The abstract of this article was presented at the 2021 Fall Conference of the Korean Society of Nephrology.
Mayo imaging classification (MIC) is a useful biomarker to predict disease progression in autosomal dominant polycystic kidney disease (ADPKD). This study was performed to validate MIC in the prediction of renal outcome in a prospective Korean ADPKD cohort and evaluate clinical parameters associated with rapid disease progression.
A total of 178 ADPKD patients were enrolled and prospectively observed for an average duration of 6.2 ± 1.9 years. Rapid progressor was defined as MIC 1C through 1E while slow progressor was defined as 1A through 1B. Renal composite outcome (doubling of serum creatinine, 50% decline of estimated glomerular filtration rate [eGFR], or initiation of renal replacement therapy) as well as the annual percent change of height-adjusted total kidney volume (mHTKV-α) and eGFR decline (mGFR-α) were compared between groups.
A total of 110 patients (61.8%) were classified as rapid progressors. These patients were younger and showed a higher proportion of male patients. Rapid progressor was an independent predictor for renal outcome (hazard ratio, 4.09; 95% confidence interval, 1.23–13.54; p = 0.02). The mGFR-α was greater in rapid progressors (–3.58 mL/min per year in 1C, –3.7 in 1D, and –4.52 in 1E) compared with that in slow progressors (–1.54 in 1A and –2.06 in 1B). The mHTKV-α was faster in rapid progressors (5.3% per year in 1C, 9.4% in 1D, and 11.7% in 1E) compared with that in slow progressors (1.2% in 1A and 3.8% in 1B).
MIC is a good predictive tool to define rapid progressors in Korean ADPKD patients.
Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited cystic kidney disease resulting in end-stage kidney disease [
Mayo imaging classification (MIC) is currently the best prediction model for selecting rapid progressors among ADPKD patients. With this prediction model, patients with typical ADPKD can be subclassified into class 1A through 1E according to height-adjusted total kidney volume (htTKV) for age [
This study was performed to evaluate the validity of MIC in defining rapid progressors among Korean ADPKD patients and to describe the clinical characteristics of rapid progressors among Korean ADPKD patients.
Among 364 adult ADPKD patients who were enrolled in the KNOW-CKD (KoreaN Cohort Study for Outcomes in Patients With Chronic Kidney Disease) from 2011 to 2016, a total of 178 typical ADPKD patients with ≥two kidney image studies with more than 1 year apart were included in this analysis. The detailed study design and methods are described in the previous studies [
Abdominal computed tomography (CT) with or without contrast enhancement was performed. All CT exams were performed with 3 to 5 mm thickness, and axial, coronal, and sagittal views were obtained to calculate total kidney volume (TKV). TKV was measured by one professional radiologist using both ellipsoid equation (TKVe) and stereologic method (TKVs) using ImageJ [
In the original MIC, the htTKV growth rate was estimated for classification using the equation [htTKV at age t] = K (1 + α/100)(t–A), where K (theoretical initial htTKV) = 150 and A (theoretical starting age) = 0 [
Baseline characteristics were collected during the enrollment period. Age, sex, presence of hypertension, height, weight, body mass index, and systolic and diastolic blood pressure were collected at the initial visit. Laboratory parameters including plasma hemoglobin, serum uric acid and albumin, serum creatinine, and random urine protein-to-creatinine ratio were assessed at the initial visit. The glomerular filtration rate (GFR) was estimated by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. The estimated GFR (eGFR) was measured annually and htTKV was measured biannually until March 31, 2020.
A total of 162 patients had available genotype data from an inherited cystic kidney disease study [
Primary outcome was renal composite outcome, which consists of doubling of serum creatinine, 50% decline of eGFR, or initiation of renal replacement therapy. Secondary outcomes were annual percent change of htTKVs (mHTKV-α) and annual decline rate of eGFR (mGFR-α). The mGFR-α was measured by a slope-based parameter using a mixed-effects model [
The correlation between TKVe and TKVs was compared using linear regression analysis. Baseline characteristics were compared between rapid progressors and slow progressors using Student t test for continuous variables and chi-square test for categorical variables. Multivariable Cox regression analysis was performed to evaluate rapid progressor as an independent factor for renal composite outcome after adjustment for sex, body mass index, systolic blood pressure, serum uric acid, baseline eGFR, and genotype. To compare mHTKV-α and mGFR-α among different MIC classes or genotypes, the Kruskal-Wallis test was performed. Statistical analyses were performed using SPSS version 20.0 (IBM Corp., Armonk, NY, USA).
