Development of BK polyomavirus-associated nephropathy risk prediction in kidney transplant recipients
Background With the development of potential prevention therapies for BK polyomavirus (BKPyV)-associated nephropathy (BKPyVAN), risk prediction models are needed to identify kidney transplant recipients at high risk for BKPyVAN.Methods This single-center retrospective study aimed to develop a risk p...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Renal Failure |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/0886022X.2025.2509785 |
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| Summary: | Background With the development of potential prevention therapies for BK polyomavirus (BKPyV)-associated nephropathy (BKPyVAN), risk prediction models are needed to identify kidney transplant recipients at high risk for BKPyVAN.Methods This single-center retrospective study aimed to develop a risk prediction model and an integer-based risk score for BKPyVAN development, defined as plasma BKPyV-DNA >10,000 copies/mL and/or biopsy-proven BKPyVAN, within 1-year post-transplant, using donor and recipient characteristics at the time of transplantation. We randomly split patients into development and validation cohorts and applied logistic regression with backward selection to identify significant variables. Model performance was evaluated using the area under the receiver-operating characteristic curve (AUC) and calibration plots.Results This study included 560 patients, of whom 75 (13%) patients had BKPyVAN. Age >50 years, male sex, and prior kidney transplant were selected for the final model. The total integer score ranged from 0 to 4 points, with 1 point assigned for age >50 years and male sex, and 2 points for prior kidney transplant. The AUC was 0.65 in both development and validation cohorts. Calibration plots showed an incremental increase in risk with higher total scores. The integer score indicated that patients with a total score of 2 or higher (i.e. males aged >50 years or those with prior kidney transplants) have a predicted risk of 20% or greater.Conclusion Although the AUC was suboptimal, the results suggest that our model may still be valuable for identifying high-risk patients. |
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| ISSN: | 0886-022X 1525-6049 |