Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
J Am Soc Nephrol. 2020 Jul;31(7):1640-1651. doi: 10.1681/ASN.2019101121. Epub 2020 Jun 2.
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.
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.
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 for class 2Ae, and from -1.7 (using original htTKVs) to 0.1 ml/min per 1.73 m for class 1.
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.
梅奥诊所的常染色体显性遗传性多囊肾病(ADPKD)影像学分类使用身高调整的总肾体积(htTKV)和年龄来识别疾病进展风险最高的患者。然而,这种分类仅适用于具有典型弥漫性囊性病变(第 1 类)的患者。由于 htTKV 对 5%-10%具有非典型形态的患者(第 2 类)的 eGFR 下降预测不佳,因此影像学风险建模仍然没有解决。
在 HALT-A 研究的 558 名 ADPKD 成年患者中,我们确定了 25 名具有明显外生囊肿(第 2Ae 类)的 2A 类患者和 43 名具有明显外生囊肿的 1 类患者;我们重新计算了他们的 htTKV 以排除外生囊肿。使用原始和重新计算的 htTKV 与逻辑和混合线性模型中的影像学分类相结合,我们比较了发展为 CKD 第 3 期和 eGFR 轨迹的预测。
使用重新计算的 htTKV,在调整基线年龄、eGFR、BMI、性别和种族后,所有参与者发展为 CKD 第 3 期的特异性从 82.6%提高到 84.2%。使用重新计算的 htTKV 预测 2Ae 类患者发生 CKD 第 3 期的比例,使用预测病例状态的截止值为 0.5,与观察到的 13.0%更吻合(45.5%),而不是原始 htTKV(63.6%)。使用重新计算的 htTKV 减少了 2Ae 类患者的预测和观察到的 eGFR 之间的平均配对差异,从使用原始 htTKV 时的 17.6ml/min/1.73m 减少到 4.0ml/min/1.73m,从使用原始 htTKV 时的-1.7ml/min/1.73m 减少到 0.1ml/min/1.73m。
使用排除明显外生囊肿的重新计算的 htTKV 测量值有助于将 2 类患者纳入梅奥分类模型,并重新分类 1 类患者。