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Xiao-Ying Hu,1– 5 Dong-Wei Liu,1– 5 Ying-Jin Qiao,1– 5 Xuan Zheng,6 Jia-Yu Duan,1– 5 Shao-Kang Pan,1– 5 Zhang-Sou Liu1– 5 1Department of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, People’s Republic of China; 2Research Institute of Nephrology, Zhengzhou University, Zhengzhou 450052, People’s Republic of China; 3Research Center for Kidney Disease, Zhengzhou 450052, Henan Province, People’s Republic of China; 4Key Laboratory of Precision Diagnosis and Treatment for Chronic Kidney Disease in Henan Province, Zhengzhou 450052, People’s Republic of China; 5Core Unit of National Clinical Medical Research Center of Kidney Disease, Zhengzhou 450052, People’s Republic of China; 6Department of Radiation Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing, 100021, People’s Republic of ChinaCorrespondence: Zhang-Sou LiuDepartment of Nephrology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, People’s Republic of ChinaTel +86-0371-66295921Fax +86-0371-66970906Email zhangsuoliu@zzu.edu.cnPurpose: To develop and validate a nomogram model to predict the occurrence of acute kidney disease (AKD) after nephrectomy.Patients and Methods: A retrospective cohort including 378 patients with renal cell carcinoma (RCC) who had undergone radical or partial nephrectomy between March 2013 and December 2017 at the First Affiliated Hospital of Zhengzhou University was analyzed. Of these, patients who had undergone surgery in an earlier period of time formed the training cohort (n=265) for nomogram development, and those who had undergone surgery thereafter formed the validation cohort (n=113) to confirm the model’s performance. The incidence rate of AKD was measured. Univariate and multivariate logistics regression analysis was used to estimate the independent risk factors associated with AKD. The independent risk factors were incorporated into the nomogram. The accuracy and utility of the nomogram were evaluated by calibration curve and decision curve analysis, respectively.Results: Overall, AKD occurred in 27.5% and 28.3% of patients in the training and validation cohorts, separately. The final nomogram included surgery approach, Charlson comorbidity index (CCI), and the decrement of eGFR. This model achieved good concordance indexes of 0.78 (95% CI=0.71– 0.84) and 0.76 (95% CI=0.67– 0.86) in the training and validation cohorts, respectively. The calibration curves and decision curve analysis (DCA) demonstrated the accuracy and the clinical usefulness of the proposed nomogram, separately.Conclusion: The nomogram accurately predicts AKD after nephrectomy in patients with RCC. The risk for patients’ progress into AKD can be determined, which is useful in guiding clinical decisions.Keywords: kidney cancer, renal cell carcinoma, nephrectomy, acute kidney disease, nomogram

Hu XY, Liu DW, Qiao YJ, et al. Cancer Manag Res. 2020;12:11783‒11791. On page 11783, the last author and the correspondence author’s name should read from Zhang-Sou Liu to Zhang-Suo Liu. This error was introduced by the Editorial staff during the publication process. Read the original article