Abstract
The purpose of this study is to build a prediction model for accurate assessment of the risk of end-stage kidney disease (ESKD) in individuals with primary focal segmental glomerulosclerosis (FSGS) by integrating clinical and pathological features at biopsy. The prediction model was created based on a retrospective study of 99 patients with biopsy-proven primary FSGS diagnosed at our hospital between December 2012 and December 2019. We assessed discriminative ability and predictive accuracy of the model by C-index and calibration plot. Internal validation of the prediction model was performed with 1000-bootstrap procedure. Eight patients (8.1%) progressed to ESKD before 31 March 2021. Univariate analysis revealed that disease duration before biopsy, hematuria, hemoglobin, eGFR, and percentages of sclerosis and global sclerosis were associated with renal outcome. In multivariate analysis, three predictors were included in final prediction model: eGFR, hematuria, and percentage of sclerosis. The C-index of the model was 0.811 and 5-year calibration plot showed good agreement between predicted renal survival probability and actual observation. A nomogram and an online risk calculator were built on the basis of the prediction model. In conclusion, we constructed and internally validated the first prediction model for risk of ESKD in primary FSGS, which showed good discriminative ability and calibration performance. The prediction model provides an accurate and simple strategy to predict renal prognosis which may help to identify patients at high risk of ESKD and guide the management for patients with primary FSGS in clinical practice.
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Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Funding
This study was supported by the National Natural Science Foundation of China (Nos. 81961138007, 81974096, 81770711, and 81522010), National Key R&D Program of China (2018YFC1314000), and the Program for HUST Academic Frontier Youth Team (2017QYTD20).
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Y.Z. and C.Z. designed the study and collected data; Y.Z. and W.X. analyzed data; Y.Z. and C.Z drafted the manuscript; C.W. and Y.C. revised the manuscript. All authors read and approved the final version of the manuscript.
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The research was approved by the Medical Ethical Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (2015–171) and was performed in accordance with Declaration of Helsinki.
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Written informed consent was obtained from each participant before biopsy.
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Zhu, Y., Xu, W., Wan, C. et al. Prediction model for the risk of ESKD in patients with primary FSGS. Int Urol Nephrol 54, 3211–3219 (2022). https://doi.org/10.1007/s11255-022-03254-w
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DOI: https://doi.org/10.1007/s11255-022-03254-w