Predicting Native Kidney Volume Regression After Transplantation in Autosomal-Dominant Polycystic Kidney Disease

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ID: 333421
2026
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Abstract
Abstract Background Native polycystic kidneys often regress after kidney transplantation in patients with autosomal-dominant polycystic kidney disease (ADPKD), but the degree of regression varies widely, and no externally validated preoperative prediction model is available. Therefore, we aimed to develop and externally validate a preoperative model to predict post-transplant native kidney volume changes. Methods This multicentre, retrospective study included 224 patients with ADPKD who underwent kidney transplantation at 11 Japanese centres. Patients were divided by centre into non-overlapping development (four centres, n = 164) and validation (seven centres, n = 60) sets. Total kidney volume (TKV) was measured before and one year after transplantation. The TKV change ratio (TKVCR) was calculated as post-transplantation TKV divided by baseline TKV. Multivariable linear regression was used to identify preoperative predictors. Results The final model included five preoperative predictors: body mass index, age², log₁₀(TKV), systolic blood pressure, and log₁₀(dialysis duration + 1) (R²=0.168). On external validation, the R² was 0.255, mean absolute error was 0.122, and root mean squared error was 0.154; however, individual-level prediction was limited. In an exploratory binary classification using the overall cohort mean TKVCR (0.62) as the cutoff, accuracy was 0.783, negative predictive value was 0.862, and the area under the receiver operating characteristic curve was 0.850 (95% confidence interval, 0.743–0.947). Conclusions Preoperative factors were associated with post-transplant native kidney volume change, but accuracy for individual patients was limited. These findings provide preliminary evidence that volume changes may be partly predictable.
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Authors Yuki Hasegawa, Takahisa Hiramitsu, Hajime Sasaki, Taiki Ogasa, Shigeaki Nakazawa, Masato Shizuku, Kentaro Ide, Yuji Hidaka, Yu Kijima, Hirotake Kodama, Masayuki Tasaki, Keizo Kaku, Shunji Narumi, Takaaki Kobayashi, Yoshihiko Watarai
Journal clinical kidney journal
Year 2026
DOI
10.1093/ckj/sfag376
URL
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