Table 2.
Summary of observational studies that identified prognostic indicators for ADPKD
| Publication(s) | Objectives | Study details | Methodology for the assessment of disease progression and identification of prognostic indicators | Results and conclusions |
|---|---|---|---|---|
| Schrier, 2003 [40] | To assess the effect of increased research, identification of prognostic factors, and a higher number of anti-hypertensive medications on ADPKD progression | An observational study was conducted over two time periods, 255 patients from 1985 to 1992 (38 % male, age 37.5 ± 10 years, mean renal volume 701 cm3) and 258 patients from 1992 to 2001 (31 % male, age 37.5 ± 10 years, mean renal volume 704.5 cm3) | Regression analyses were performed for all patients to identify factors correlated with progression to ESRD, defined as dialysis or renal transplant | Age (P < 0.0001), renal volume (P < 0.0001), MAP (P = 0.0026) and UPE (P = 0.0051), but not gender, correlated with progression to ESRD |
| CRISP: Grantham, 2006; Torres, 2007, 2010, 2011; Harris, 2006; Irazabal, 2012; Marier, 2013 [15–17, 46, 48, 49, 55] | To identify markers of ADPKD disease progression | A prospective, long-term observational study of 241 ADPKD patients with normal renal function who were considered at high risk of renal insufficiency | Correlations between BL characteristics (including age, gender, BMI, hypertension, MAP, TKV, TCV, RBF, RVR, GFR, serum uric acid, Cho, 24-hour urine volume, UNaE, UAE, and estimated protein intake) and ∆TKV or ∆eGFR were assessed over 3, 6 or 8 years | Factors that predict ∆TKV: |
| • BL TKV (P < 0.001) | ||||
| • BL RBF, UNaE, HDL-c, and age at BL (P ≤ 0.05) | ||||
| • Male gender (P = 0.0163) | ||||
| • UAE (when BL TKV was excluded, P ≤ 0.005) | ||||
| • There was no significant difference in ∆TKV or ∆TCV between patients with PKD1 and PKD2 mutations (P = 0.24 and 0.79, respectively) | ||||
| Factors that predict ∆GFR: | ||||
| • TKV (P < 0.02, 6 years’ follow-up). TKV for patients with BL TKV > 1500 mL (P < 0.001), but not for BL TKV < 750 mL (P = 0.063) or 750–1500 mL (P = 0.57, after 3 years of follow up) | ||||
| • Age (when BL GFR was excluded, P ≤ 0.02) | ||||
| • SCr, BUN (both P ≤ 0.001) | ||||
| • BL GFR, RBF and UNaE (P ≤ 0.02) | ||||
| • UAE, BSA and 24-h urine osmolarity (when BL GFR was excluded, P ≤ 0.02) | ||||
| Kistler, 2009 [92] | To assess the reliability of TKV MRI imaging over 6 months with the aim of using such timescales in studies of potential treatments | A prospective study of 100 young patients with ADPKD (63 % male, mean age 31.2 ± 6.4 years, 97 % had family history of ADPKD) with preserved GFR | Correlations between % change in TKV and clinical and demographical parameters (not specified) were calculated to identify prognostic indicators | Higher ∆TKV were observed in males (P = 0.339) and in patients with albuminuria (P = 0.005) |
| Boertien, 2010, 2012 [93, 94] | To study the correlation between endogenous vasopressin concentration using plasma copeptin as a marker, and renal function | A review of data from a trial investigating the effect of an ACEI on progression of ADPKD (no treatment effect reported). Data were reviewed for 79 patients (43 % male, age 36.8 ± 10.1 years, GFR 96.8 ± 18.2 mL/min/1.73 m2) over a median of 11.2 years | ∆eGFR was used as a measure of renal function | Higher baseline copeptin was associated with a faster ∆eGFR (P < 0.01). This association was independent of age, gender and BL eGFR |
