Clinical Kidney Journal, 2022, vol. 15, no. 5, 912–921 https:/doi.org/10.1093/ckj/sfab293 Advance Access Publication Date: 28 December 2021 Original Article Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 O R I G I NA L A RT I C L E Comparative analysis of tools to predict rapid progression in autosomal dominant polycystic kidney disease Javier Naranjo 1,2,∗ , Mónica Furlano 2,∗ , Ferran Torres3,4 , Jonathan Hernandez5 , Marc Pybus6 , Laia Ejarque6 , Christian Cordoba7 , Lluis Guirado7 , Elisabet Ars6 and Roser Torra 2 1 Nephrology Department, Hospital Universitario Puerta del Mar, Cádiz, Spain, 2 Inherited Kidney Diseases, Nephrology Department, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB-Sant Pau), Medicine Department, Universitat Autónoma de Barcelona, REDinREN, Barcelona, Spain, 3 Biostatistics Unit, Faculty of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain, 4 Medical Statistics Core Facility, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clinic, Barcelona, Spain, 5 Radiology Department, Fundació Puigvert, Barcelona, Spain, 6 Molecular Biology Laboratory, Fundació Puigvert, Instituto de Investigaciones Biomédicas Sant Pau (IIB Sant Pau), Universitat Autónoma de Barcelona, REDinREN, Barcelona, Spain and 7 Nephrology Department, Fundació Puigvert, REDinREN, IIB Sant Pau, Universitat Autónoma de Barcelona, Barcelona, Spain ∗ These authors equally contributed to this work. Correspondence to: Roser Torra; E-mail: rtorra@fundacio-puigvert.es ABSTRACT Background. Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic kidney disease and shows a wide phenotype. Only patients with rapid progression (RP) are included in clinical trials or are approved to receive disease-modifying drugs. This study aims at comparing different available predictive tools in ADPKD with the Mayo classification (MC) identification of rapid progressors based on high total kidney volume (TKV) according to age. Methods. A total of 164 ADPKD patients were recruited retrospectively from a single centre. The performance of diverse tools to identify RP defined as being in MC categories 1C–1E was assessed. Results. A total of 118 patients were MC 1C–1E. The algorithm developed by the European Renal Association–European Dialysis and Transplant Association Working Group on Inherited Kidney Disorders/European Renal Best Practice had a low sensitivity in identifying MC 1C–1E. The sensitivity and specificity of TKV to predict RP depend on the cut-off used. A kidney length of >16.5 cm before age 45 years has high specificity but low sensitivity. Assessing the MC by ultrasonography had high levels of agreement with magnetic resonance imaging (MRI) data, especially for 1A, 1D and 1E. The estimated glomerular filtration rate (eGFR) decline was very sensitive but had low specificity. In contrast, the Predicting Renal Outcome in Polycystic Kidney Disease (PROPKD) score was very specific but had poor sensitivity. Having hypertension before 35 years of age is a good clinical predictor of MC 1C–1E. Family history can be of help in suggesting RP, but by itself it lacks sufficient sensitivity and specificity. Received: 11.8.2021; Editorial decision: 6.12.2021 © The Author(s) 2021. Published by Oxford University Press on behalf of the ERA. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com 912 Comparative analysis of tools in ADPKD 913 Conclusions. The MC by ultrasonography could be an option in hospitals with limited access to MRI as it performs well generally, and especially at the extremes of the MC, i.e. classes 1A, 1D and 1E. The eGFR decline is sensitive but not very specific when compared with the MC, whereas the PROPKD score is very specific but has low sensitivity. Integrating the different tools currently available to determine RP should facilitate the identification of rapid progressors among patients with ADPKD. GRAPHICAL ABSTRACT Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 