Abstract:Autosomal dominant polycystic kidney disease (ADPKD) patients with PKD1 mutations, particularly those with truncating mutations, show poor prognosis. However, the differences in disease progression with different mutation types are unclear. Here, a comparative study was conducted on the renal prognosis of patients with ADPKD who were categorized based on genotype (PKD1 versus PKD2 mutation), mutation type (truncating mutation: nonsense, frameshift, splicing mutation, and large deletion; non-truncating mutation… Show more
“…Japanese patients [47] ( Although several methods for measuring TKV have been developed, two methods using stereology (TKVs) and ellipsoid equation (TKVe) are widely used. TKVs and TKVe were strongly correlated [49].…”
Section: Table 3 Mutation Frequency Between Different Adpkd Cohortmentioning
confidence: 99%
“…Table 3 shows the comparison of mutation frequencies between HOPE-PKD and other large cohorts. Korean ADPKD cohort showed similar proportion of PKD1 PT and PKD1 NT [ 36 , 38 , 39 , 46 , 47 ].…”
Section: Assessment Of the Rapid Progression Of Kidney Diseasementioning
Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease. It is characterized by cyst growth in the kidneys, resulting in kidney enlargement and end-stage kidney disease. The polycystic kidney disease 1 (PKD1) and PKD2 have been identified as genes related to ADPKD and their significance in the molecular pathology of the disease has been studied. A disease-modifying drug has been approved; therefore, it has become important to identify patients at a high risk of kidney disease progression. Genetic tests, image analysis methods, and clinical factors for kidney disease progression prediction have been established. This review describes genetic and clinical characteristics, and discusses ongoing studies in Korean ADPKD patients.
“…Japanese patients [47] ( Although several methods for measuring TKV have been developed, two methods using stereology (TKVs) and ellipsoid equation (TKVe) are widely used. TKVs and TKVe were strongly correlated [49].…”
Section: Table 3 Mutation Frequency Between Different Adpkd Cohortmentioning
confidence: 99%
“…Table 3 shows the comparison of mutation frequencies between HOPE-PKD and other large cohorts. Korean ADPKD cohort showed similar proportion of PKD1 PT and PKD1 NT [ 36 , 38 , 39 , 46 , 47 ].…”
Section: Assessment Of the Rapid Progression Of Kidney Diseasementioning
Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease. It is characterized by cyst growth in the kidneys, resulting in kidney enlargement and end-stage kidney disease. The polycystic kidney disease 1 (PKD1) and PKD2 have been identified as genes related to ADPKD and their significance in the molecular pathology of the disease has been studied. A disease-modifying drug has been approved; therefore, it has become important to identify patients at a high risk of kidney disease progression. Genetic tests, image analysis methods, and clinical factors for kidney disease progression prediction have been established. This review describes genetic and clinical characteristics, and discusses ongoing studies in Korean ADPKD patients.
“…Considering that the treatment of patients in real clinical settings requires multifaceted and comprehensive judgments based on abundant medical information, it is meaningful to examine various cutoff values in various sub-cohorts, at various follow-up periods, especially for important prognostic factors. Indeed, the appropriate cutoff value for a risk factor can depend on the handling of the risk factor [ 43 , 44 , 45 ], the cohort evaluated [ 43 , 44 , 46 , 47 ], and the observation period [ 31 , 32 ].…”
Studies on sex differences in time-series changes in pseudo-R2 values regarding hyperuricemia (HU) in relation to the kidney prognosis among patients with chronic kidney disease (CKD) are scant. The kidney prognosis was evaluated in 200 patients with CKD (median follow-up, 12.3 years). Survival analyses and logistic regression analyses were conducted, generating time-series pseudo-R2 values. We used four definitions of HU according to serum uric acid (SUA) levels (HU6, SUA ≥ 6.0 mg/dL; HU7, SUA ≥ 7.0 mg/dL; HU8, SUA ≥ 8.0 mg/dL) and antihyperuricemic agent use to calculate the mean and percentage of the change in pseudo-R2 values from the 6th year until the end of the study (6Y–End Mean and 6Y–End Change, respectively). The multivariable Cox regression analysis showed that HU7 was significantly associated with kidney outcomes. When stratified by sex, the 6Y–End Mean was clearly higher in women than in men for all HU definitions, with the highest value (0.1755) obtained for HU7 in women. The pseudo-R2 values for HU6 in women showed an increasing pattern, with a 6Y–End Change of 11.4%/year. Thus, it may be clinically meaningful to consider sex differences in the time-series pseudo-R2 values regarding HU and kidney outcomes.
“…Furthermore, considering that multifaceted and comprehensive judgments based on abundant medical information are required in the treatment of patients in real clinical settings, there is merit in evaluating various cut-off values in various sub-cohorts, at various follow-up periods, for prognostic factors of importance. In fact, the adequate cut-off value for a risk factor depends on the handling of the risk factor [38][39][40], the cohort evaluated [38,39,41,42], and the observation period [19,21]. Fat distribution generally differs between the sexes; men have relatively more visceral fat and women have relatively more subcutaneous fat.…”
Whether the visceral-to-subcutaneous fat ratio (V/S ratio) is associated with renal prognosis in patients with chronic kidney disease (CKD) remains unclear. Furthermore, little is known about the effect of sex and the absolute amount of visceral fat accumulation such as visceral fat area (VFA) ≥100 cm2 on the V/S ratio in relation to renal prognosis. In this study, 200 patients with CKD were evaluated for renal prognosis. Survival analyses and logistic regression analyses were conducted, generating time-series pseudo-R2 values. The mean and percent change of the pseudo-R2 values from the 6th year to the 10th year (6Y–10Y Mean and 6Y–10Y Change, respectively) were calculated for determining the cut-off points for the medium-term renal prognosis. Multivariate Cox regression analysis revealed that the V/S ratio was significantly associated with renal outcomes and that the VFA category (VFA ≥ 100 cm2) had significant interactions with the V/S ratio regarding renal prognosis. The hazard ratio (HR) of the V/S ratio was higher in the sub-cohort of VFA < 100 cm2 than in the sub-cohort of VFA ≥ 100 cm2 (HR: 6.42 vs. 1.00). Regarding sex differences, a strong association was noted between the V/S ratio and renal prognosis in women but not in men (HR: 2.40 vs. 1.10). On the other hand, 6Y–10Y Mean of the pseudo-R2 values indicated differences in the cut-off points of the V/S ratio between men and women (V/S ratio: 0.75 vs. 0.5). Our findings indicate that it may be clinically meaningful to consider the differences in sex and the amount of VFA ≥100 cm2 for the V/S ratio in relation to renal outcomes in patients with CKD. The 6Y–10Y Mean of the pseudo-R2 values contributed to determining the cut-off points of the V/S ratio according to the sex difference.
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