| Azurmendi, 2011 [23] | To investigate albuminuria, measured by urinary Alb/Cr, as a predictor of disease progression | 32 patients with ADPKD (mean age 26 ± 1 years) were observed over 30 ± 1 months | Yearly change in TKV, urinary MCP1 and eGFR were used as measures of renal function | In patients with high urinary Alb/Cr, yearly change in both TKV and urinary MCP1, but not eGFR, were increased compared with patients with normal urinary Alb/Cr (P < 0.05) |
| Griveas, 2012 [58] | To identify patients with ADPKD who progressed and those who did not | A retrospective review of 120 patients (39 % male, age 36.7 ± 12.7 years) was conducted with a median follow-up of 52 months | Correlations were made between annual change in eGFR and the following BL characteristics: | Higher BL eGFR was associated with a faster ∆eGFR (P = 0.04). Correlations between annual ∆eGFR and other BL characteristics were not significant |
| • eGFR | ||||
| • Hb | ||||
| • Cho | ||||
| • Parathormone | ||||
| • SBP and DBP | ||||
| • MAP | ||||
| Kurashige, 2012, 2013 [95, 96] | To investigate genotypic indicators of disease progression in Japanese patients with ADPKD | A mutation search was conducted in the coding and flanking regions of PKD1/2 from 180 patients from 161 unrelated families | Multiple linear regression analyses were conducted to assess the correlations between eGFR decline and gene mutations, plasma arginine vasopressin, and urine osmolarity | • Patients with PDK1 mutations had significantly faster ∆eGFR than patients with PDK2 mutations (P < 0.01) |
| • There was no association between ∆eGFR and mutation type or position | ||||
| • Lower urine osmolarity was found to correlate with ∆eGFR (significance not reported) | ||||
| • Plasma arginine vasopressin was significantly associated with ∆eGFR in patients with PDK1 mutations (P = 0.018) | ||||
| Panizo, 2012 [60] | To analyse factors influencing ADPKD disease progression | A retrospective observational study was conducted in 101 patients with ADPKD (mean age 43 ± 17.3 years, 43.6 % male, median follow-up 69 months, mean kidney size 14.8 ± 2.9 cm, mean eGFR 74.5 ± 32.0 mL/min/1.73 m2) | The following data were collected as potential prognostic markers using eGFR reduction as an indicator of renal function decline: | • SBP, DBP, uric acid, total and LDL-c, Cr, microalbuminuria and kidney size were significantly associated with ∆eGFR (P ≤ 0.05) |
| • Kidney size | • Younger age at diagnosis was also associated with rapid ∆eGFR (P = 0.010) | |||
| • SBP and DBP | ||||
| • Concomitant medications | ||||
| • Hb | ||||
| • Cr | ||||
| • Uric acid | ||||
| • Total Cho, HDL-c and LDL-c | ||||
| • Triglycerides | ||||
| • Calcium | ||||
| • Phosphorus | ||||
| • Parathyroid hormone | ||||
| • Proteinuria (microalbuminuria) | ||||
| • Haematuria | ||||
| CRISP: Warner, 2012 [56] | To assess the association between CPSA and decline in eGFR to determine whether this is a better indicator of ADPKD progression than TKV | Patients were randomly selected from the CRISP cohort: 10 rapid progressors, 10 slow progressors, and 4 atypical cases with large TKV and a small number of cysts at baselinea | • When the atypical cases were excluded from the analysis, BL lnCPSA and lnTKV correlated equally well with ∆eGFR over 6 years (P = 0.0003) | |
| • When atypical cases were included, baseline lnCPSA correlated better than lnTKV with ∆eGFR (P < 0.0001 and P = 0.0008, respectively) | ||||