Keywords: ADPKD, Mayo classification, prediction, PROPKD, rapid progression, total kidney volume INTRODUCTION this publication, more evidence has been provided on the effi- cacy of tolvaptan in other subpopulations and also concerning Autosomal dominant polycystic kidney disease (ADPKD) is the prediction tools for RP assessment in ADPKD [14–17], so this al- most common hereditary kidney disorder. It is characterized gorithm is now outdated (https://www.era-online.org/en/erbp/ by fluid-filled cyst development from birth and causes progres- blog/category/guidance/). To date, the single most accepted pre- sive and irreversible deterioration of kidney function, leading diction tool is the Mayo classification (MC) [18]. In this study, MC to kidney failure [1–3]. ADPKD is genetically heterogeneous and categories 1C–1E were used as the gold standard to define RP is caused by pathogenic variants in PKD1 (78%), PKD2 (15%), for purposes of comparison. We aimed at evaluating the perfor- GANAB (0.3%) and DNAJB11 (0.1%) [4–6]. The natural course of mance of different tools to predict RP (MC categories 1C–1E) in ADPKD varies significantly, both within and between families patients with ADPKD. [7]. Identifying patients at high risk for rapid progression (RP) to needing kidney replacement therapy (KRT) has become increas- ingly important given the emergence of potential new treat- ments [8, 9]. For example, tolvaptan has been approved only for MATERIALS AND METHODS patients with ADPKD and RP [10]. Currently, multiple potential A total of 178 patients aged 18–72 years with a diagnosis of tools are available to predict disease progression in ADPKD [11]. ADPKD (according to the criteria proposed by Pei et al. [19]), fol- Unfortunately, there is no consensus on the optimal prediction lowed at an outpatient clinic for inherited kidney diseases, were model for the identification of RP [12]. In 2016, the European Re- studied for RP. All of them underwent magnetic resonance imag- nal Association–European Dialysis and Transplant Association ing (MRI) between January 2015 and December 2019. Fourteen Working Group on Inherited Kidney Disorders/European Renal presented atypical imaging on the MRI and were excluded [20]. Best Practice (ERA WGIKD/ERBP) developed an algorithm to iden- The study was conducted in accordance with the declaration tify patients with RP and an indication for treatment [13]. Since of Helsinki and the International Council for Harmonization 914 J. Naranjo et al. ERA WGIKD/ERBP algorithm ERA WGIKD/ERBP with less restrictive age algorithm and eGFR n = 164 n = 164 TKV > 750 mL eGFR decline ≥ 5 mL/min/1.73 m2 n = 164 Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 in at least one year n = 109 TKV > 1500 mL Algorithm n = 164 eGFR decline ≥ 2.5 mL/min/1.73 m2/year (≥ 5 years) > 16.5 cm and n = 92 < 45 years by MRI n = 131 Image Mayo Classification Laboratory n = 164 eGFR decline ≥ 3 mL/min/1.73 m2/year (≥ 5 years) > 16.5 cm and n = 92 < 45 years by US n = 126 Others Based on eGFR and age: 35–45 yr and eGFR 30–90 mL/min/1.73 m2 Mayo Classification 46–55 yr and eGFR 15–60 mL/min/1.73 m2 by US n = 164 n = 109 Family history Family history PROPKD (≥ 1 family member) (≥ 2 family members) n = 162 n = 117 n = 117 FIGURE 1: Different prediction tools used for the assessment of rapid kidney disease progression in ADPKD. European Renal Association Working Group on Inherited Kidney Disorders/European Renal Best Practice. guidelines and was approved by the Fundació Puigvert institu- Kidney length >16.5 cm at age <45 years tional review board. All patients gave signed informed consent. Kidney length was measured by US and MRI from longitudinal Data at the time of MRI study were collected by reviewing images obtained in a sagittal plane. Patients with a kidney length medical records and included age, height, sex, historical esti- of >16.5 cm