicting 1-year death and 0.719 for 1-year recurrence prediction; for NRS, the AUROC was 0.820 2002 for predicting 30-day readmission. The optimal cutoff values that maximized the prognostic prediction ability were PNI values of 47.75 g/L and 50.40 g/L for 1-year death and 1-year recurrence, respectively, and an NRS 2002 score of 3 points for 30-day readmission following discharge. CONCLUSION: For ovarian cancer patients, the PNI is better at predicting 1-year death and 30-day readmission after discharge, and the NRS 2002 is superior for predicting 1-year recurrence.
BACKGROUND: The study aimed to compare the predictive values of three widely used nutritional assessment methods, body mass index (BMI), Nutritional Risk Screening 2002 (NRS 2002), and the prognostic nutritional index (PNI), for different clinical prognostic indicators of ovarian cancer patients. METHODS: Patients diagnosed with ovarian cancer treated in our hospital between January 2017 and March 2019 were retrospectively included. The three nutritional assessment methods were assessed, and multivariable analysis was conducted to explore predictive factors for clinical prognoses. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUROC) were generated to evaluate the discriminative abilities of the three nutritional assessment tools. RESULTS: A total of 442 patients were recruited. Multivariable analysis revealed that the PNI value predicted 1-year death and 1-year recurrence and that both the NRS 2002 score and the PNI value predicted 30-day readmission (P < 0.05). For PNI, AUROCs were 0.834 for predicting 1-year death and 0.719 for 1-year recurrence prediction; for NRS, the AUROC was 0.820 2002 for predicting 30-day readmission. The optimal cutoff values that maximized the prognostic prediction ability were PNI values of 47.75 g/L and 50.40 g/L for 1-year death and 1-year recurrence, respectively, and an NRS 2002 score of 3 points for 30-day readmission following discharge. CONCLUSION: For ovarian cancer patients, the PNI is better at predicting 1-year death and 30-day readmission after discharge, and the NRS 2002 is superior for predicting 1-year recurrence.
Authors: Amanika Kumar; Michelle L Torres; William A Cliby; Kimberly R Kalli; Giorgio Bogani; Giovanni Aletti; Caroline C Nitschmann; Francesco Multinu; Amy L Weaver; Matthew S Block; Andrea Mariani Journal: Anticancer Res Date: 2017-07 Impact factor: 2.480