| Hwang, 2013 [97] | To investigate the association between asymptomatic pyuria and the development of UTIs and the deterioration of renal function | Retrospective case control study of 256 patients with ADPKD (52 % male, mean age 48.1 ± 12.8 years, mean eGFR 91.1 ± 29.2 mL/min/1.73 m2) in South Korea observed over 1 year | ∆GFR was used as a measure of renal function | Patients with chronic asymptomatic pyuria, who were predominantly female (58.5 %) exhibited a significantly faster ∆GFR (P = 0.01) than patients without pyuria or with transient pyuria |
| Lacquaniti, 2013 [98] | To quantify the predictive potential of apelin (marker of vasopressin) and copeptin (antagonist of vasopressin signalling) in ADPKD disease progression | A prospective observational study of 52 patients with ADPKD (60 % male, mean age 43 ± 10 years, mean TKV 1057.3 ± 417.9 mL, mean mGFR 47.7 ± 35.6 mL/min/1.73 m2) and 50 matched healthy control patients (50 % male, mean age 40.3 ± 9.6 years, mean mGFR 116.6 ± 17 mL/min/1.73 m2) were followed for 24 months | Renal function was assessed by combination of ∆mGFR and ∆TKV (>5 % per year) | Concentrations of apelin < 68.5 pg/mL (P = 0.0002) and copeptin > 9.5 pmol/L (P = 0.02) were each associated with a faster decline in renal function |
| Ozkok, 2013 [59] | To investigate the importance of clinical characteristics and biochemical data on disease progression | 323 patients with ADPKD (46 % male, mean age 53 ± 15 years) were followed for a mean of 100 ± 38 months | In Cox regression analysis, the following factors were assessed as potential predictors of ∆GFR: | Age, hypertension, hernia, proteinuria, and urinary stone were significantly associated with faster ∆GFR (P ≤ 0.04) |
| • Age | ||||
| • Gender | ||||
| • BL SCr | ||||
| • Smoking history | ||||
| • History of hypertension | ||||
| • Abdominal wall hernia | ||||
| • Hepatic cyst | ||||
| • Familial history of ADPKD | ||||
| • Macroscopic haematuria | ||||
| • Proteinuria | ||||
| • Urinary stone | ||||
| • Palpable kidney | ||||
| • Use of ACEIs and/or ARBs | ||||
| Spithoven, 2013 [99] | To measure CCr(TS) in patients with ADPKD compared with healthy adults | A case control study of 125 patients with ADPKD (56 % male, mean age 40.4 ± 10.8 years, mean TKV 1470 mL, mean mGFR 77.7 ± 30.1 mL/min/1.73 m2) and 215 healthy controls (48 % male, mean age 53.1 ± 10.3 years, mean eGFR 97.7 ± 17.0 mL/min/1.73 m2) | CCr(TS) was used as a measure of renal function | • CCr(TS) was significantly higher for patients with ADPKD than for controls (P < 0.001), which may be due to cyst formation |
| • In patients with ADPKD, CCr(TS) correlated with BMI (P = 0.003), BL mGFR (P = 0.03) and age (P = 0.07), but was not associated with TKV, female sex, filtration fraction, serum albumin, albuminuria (all P > 0.1) | ||||
| Thong & Ong, 2013 [100] | To analyse the natural history of ADPKD progression | A retrospective study of 210 patients with ADPKD (48.6 % male, mean age 45.6 ± 16.2 years) | Regression analyses were performed to identify risk factors for ∆eGFR for 55 patients who had eGFR and kidney length measurements recorded over 5 years | ∆eGFR was significantly associated with age at diagnosis and with mean kidney length (both P < 0.05). Gender, hypertension, haematuria, proteinuria, UTIs, and liver cysts were not significantly associated with renal function decline |
| Chen, 2014 [14] | To identify parameters that predict cyst growth and decline in renal function | A prospective, longitudinal observational study was performed in 541 Chinese patients with ADPKD and eGFR ≥30 mL/min/1.73 m2 (54 % male, mean age 39.7 ± 12.1 years, eGFR 100.4 ± 20.1 mL/min/1.73 m3) over a median follow-up of 14.3 ± 10.6 months | Analyses were performed for 279 patients with measurements for all variables of the correlation between yearly change in eGFR or yearly % growth in TKV and: | The following parameters correlated with yearly eGFR: |
