Development and Validation of a Nomogram for Renal Survival Prediction in Patients with Autosomal Dominant Polycystic Kidney Disease

Xiaomei Wang; Rui Zheng; Zhende Liu; Ling Qi; Liang Gu; Xiaoping Wang; Shan Zhu; Mingyue Zhang; Danya Jia; Zhen Su

doi:10.1159/000531329

Development and Validation of a Nomogram for Renal Survival Prediction in Patients with Autosomal Dominant Polycystic Kidney Disease

Kidney Dis (Basel). 2023 Jun 6;9(5):398-407. doi: 10.1159/000531329. eCollection 2023 Oct.

Authors

Xiaomei Wang^{1

2}, Rui Zheng³, Zhende Liu⁴, Ling Qi¹, Liang Gu¹, Xiaoping Wang¹, Shan Zhu¹, Mingyue Zhang⁵, Danya Jia¹, Zhen Su¹

Affiliations

¹ Department of Nephrology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
² Department of Nephrology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
³ Department of Critical Care Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
⁴ Research Center for Intelligent Supercomputing, Zhejiang Laboratory, Hangzhou, China.
⁵ Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Abstract

Introduction: Due to the wide variation in the prognosis of autosomal dominant polycystic kidney disease (ADPKD), prediction of risk of renal survival in ADPKD patients is a tough challenge. We aimed to establish a nomogram for the prediction of renal survival in ADPKD patients.

Methods: We conducted a retrospective observational cohort study in 263 patients with ADPKD. The patients were randomly assigned to a training set (N = 198) and a validation set (N = 65), and demographic and statistical data at baseline were collected. The total kidney volume was measured using stereology. A clinical prediction nomogram was developed based on multivariate Cox regression results. The performance and clinical utility of the nomogram were assessed by calibration curves, the concordance index (C-index), and decision curve analysis (DCA). The nomogram was compared with the height-adjusted total kidney volume (htTKV) model by receiver operating characteristic curve analysis and DCA.

Results: The five independent factors used to construct the nomogram for prognosis prediction were age, htTKV, estimated glomerular filtration rate, hypertension, and hemoglobin. The calibration curve of predicted probabilities against observed renal survival indicated excellent concordance. The model showed very good discrimination with a C-index of 0.91 (0.83-0.99) and an area under the curve of 0.94, which were significantly higher than those of the htTKV model. Similarly, DCA demonstrated that the nomogram had a better net benefit than the htTKV model.

Conclusion: The risk prediction nomogram, incorporating easily assessable clinical parameters, was effective for the prediction of renal survival in ADPKD patients. It can be a useful clinical adjunct for clinicians to evaluate the prognosis of ADPKD patients and provide individualized decision-making.

Keywords: Autosomal dominant polycystic kidney disease; End-stage renal disease; Nomogram; Prediction model; Renal survival.

Grants and funding

This work was supported by grants from the National Natural Science Foundation of China (81671403, 30871179) for Zhen Su, Zhejiang Provincial Health Science and Technology Foundation of China (2021KY203) for Zhen Su, and Special Support Plan for High-level Talents in Wenzhou – Famous Doctors in Wenzhou for Zhen Su.