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Abstract
Abstract Title
Prediction model for postoperative acute kidney injury and chronic kidney disease in patients with renal cell carcinoma and venous tumor thrombus
Presentation Type
Podium Abstract
Manuscript Type
Clinical Research
Abstract Category *
Oncology: Kidney (non-UTUC)
Author's Information
Number of Authors (including submitting/presenting author) *
2
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Country
China
Co-author 1
Qilong Jiao nkjiaoqilong@163.com Nankai University School of Medicine Tianjin China *
Co-author 2
Xu Zhang xzhang301@163.com The Third Medical Center, Chinese PLA General Hospital Department of Urology Beijing China - Nankai University School of Medicine Tianjin China
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Abstract Content
Introduction
To develop nomograms to predict the risk of postoperative acute kidney injury (PO-AKI) and chronic kidney disease (CKD) in patients with renal cell carcinoma and venous tumor thrombus (RCC-VTT).
Materials and Methods
A total of 353 consecutive postoperative patients with RCC-VTT were enrolled between Jan 2006 and June 2023. Clinicopathological, operative data and functional outcomes were collected and analyzed. Logistic regression was employed to develop predictive models incorporating risk factors. Model performance was assessed using the area under the curve (AUC), calibration, and decision curve analysis.
Results
Among the 353 patients, the incidence of PO-AKI was 61.5%, with stage 2-3 PO-AKI observed in 15.0% overall and in 4.0% of cases with RCC and renal venous tumor thrombus, as well as 21.1% of RCC with inferior vena cava (IVC) tumor thrombus. Independent risk factors for PO-AKI included age >60 years, male sex, contralateral renal artery and IVC clamping time >20 minutes, BMI and preoperative eGFR. Tumor size was identified as the only independent protective factor against PO-AKI. Of 297 patients, 83 (27.9%) developed CKD, with BMI >24 kg/m2, age >60 years, hypertension, IVC cavectomy, PO-AKI, and adjuvant therapy identified as independent risk factors, preoperative eGFR emerged as the only independent protective factor. The AUCs for PO-AKI and CKD predictive models were 0.776 (95% CI, 0.728-0.824) and 0.863 (95% CI, 0.817-0.908), respectively, demonstrating good calibration and predictive accuracy.
Conclusions
The developed nomograms effectively predict PO-AKI and CKD risk in RCC-VTT patients, aiding in clinical decision-making and optimizing patient management to improve functional outcomes.
Keywords
Renal tumor; tumor thrombus; prediction model; acute kidney injury; chronic kidney disease; congestive kidney injury
Figure 1
https://storage.unitedwebnetwork.com/files/1237/62dcb63cea465917dbcb729157f2ecc8.tif
Figure 1 Caption
Nomogram and ROC curves for prediction PO-AKI and CKD
Figure 2
https://storage.unitedwebnetwork.com/files/1237/3d722d1d44fe947ec970abff7a8becc6.tif
Figure 2 Caption
Validation of nomogram
Figure 3
https://storage.unitedwebnetwork.com/files/1237/abd6095c91e255b7c3c21a0185fc62fe.tif
Figure 3 Caption
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Character Count
1501
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