| • Age | • Age (P = 0.016) | |||
| • Sex | • History of hypertension (P = 0.056) | |||
| • Observation time | • Use of anti-hypertensive drugs (P = 0.102) | |||
| • History of hypertension | • BL eGFR (P = 0.290) | |||
| • Use of anti-hypertensive drugs | • Log10 Pr/Cr (P < 0.001) | |||
| • BP | • Log10 BL TKV (P < 0.001) | |||
| • Macrohaematuria | • BL thrombocyte count (P = 0.031) | |||
| • BL eGFR | ||||
| • Pr/Cr | ||||
| • BL TKV | ||||
| • BL thrombocyte count | The following parameters correlated significantly with yearly TKV: | |||
| • Age (P < 0.001) | ||||
| • Male sex (P = 0.023) | ||||
| • Observation time (P = 0.072) | ||||
| • Use of anti-hypertensive drugs (P = 0.015) | ||||
| • DBP (P = 0.041) | ||||
| • BL eGFR (P = 0.173) | ||||
| • Log10 Pr/Cr (P = 0.050) | ||||
| • Log10 BL TKV (P = 0.092) | ||||
| • BL thrombocyte count (P = 0.042) | ||||
| Higashihara, 2014 [101] | To assess the relationship between TKV and kidney function (measured by eGFR) | An observational study of 64 patients with ADPKD who completed ≥3 measurements and did not have any clinical conditions affecting kidney volume (33 % male, mean age 47.0 ± 14.1 years, mean TKV 1681.1 ± 1001.1 mL, mean eGFR 60.2 ± 27.38 mL/min/1.73 m2) | TKV, GFR, SCr, Cr clearance, UPE, and BP were measured over 5 years | • TKV, height-adjusted TKV, BSA-adjusted TKV and log-TKV significantly correlated with eGFR (all P < 0.0001) |
| • BL TKV, age, and final eGFR were significantly associated with the yearly change in eGFR (P = 0.0349, P < 0.001, P = 0.0011, respectively), but the relationship between BL eGFR and the yearly change in eGFR was not significant (P = 0.4007) | ||||
| • Although there was no significant correlation between age and the TKV parameters investigated (P > 0.1), there was a significant relationship between age and both the yearly % change in TKV and change in log-TKV (P < 0.01) | ||||
| • There was a significant correlation between BL and final TKV and the yearly change in TKV (both P < 0.001) |
ACEI angiotensin-converting enzyme inhibitor, ADPKD autosomal dominant polycystic kidney disease, Alb/Cr albumin/creatinine ratio, ARB angiotensin receptor blocker, BL baseline, BMI body mass index, BP blood pressure, BSA body surface area, BUN blood urea nitrogen, CCr(TS) tubular secretion of creatinine, Cho cholesterol, CPSA cyst parenchyma surface area, Cr creatinine, CRISP consortium for radiologic imaging studies in polycystic kidney disease, DBP diastolic blood pressure, ∆eGFR rate of decline in estimated glomerular filtration rate, ∆TCV rate of increase in total cyst volume, ∆TKV rate of increase in total kidney volume, eGFR estimated glomerular filtration rate, GFR glomerular filtration rate, Hb haemoglobin, HDL-c high density lipoprotein cholesterol, LDL-c low density lipoprotein cholesterol, MAP mean arterial pressure, MCP1 monocyte chemoattractant protein-1, mGFR measured glomerular filtration rate, MRI magnetic resonance imaging, Pr/Cr protein/creatinine ratio, RBF renal blood flow, RVR renal vascular resistance, SBP systolic blood pressure, SCr serum creatinine, TCV total cyst volume, TKV total kidney volume, UAE urine albumin excretion, UNaE urine sodium excretion, UPE urine protein excretion, UTI urinary tract infection
aRapid and slow decline not defined