and aged >45 years were excluded because the age mated glomerular filtration rate (eGFR using the Chronic Kidney at which their kidneys had reached this diameter was unknown. Disease Epidemiology Collaboration formula [21]), family history, Patients with a kidney length of <16.5 cm and aged >45 years left and right kidney lengths as measured by ultrasound (US) and were considered as not having RP. Patients with a kidney length by MRI, total kidney volume (TKV) as measured by MRI and by US, of <16.5 cm and aged <45 years were considered as not having genotype, age at the onset of hypertension and urological events. RP at the time of the study while recognizing that they might Radiologists with extensive experience in kidney imaging per- meet the criterion in the future. Patients with a kidney length of formed US and assessed MRI. TKV, together with age and height, >16.5 cm and aged <45 years were considered to have RP [24]. was introduced into the Mayo ADPKD calculator and patients were classified accordingly [22]. Patients with MC 1C, 1D or 1E were considered to have RP [20]. The following prediction mod- els for determining RP in ADPKD were also assessed (Figure 1) Mayo classification by ultrasound and compared with the MC. The MC was assessed by MRI and, as an exploratory experiment, was also calculated using height-adjusted total kidney volume ERA WGIKD/ERBP algorithm (htTKV) as measured by US. The ERA WGIKD/ERBP algorithm [13] was assessed in all patients and was considered as one of the prediction models for RP. A modification of the algorithm incorporating less restrictive age Kidney function decline and an eGFR criteria based on more recent findings [9] was also Historical eGFR decline was calculated retrospectively based analysed. It included patients 18–35 years old with an eGFR of on clinical records from 2011 to 2019. Patients with two ≥30 mL/min/1.73 m2 , those aged 35–45 years with an eGFR of or fewer blood tests were excluded from eGFR decline pre- ≥30 to <90 mL/min/1.73 m2 and those aged 45–55 years with an diction models. Patients with chronic kidney disease (CKD) eGFR of ≥15 to <60 mL/min/1.73 m2 . group 1 were also excluded due to the unreliability of eGFR changes at this stage [13]. An eGFR decline of ≥5 mL/min/ Total kidney volume 1.73 m2 in 1 year, as suggested by the KDIGO Guideline [13, 25], and an eGFR decline of ≥2.5 mL/min/1.73 m2 /year over 5 years The ellipsoid formula was used to calculate TKV. TKV [20] were considered as thresholds for RP. An eGFR decline of >750 mL and TKV >1500 mL were considered as different ≥3 mL/min/1.73 m2 /year over 5 years was also analysed to see thresholds to determine RP [8, 23]. whether it was more accurate in identifying patients with RP. Comparative analysis of tools in ADPKD 915 Table 1. Baseline characteristics of patients with ADPKD Characteristics All patients, n = 164 MC 1A–1B, n = 46 MC 1C–1E, n = 118 P-value* Female, n (%) 84 (51.2) 31 (67.4) 53 (44.9) 0.01 Age (years) 40.5 ± 11.4 38.7 ± 12.7 41.2 ± 10.8 0.16 eGFR (mL/min/1.73 m2 ) 88.6 ± 27.8 92.2 ± 24.4 87.2 ± 29.0 0.39 CKD, n (%) 0.04 G1 (eGFR >90 mL/min/1.73 m2 ) 48 (29.3) 20 (43.5) 28 (23.7) G2 (eGFR 60–90 mL/min/1.73 m2 ) 54 (32.8) 19 (41.3) 35 (29.7) Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 G3a (eGFR 45–60 mL/min/1.73 m2 ) 26 (15.9) 1 (2.2) 25 (21.2) G3b (eGFR 30–45 mL/min/1.73 m2 ) 10 (6.1) 1 (2.2) 9 (7.6) G4 (eGFR 15–30 mL/min/1.73 m2 ) 21 (12.8) 5 (10.9) 16 (13.6) G5 (eGFR <15 mL/min/1.73 m2 ) 5 (3.0) 0 (0.0) 5 (4.2) TKV measured by MRI (mL) 1139 (687–1965) 519 (410–671) 1488 (1051–2414) <0.0001 htTKV measured by MRI (mL) 678 (398–1109) 302 (248–396) 843 (637–1413) <0.0001 Kidney length (cm) MRI 16.7 ± 4.0 12.8 ± 1.4 18.7 ± 3.6 <0.0001 US 15.8 ± 3.0 12.8 ± 1.6 17.1 ± 2.4 Genotype, n (%) 0.08 PKD1 truncating 31 (45.6) 4 (20.0) 27 (56.3) PKD1 nontruncating 23 (33.8) 9 (45.0) 14 (29.2) PKD2 10 (14.7) 6 (30.0) 4 (8.3) No mutation identified 4 (5.9) 1 (5) 3 (6.3) Hypertension <35 years, n (%) 57 (34.8) 8 (17.4) 49 (41.5) 0.005 Urological events <35 years, n (%) 22 (13.4) 4 (8.7) 18 (15.3) 0.32 All patients, slow progressors (MC 1A–1B) and rapid progressors (MC 1C–1E) are shown. * P-value for comparisons between MC groups. Rapid disease progression based only on age and eGFR cies and percentages. Fisher’s exact test was used to compare categorical variables, whereas the t-test or the Mann–Whitney As an exploratory experiment, an eGFR under a certain thresh- test was used for continuous variables, as appropriate. old at a certain age was evaluated as a criterion for RP. Pa- Kidney function decline was assessed using a slope analysis tients aged 35–45 years with CKD groups 2 and 3, and patients by means of mixed models for repeated measurements taking aged 46–55 years with CKD groups 3 and 4 were considered to into account the intrasubject correlation. The Bland–Altman ap- have RP. proach was used to compare US and MRI assessments [27, 28]. Lin’s coefficient was also employed to assess the concordance Predicting Renal Outcome in Polycystic Kidney Disease [29]. For sensitivity and specificity, the 95% confidence intervals (PROPKD) score (CIs) are based on the Clopper–Pearson exact method [30]. Logis- tic regression models were used to calculate the area under the The PROPKD score was calculated in all patients [26]. A genetic receiver operating characteristic curve (AUROC) as a measure of test was carried out in patients with a PROPKD score of at least the overall performance of the diagnostic predictors [31]. 3 before genetic data were added to the score (potentially RP The analysis was performed using the SAS version 9.4 soft- patients). The reason for this was to minimize the number of ge- ware (SAS Institute Inc., Cary, NC, USA), and the level of signifi- netic tests for the present purpose. Two of these patients were cance was established at the 0.05 level (two-sided). unavailable for genetic testing. Patients with a PROPKD score of >6 were considered to have RP [26]. Genetic testing Family history Genetic testing was performed in index cases by next- generation sequencing using a kidney disease gene panel as pre- The number of affected family members and age at which these viously described [32, 33]. family members needed KRT were collected. Patients with no af- fected parents were considered de novo cases. Patients without family members reaching KRT or without data on their family Limitations history were excluded. Patients with at least two family mem- There is no gold standard prediction model for the definition of bers who reached KRT before 58 years of age were considered to RP in ADPKD, and in choosing the MC as the gold standard to have RP [7]. In addition, we assessed, and considered as having compare the different prediction models, we accepted its limi- RP, those patients with at least one family member who reached tations. Not all patients in our cohort were available for assess- KRT before the age of 58 years, as long as this was the only family ment by all the prediction tools used. Our population may have member who had reached KRT. been biased towards patients with more severe diseases. Statistical analysis RESULTS For descriptive statistics, continuous variables are presented as A total of 164 ADPKD patients were included in the study. Out of mean ± standard deviation or median (interquartile range, i.e. 164 patients, 46 were classified as MC 1A (n = 11) or 1B (n = 35) 25th–75th percentiles), according to their adherence to the Gaus- and 118 as MC 1C (n = 47), 1D (n = 51) or 1E (n = 20). Patients’ sian distribution and categorical data, are presented as frequen- baseline characteristics are described in Table 1. 