TKVe was highly correlated with TKVs (R2 = 0.938) (
We compared eHTKV-α (A = 0 and K = 130) and eHTKV-α (A = 0 and K = 150) in our cohort. We calculated eHTKV-α from the initial and final htTKV measurements and compared the stability between values. When we applied the original equation used in MIC (A = 0 and K = 150) (
When we compared the change in MIC classes from initial to last CT exam, the prediction model using eHTKV-α (A = 0 and K = 130) showed an overall more stationary proportion of classes compared with that using eHTKV-α (A = 0 and K = 150) (
A total of 110 patients (61.8%) were classified as rapid progressors and 68 patients (38.2%) were classified as slow progressors according to eHTKV-α (A = 0 and K = 150) (
A total of 46 renal events occurred during the mean follow-up duration of 6.2 ± 1.9 years. Renal events occurred more frequently among rapid progressors compared with slow progressors defined by original MIC (42 events vs. four events, p < 0.001) (
To validate the clinical utility of MIC among the Korean ADPKD population, we evaluated mHTKV-α and mGFR-α according to MIC classes (
This study evaluated the clinical utility of MIC among Korean ADPKD patients to predict renal outcome. We have confirmed that TKVe and TKVs are strongly correlated. We compared the original equation from MIC (A = 0 and K = 150) and the modified equation from Higashihara’s group (A = 0 and K = 130) and found that the Higashihara equation showed more stable prediction over years. However, Higashihara’s equation did not predict renal outcome according to MIC. Rapid progressor applied by original equation from MIC was an independent predictor for renal outcome together with macroalbuminuria and baseline eGFR. Rapid progressors also demonstrated greater mHTKV-α and mGFR-α compared with slow progressors.
This is the first study to validate the clinical utility of MIC to predict renal outcome in a Korean ADPKD population. Recently, Higashihara’s group suggested to use a theoretical starting htTKV of 130 mL/m instead of 150 mL/L when estimating annual TKV growth [
Our data demonstrated that TKVe strongly correlates with TKVs (R2 = 0.938). A previous study by Irazabal et al. [
Our study showed that MIC classes can change over time in some individuals. Our analysis demonstrated that patients whose MIC classes changed over time were younger than those whose MIC classes were stationary. A previous review by Chebib and Torres [
The risk factors associated with rapid progressors defined by MIC were largely in concordance with the results from previous studies. Our study demonstrated that younger age at enrollment, male sex, higher systolic and diastolic blood pressure, higher body mass index, higher serum uric acid, and lower eGFR were risk factors associated with rapid progressors defined by MIC. A previous study demonstrated that younger age at diagnosis and male sex were the nonmodifiable factors associated with rapid progression [
Rapid progressors defined by MIC (A = 0 and K = 150) also effectively predict renal outcome among the Korean ADPKD population. The mGFR-α declined faster while the mHTKV-α became larger as the MIC classes progressed. However, Korean ADPKD patients showed faster enlargement of the mHTKV-α with a similar mGFR-α according to the MIC classes compared with previous studies with a Caucasian population (
Apart from MIC, genotype neither was an independent factor for renal composite outcome nor significant factors affecting mGFR-α and mHTKV-α. In addition, the proportion of each PKD genotype was not different according to MIC classes. This result may be because of the small number of cases in each subgroup.
Our study has several limitations. First, we did not investigate other risk factors for renal progression including smoking, history of gross hematuria, cholesterol profile, or glucose level. The study population was from a single ethnic group, and therefore the results cannot be generalized. We did not evaluate and compare results from various methods of volumetry. Lastly, the numbers of patients included in each MIC class and genotype were too small.
This is the first study to demonstrate the clinical characteristics and renal outcome among Korean ADPKD patients according to rapid progressor defined by MIC. MIC (A = 0 and K = 150) can be used effectively to define rapid progressors for candidates of Tolvaptan treatment among Korean ADPKD patients.
All authors have no conflicts of interest to declare.
