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常染色体显性多囊肾病中经年龄和身高校正的总肾体积生长率

Age- and height-adjusted total kidney volume growth rate in autosomal dominant polycystic kidney diseases.

作者信息

Higashihara Eiji, Yamamoto Kouji, Kaname Shinya, Okegawa Takatsugu, Tanbo Mitsuhiro, Yamaguchi Tsuyoshi, Shigemori Kaori, Miyazaki Isao, Yokoyama Kenichi, Nutahara Kikuo

机构信息

Department of Hereditary Kidney Disease Research, Kyorin University Faculty of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo, 181-8611, Japan.

Department of Medical Statistics, Graduate School of Medicine, Osaka City University, Osaka, Japan.

出版信息

Clin Exp Nephrol. 2019 Jan;23(1):100-111. doi: 10.1007/s10157-018-1617-8. Epub 2018 Jul 26.

Abstract

BACKGROUND

The Mayo Clinic Image Classification (MIC) was proposed as a renal prognosis prediction model for autosomal dominant polycystic kidney disease (ADPKD). MIC is based on the assumption of exponential constant increase in height-adjusted total kidney volume (HtTKV). HtTKV growth rate is calculated by one-time measurement of HtTKV and age. We named it as an age-adjusted HtTKV growth rate (AHTKV-α). AHTKV-α was compared with HtTKV slope measured by at least two HtTKV values.

METHODS

Comparison of repeatability between AHTKV-α and HtTKV slope, correlation of subgroups divided according to baseline AHTKV-α and HtTKV slope with disease manifestations, estimated glomerular filtration rate (eGFR) slope, and renal survival were analyzed in 296 patients with ADPKD. PKD genotype influences were compared between AHTKV-α and HtTKV slope in 88 patients with characterized PKD mutations.

RESULTS

Absolute differences between baseline and follow-up measures were significantly larger for the HtTKV slope than for AHTKV-α (P < 0.0001). From baseline AHTKV-α-based subgroups A-E according to MIC, disease manifestations occurred earlier and future eGFR slopes became steeper (P < 0.0001). Multivariate hazard ratios of renal survival differed significantly among baseline AHTKV-α-based subgroups. Inter-subgroup differences in these predictors were less evident during baseline HtTKV slope-based classification. AHTKV-α values, but not HtTKV slopes, were significantly higher for PKD1 mutation carriers than for PKD2 mutation carriers (P < 0.0001).

CONCLUSION

MIC is a good renal prediction model applicable to Japanese patients also. AHTKV-α can be a more sensitive and reliable indicator in TKV growth rate than HtTKV slope.

摘要

背景

梅奥诊所影像分类法(MIC)被提出作为常染色体显性多囊肾病(ADPKD)的肾脏预后预测模型。MIC基于身高校正后的总肾体积(HtTKV)呈指数常数增长的假设。HtTKV生长率通过一次性测量HtTKV和年龄来计算。我们将其命名为年龄校正后的HtTKV生长率(AHTKV-α)。将AHTKV-α与通过至少两个HtTKV值测量的HtTKV斜率进行比较。

方法

分析了296例ADPKD患者中AHTKV-α与HtTKV斜率之间的重复性比较、根据基线AHTKV-α和HtTKV斜率划分的亚组与疾病表现、估计肾小球滤过率(eGFR)斜率及肾脏生存率的相关性。比较了88例具有特征性PKD突变患者中AHTKV-α与HtTKV斜率对PKD基因型的影响。

结果

HtTKV斜率的基线与随访测量之间的绝对差异显著大于AHTKV-α(P<0.0001)。根据MIC,从基于基线AHTKV-α的A-E亚组来看,疾病表现出现得更早,未来eGFR斜率变得更陡(P<0.0001)。基于基线AHTKV-α的亚组之间肾脏生存的多变量风险比差异显著。在基于基线HtTKV斜率的分类中,这些预测指标的亚组间差异不太明显。PKD1突变携带者的AHTKV-α值显著高于PKD2突变携带者,而HtTKV斜率则不然(P<0.0001)。

结论

MIC是一个也适用于日本患者的良好肾脏预测模型。在TKV生长率方面,AHTKV-α可能是比HtTKV斜率更敏感、更可靠的指标。

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