916 J. Naranjo et al. CKD stage by age 29 at age 18–30 years: CKD 1–3a (eGFR > 45 mL/min/1.73 m2) 28 at age 30–40 years: CKD 2–3a (eGFR 45–90 mL/min/1.73 m2) 10 at age 40–50 years: CKD 3a (eGFR 45–60 mL/min/1.73 m2) 67 Yes 97 No Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 Historical eGFR decline, with no other confounding cause than ADPKD (excluded 23 CKD G1) 1 No 2 41 in one year 2 33 per year over a period of 5 years or more 23 Data not reliable (CKD G1) 2 Data not available Predicted progression by baseline htTKV indexed for age and/or genotype 10 No 15 Mayo Classification 1C, 1D, 1E 2 US kidney length > 16.5 cm and age < 45 years 4 PROPKD > 6 (truncating PKD1 mutation + early symptoms) 41 Yes 15 Yes Rapid progression Likely rapid progression Likely slow progression or eGFR/age outside indication FIGURE 2: The ERA WGIKD/ERBP algorithm used in our cohort to identify patients with rapid disease progression (adapted from [13]). Numbers in bold indicate the number of patients who met each criterion. ERA WGIKD/ERBP algorithm <16.5 cm and 0.20 (0.04–0.35) for kidney length of >20 cm. A total of 37 patients <45 years old had a kidney length of >16.5 cm on A total of 67 patients (40.9%) met the age and eGFR criteria of either MRI (28.2%) or US (29.4%) and were considered to have RP. the ERA WGIKD/ERBP algorithm for evaluation for RP. Of them, All of them were 1C–1E on MC. 56 patients (34.1% of the entire cohort) were considered to have RP using the algorithm (Figure 2). An additional 42 patients, or 109 in total, met the less restrictive age and eGFR criteria ap- Mayo classification by ultrasound plied to the algorithm (see the Materials and methods section). TKV measured by US was available for 69.9% (119/157) of patients Ninety-three of these patients (56.7% of the entire cohort) were who underwent US. US and MRI were performed less than a year considered to have RP using these less restrictive criteria, in- apart in 90% of cases. Median TKV measured by MRI and US was creasing by 66% (93 versus 56) the number of patients identified 1042 mL (924–1160) and 900 mL (810–989), respectively. MCs using by the algorithm as having RP (Figure 3). US and MRI were compared and presented high levels of agree- ment, with a Kendall’s coefficient of 0.83 (0.77–0.88) (Table 2). Of Total kidney volume those patients identified as having RP using MC by US, 94.6% were also identified as having RP using MC by MRI. Only three Bland–Altman plots demonstrated high levels of agreement in patients were considered to have RP using MC by the US but not TKV between MRI and the US, the level of agreement declin- using MC by the MRI. ing as TKV increased (Figure 4). The US underestimated TKV mainly at TKV >1500 mL. Lin’s coefficient was 0.71 (0.52–0.83) at TKV <750 mL and 0.49 (0.20–0.7) at TKV >1500 mL. One hun- Kidney function decline dred and twenty patients had a TKV of >750 mL on MRI and The mean retrospective follow-up (time from first blood test were considered to have RP. Of these, 93.3% were 1C, 1D or 1E to baseline) was 6.8 ± 2.7 years with a mean of 6.3 ± 2.6 blood on MC. Fifty-nine patients had a TKV of >1500 mL on MRI and tests. The eGFR annual decline increased at each stage of MC, as were considered to have RP; 98.3% of these patients were 1C–1E expected (Supplementary data, Figures S1 and S2). Forty-eight on MC, the single exception being a 68-year-old who was 1B on patients with CKD G1 and seven patients with two or fewer MC. blood tests were excluded from this analysis. Of the 109 included patients, 102 (93.6%) had an eGFR decline of 5 mL/min/1.73 m2 in 1 year and were considered to have RP. The proportion of Kidney length >16.5 CM at age <45 years patients with such an eGFR decline was similar for MC 1A–1B Bland–Altman plots also demonstrated high levels of agreement (92%) and MC 1C–1E (94.1%). between MRI and US with respect to kidney length, the level A total of 92 patients had at least two or more blood tests of agreement declining as kidney length increased (Figure 5). within a