This work was supported by the Research Program funded by the Korea Disease Control and Prevention Agency (2011E3300300, 2012E3301100, 2013E3301600, 2013E3301601, 2013E3301602, 2016E3300200, 2016E3300201, 2016E3300202, 2019E320100, 2019E320101, 2019E320102, 2019-ER-7304-00, 2019-ER-7304-01, 2019-ER-7304-02).
Conceptualization: CA, YKO
Data curation: HCP, HR, YCK, JL, YHK, DWC, WKC
Formal analysis: HCP
Funding acquisition: KHO
Investigation: YH, JHY, HR
Methodology: YH, JHY
Supervision: CA, KHO, YKO
Visualization: JHY
Writing–original draft: HCP, YH, JHY, HR, YCK,
Writing–review & editing: JL, YHK, DWC, WKC, CA, KHO, YKO
All authors read and approved the final manuscript.
We thank all the members of Polycystic Kidney Disease Study Group under the Korean Society of Nephrology for their active participation in the clinical practice and research. We also thank the patient group ‘Da-Nang Sarang’ for their support.
Among 2,238 participants enrolled in the KNOW-CKD (KoreaN Cohort Study for Outcomes in Patients With Chronic Kidney Disease) observational cohort study, a total of 364 patients with ADPKD were identified. Among them, 140 patients without initial htTKV data and 37 patients without follow-up computed tomography exam were excluded from the analysis; in addition, nine patients who received tolvaptan treatment during the observational period were excluded from the analysis. Finally, a total of 178 patients were included in the current study. Among them, 110 patients (61.8%) were classified as rapid progressors and 68 patients (38.2%) were classified as slow progressors according to the original equation of Mayo imaging classification (A = 0 and K = 150).
ADPKD, autosomal dominant polycystic kidney disease; CKD, chronic kidney disease; FU, follow-up; htTKV, height-adjusted total kidney volume.
(A) TKVe and TKVs strongly correlated with each other. (B) Systematic underestimation or overestimation of TKVe was noticed with a mean difference of 5.3%.
SD, standard deviation; TKVe, total kidney volume using ellipsoid methods; TKVs, total kidney volume using stereologic methods.
The eHTKV-α was predicted from htTKV at a certain age. The eHTKV-α at the initial point of TKV measurement and at the final point of TKV measurement was compared in each patient. Using the original equation in MIC (A = 0 and K = 150), the difference between initial and final values was larger than the modified equation from Higashihara’s group (A = 0 and K = 130). (A) Using the original equation (A = 0 and K = 150), 10 of the 178 patients (5.6%) showed more than 1% change in final eHTKV-α from the initial value. (B) Using the modified equation (A = 0 and K = 130), only six out of 178 patients (3.4%) showed more than 1% difference from the initial value. (C, D) We analyzed the associations between eHTKV-α and mHTKV-α, and both equations demonstrated good association between eHTKV-α and mHTKV-α.
eHTKV-α, estimated htTKV slope; htTKV, height-adjusted TKV; mHTKV-α, annual percent change of htTKVs; MIC, Mayo imaging classification; SD, standard deviation; TKV, total kidney volume.
A total of 46 renal events occurred within 6.2 years. No renal event occurred in patients with MIC 1A. Four events (7.8%) occurred in 1B, 21 events (33.9%) in 1C, 15 events (42.9%) in 1D, and six events (46.2%) in 1E. Rapid progressors defined by original MIC predicted more frequent renal events compared to slow progressors (p < 0.001).
MIC, Mayo imaging classification.
