Integrated Use of Autosomal Dominant Polycystic Kidney Disease Prediction Tools for Risk Prognostication

被引:1
|
作者
Wolff, Constantin A. [1 ]
Aiello, Valeria [2 ]
Elhassan, Elhussein A. E. [3 ,4 ]
Cristalli, Carlotta [5 ]
Lerario, Sarah [2 ]
Paccapelo, Alexandro [6 ]
Ciurli, Francesca [2 ]
Montanari, Francesca [5 ]
Conti, Amalia [5 ]
Benson, Katherine [7 ]
Seri, Marco [5 ]
Brigl, Carolin B. [1 ]
Muenster, Julia S. [1 ]
Sciascia, Nicola [8 ]
Kursch, Sebastian [9 ]
de Fallois, Jonathan [9 ]
La Manna, Gaetano [2 ,10 ]
Eckardt, Kai-Uwe [1 ]
Rank, Nina [1 ]
Popp, Bernt [11 ]
Schoenauer, Ria [1 ]
Conlon, Peter J. [3 ,4 ]
Capelli, Irene [2 ,10 ]
Halbritter, Jan [1 ]
机构
[1] Charite Univ Med Berlin, Dept Nephrol & Med Intens Care, Berlin, Germany
[2] IRCCS Azienda Osped Univ Bologna, Nephrol Dialysis & Kidney Transplant Unit, Bologna, Italy
[3] Beaumont Hosp, Dept Nephrol & Transplantat, Dublin, Ireland
[4] Royal Coll Surgeons Ireland, Dept Med, Dublin, Ireland
[5] IRCCS Azienda Osped Univ Bologna, Med Genet Unit, Bologna, Italy
[6] IRCCS Azienda Osped Univ ia Bologna, Res & Innovat Unit, Bologna, Italy
[7] Royal Coll Surg, Sch Pharm & Biomol Sci, Dublin, Ireland
[8] Univ Bologna, Dept Med & Surg Sci DIMEC, Alma Mater Studiorum, Bologna, Italy
[9] IRCCS Azienda Osped Univ Bologna, Oncohematol & Emergency Radiol Unit, Pediat & Adult CardioThorac & Vasc, Bologna, Italy
[10] Univ Hosp Leipzig, Div Nephrol, Leipzig, Germany
[11] Berlin Inst Hlth, Einstein Ctr Neurosci Berlin, D-10117 Berlin, Germany
来源
CLINICAL JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY | 2025年 / 20卷 / 03期
关键词
ADPKD; CKD; cystic kidney; ESKD; gene expression; kidney volume; polycystic kidney disease; progression of renal failure; cystic kidney disease; genetic diseases and development; VOLUME; PROGRESSION; TOLVAPTAN; ADPKD;
D O I
10.2215/CJN.0000000625
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Background Autosomal dominant polycystic kidney disease is the most common genetic cause of kidney failure. Specific treatment is indicated on observed or predicted rapid progression. For the latter, risk stratification tools have been developed independently based on either total kidney volume or genotyping as well as clinical variables. This study aimed to improve risk prediction by combining both imaging and clinical-genetic scores. Methods We conducted a retrospective multicenter cohort study of 468 patients diagnosed with autosomal dominant polycystic kidney disease. Clinical, imaging, and genetic data were analyzed for risk prediction. We defined rapid disease progression as an eGFR slope >= 3 ml/min per 1.73 m(2) per year over 2 years, Mayo imaging classification (MIC) 1D-1E, or a predicting renal outcome in polycystic kidney disease (PROPKD) score of >= 7 points. Using MIC, PROPKD, and rare exome variant ensemble learner scores, several combined models were designed to develop a new classification with improved risk stratification. Primary endpoints were the development of advanced CKD stages G4-G5, longitudinal changes in eGFR, and clinical variables such as hypertension or urological events. Statistically, logistic regression, survival, receiver operating characteristic analyses, linear mixed models, and Cox proportional hazards models were used. Results PKD1-genotype (P < 0.001), MIC class 1E (P < 0.001), early-onset hypertension (P < 0.001), and early-onset urological events (P = 0.003) correlated best with rapid progression in multivariable analysis. While the MIC showed satisfactory specificity (77%), the PROPKD was more sensitive (59%). Among individuals with an intermediate risk in one of the scores, integration of the other score (combined scoring) allowed for more accurate stratification. Conclusions The combined use of both risk scores was associated with higher ability to identify rapid progressors and resulted in a better stratification, notably among intermediate risk patients.
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收藏
页码:397 / 409
页数:13
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