Expanded Imaging Classification of Autosomal Dominant Polycystic Kidney Disease

被引:23
作者
Bae, Kyongtae T. [1 ]
Shi, Tiange [2 ]
Tao, Cheng [1 ]
Yu, Alan S. L. [3 ,4 ]
Torres, Vicente E. [5 ]
Perrone, Ronald D. [6 ]
Chapman, Arlene B. [7 ]
Brosnahan, Godela [8 ]
Steinman, Theodore I. [9 ]
Braun, William E. [10 ]
Srivastava, Avantika [2 ]
Irazabal, Maria V. [5 ]
Abebe, Kaleab Z. [11 ]
Harris, Peter C. [5 ]
Landsittel, Douglas P. [2 ]
机构
[1] Univ Pittsburgh, Sch Med, Dept Radiol, 3362 Fifth Ave, Pittsburgh, PA 15213 USA
[2] Univ Pittsburgh, Sch Med, Dept Biomed Informat, Pittsburgh, PA USA
[3] Univ Kansas, Med Ctr, Dept Internal Med, Div Nephrol & Hypertens, Kansas City, KS 66103 USA
[4] Univ Kansas, Med Ctr, Jared Grantham Kidney Inst, Kansas City, KS 66103 USA
[5] Mayo Clin, Coll Med, Div Nephrol & Hypertens, Rochester, MN USA
[6] Tufts Univ, Med Ctr, Div Nephrol, Boston, MA 02111 USA
[7] Univ Chicago, Sch Med, Sect Nephrol, Chicago, IL 60637 USA
[8] Univ Colorado, Div Renal Dis & Hypertens, Anschutz Med Campus, Aurora, CO USA
[9] Beth Israel Deaconess Med Ctr, Renal Div, Boston, MA 02215 USA
[10] Cleveland Clin, Dept Nephrol & Hypertens, Cleveland, OH 44106 USA
[11] Univ Pittsburgh, Sch Med, Dept Med, Pittsburgh, PA 15213 USA
来源
JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY | 2020年 / 31卷 / 07期
关键词
ADPKD; clinical trial; kidney volume; risk factors; VOLUME; PROGRESSION; TRIALS; DESIGN;
D O I
10.1681/ASN.2019101121
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
Significance Statement Accurate prediction of risk for disease progression is crucial for clinical management of autosomal dominant polycystic kidney disease (ADPKD). The Mayo imaging classification of ADPKD uses height-adjusted total kidney volume (htTKV) and age to identify patients at highest risk. Because the current Mayo classification applies only to patients with typical diffuse cystic disease (class 1) and poorly predicts eGFR decline for the remaining 5%?10% of patients with atypical morphology (class 2), imaging-based risk modeling remains unresolved. The authors report an expanded imaging classification model in which use of a recalculated htTKV value that excludes prominent exophytic cysts improved prediction for eGFR trajectory. Using a recalculated htTKV may allow inclusion of class 2 patients in the Mayo classification of ADPKD and reclassification of class 1 patients with prominent exophytic cysts. Background The Mayo Clinic imaging classification of autosomal dominant polycystic kidney disease (ADPKD) uses height-adjusted total kidney volume (htTKV) and age to identify patients at highest risk for disease progression. However, this classification applies only to patients with typical diffuse cystic disease (class 1). Because htTKV poorly predicts eGFR decline for the 5%?10% of patients with atypical morphology (class 2), imaging-based risk modeling remains unresolved. Methods Of 558 adults with ADPKD in the HALT-A study, we identified 25 patients of class 2A with prominent exophytic cysts (class 2Ae) and 43 patients of class 1 with prominent exophytic cysts; we recalculated their htTKVs to exclude exophytic cysts. Using original and recalculated htTKVs in association with imaging classification in logistic and mixed linear models, we compared predictions for developing CKD stage 3 and for eGFR trajectory. Results Using recalculated htTKVs increased specificity for developing CKD stage 3 in all participants from 82.6% to 84.2% after adjustment for baseline age, eGFR, BMI, sex, and race. The predicted proportion of class 2Ae patients developing CKD stage 3 using a cutoff of 0.5 for predicting case status was better calibrated to the observed value of 13.0% with recalculated htTKVs (45.5%) versus original htTKVs (63.6%). Using recalculated htTKVs reduced the mean paired difference between predicted and observed eGFR from 17.6 (using original htTKVs) to 4.0 ml/min per 1.73 m(2) for class 2Ae, and from ?1.7 (using original htTKVs) to 0.1 ml/min per 1.73 m(2) for class 1. Conclusions Use of a recalculated htTKV measure that excludes prominent exophytic cysts facilitates inclusion of class 2 patients and reclassification of class 1 patients in the Mayo classification model.
引用
收藏
页码:1640 / 1651
页数:12
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