Clinical parameters associated with Korean ADPKD rapid progressors
Variable | Total (n = 178) | Slow progressors (n = 68) | Rapid progressors (n = 110) | p-value |
---|---|---|---|---|
Age (yr) | 46.9 ± 10.6 | 49.0 ± 11.2 | 45.7 ± 10.0 | 0.04 |
Male sex | 90 (50.6) | 24 (35.3) | 66 (60.0) | 0.001 |
Hypertension | 157 (88.2) | 58 (85.3) | 99 (90.0) | 0.34 |
htTKV (mL/m) | 784.9 (430.1–1,177.7) | 398.1 (276.5–537.1) | 1,030.9 (819.2–1,390.7) | <0.001 |
PKD1 genotype | 116 (82.3) | 37 (80.4) | 79 (83.2) | 0.69 |
Body mass index (kg/m2) | 23.5 ± 2.97 | 22.5 ± 2.57 | 24.0 ± 3.1 | 0.001 |
Systolic BP (mmHg) | 127.7 ± 12.3 | 124.7 ± 11.8 | 129.5 ± 12.4 | 0.01 |
Diastolic BP (mmHg) | 81.1 ± 10.0 | 79.0 ± 9.8 | 82.4 ± 10.0 | 0.03 |
Hemoglobin (g/dL) | 13.5 ± 1.56 | 13.5 ± 1.36 | 13.6 ± 1.66 | 0.83 |
Uric acid (mg/dL) | 5.8 ± 1.42 | 5.4 ± 1.34 | 6.0 ± 1.44 | 0.007 |
Albumin (g/dL) | 4.44 ± 0.25 | 4.47 ± 0.27 | 4.42 ± 0.24 | 0.25 |
Creatinine (mg/dL) | 1.1 ± 0.43 | 0.94 ± 0.38 | 1.2 ± 0.43 | <0.001 |
eGFR (mL/min/1.73 m2) | 78.3 ± 27.4 | 86.4 ± 25.3 | 73.3 ± 27.6 | 0.002 |
Urinary protein-to-creatinine ratio (g/g) | 0.08 (0.05–0.15) | 0.06 (0.04–0.12) | 0.1 (0.05–0.21) | 0.06 |
Data are expressed as mean ± standard deviation, number (%), or median (interquartile range).
ADPKD, autosomal dominant polycystic kidney disease; BP, blood pressure; eGFR, estimated glomerular filtration rate; htTKV, height-adjusted total kidney volume.
Rapid progressor was defined as 1C to 1E by the original equation of the Mayo imaging classification (A = 0 and K = 150).
Multivariable Cox regression analysis for renal outcome in patients with ADPKD
Variable | HR (95% CI) | p-value |
---|---|---|
Age (yr) | 0.97 (0.93–1.02) | 0.12 |
Male sex (vs. female sex) | 0.78 (0.39–1.55) | 0.47 |
Body mass index (kg/m2) | 0.95 (0.82–1.09) | 0.44 |
Systolic BP (mmHg) | 1.00 (0.97–1.03) | 0.98 |
Serum uric acid (mg/dL) | 1.12 (0.84–1.45) | 0.43 |
Baseline eGFR (mL/min/1.73 m2) | 0.94 (0.92–0.96) | <0.001 |
Macroalbuminuria (vs. normoalbuminuria or microalbuminuria) | 3.53 (1.66–7.49) | 0.001 |
PKD1 genotype (vs. PKD2) | 2.45 (0.71–8.44) | 0.16 |
Rapid progressor |
4.09 (1.23–13.54) | 0.02 |
ADPKD, autosomal dominant polycystic kidney disease; BP, blood pressure; CI, confidence interval; eGFR, estimated glomerular filtration rate; HR, hazard ratio.
Rapid progressor was defined as 1C to 1E by the original equation of the Mayo imaging classification (A = 0 and K = 150).
mHTKV-α and mGFR-α according to MIC (A = 0 and K = 150) in the Korean ADPKD cohort
Mayo class | 1A (n = 17) | 1B (n = 51) | 1C (n = 62) | 1D (n = 35) | 1E (n = 13) | p-value |
---|---|---|---|---|---|---|
mHTKV-α | 1.22 (–0.3 to 2.73) | 3.83 (2.62–5.05) | 5.26 (4.16–6.36) | 9.39 (5.3–13.49) | 11.72 (6.84–16.59) | <0.001 |
mGFR-α | –1.54 (–2.3 to –0.77) | –2.06 (–2.48 to –1.64) | –3.58 (–4.05 to –3.11) | –3.7 (–4.31 to –3.09) | –4.52 (–6.2 to –2.83) | <0.001 |
Data are expressed as mean (95% confidence interval).
ADPKD, autosomal dominant polycystic kidney disease; MIC, Mayo imaging classification; mGFR-α, annual decline rate of glomerular filtrate rate; mHTKV-α, annual change to height-adjusted total kidney volume.