period of 5 years. Seventy-two of these (78.3%) had a The US again tended to give underestimations of larger kidney mean eGFR decline of 2.5 mL/min/1.73 m2 /year and were consid- lengths. Lin’s coefficient was 0.73 (0.62–0.81) for kidney length of ered to have RP. Of them 60 patients (83.3%) were 1C–1E on MC. Comparative analysis of tools in ADPKD 917 CKD stage by age 41 at age 18–35 years: CKD 1–3 (eGFR > 30 mL/min/1.73 m2) 41 at age 35–45 years: CKD 2–3 (eGFR 30–90 mL/min/1.73 m2) 27 at age 45–55 years: CKD 3–4 (eGFR 15–60 mL/min/1.73 m2) 109 Yes 65 No Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 Historical eGFR decline, with no other confounding cause than ADPKD (excluded 29 CKD G1) 4 No 2 72 in one year 2 54 per year over a period of 5 years or more 29 Data not reliable (CKD G1) 4 Data not available Predicted progression by baseline htTKV indexed for age and/or genotype 12 No 21 Mayo Classification 1C, 1D, 1E 3 US kidney length > 16.5 cm and age < 45 years 5 PROPKD > 6 (truncating PKD1 mutation + early symptoms) 72 Yes 21 Yes Rapid progression Likely rapid progression Likely slow progression or eGFR/age outside indication FIGURE 3: The ERA WGIKD/ERBP algorithm with less restrictive age and eGFR criteria (adapted from [13]). Numbers in bold indicate the number of patients who met each criterion. FIGURE 4: Total kidney volume (TKV) assessed by US and MRI. (A) Bland–Altman plots showing the disagreement between the TKV measured by MRI and by US. The dashed line represents the mean difference (bias) and dotted lines 95% limits of agreement. (B) Concordance between TKV measured by MRI and by US. The bold line at 45 degrees represents the perfect concordance; the grey line indicates the observed regression line and dashed lines the 95% prediction intervals. Sixty-five patients (70.6%) were identified as having RP based were aged between 46 and 55 years old and had an eGFR of 15– on a mean eGFR decline of 3 mL/min/1.73 m2 /year. Of them 54 60 mL/min/1.73 m2 . In total, therefore, 69 patients met the age (83.1%) were 1C–1E on MC. and eGFR criteria and were considered to have RP. Of them 60 patients (87%) were MC 1C–1E. RAPID DISEASE PROGRESSION BASED ONLY ON AGE AND eGFR Propkd score Forty-one patients were aged between 35 and 45 years old and A total of 57 patients had hypertension before the age of 35 years, had an eGFR of 30–90 mL/min/1.73 m2 . Twenty-eight patients of whom 49 patients (86%) were classified as having RP by MC 918 J. Naranjo et al. Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 FIGURE 5: Kidney length assessed by US and MRI. (A) Bland–Altman plots showing the disagreement between the kidney lengths measured by MRI and by US. The dashed line represents the mean difference (bias) and dotted lines 95% limits of agreement. (B) Concordance between the kidney lengths measured by MRI and by US. The bold line at 45 degrees represents the perfect concordance; the grey line indicates the observed regression line and dashed lines the 95% prediction intervals. Table 2. Comparison of the MC as assessed by US and MRI and even intrafamilial variability remain to be totally elucidated. There is a need to define RP in ADPKD for the purposes of selec- US 1A 1B 1C 1D 1E tion of disease-modifying therapies and recruitment to clinical MRI trials [8, 10]. ADPKD with RP may be defined as onset of kid- 1A 11 0 0 0 0 ney failure at a relatively young age, though the threshold has 1B 2 28 3 0 0 yet to be clearly determined. Currently, the only two objective 1C 0 12 19 1 0 means of determining RP are retrospective analysis of an eGFR 1D 0 0 12 13 1 decline and retrospective TKV data. Although there is evidence 1E 0 0 0 3 4 that they are correlated [20], this is not always the case. As is known from clinical practice, some patients have large kidneys with preserved kidney function, while others have impaired kid- (P = 0.005). Twenty-seven patients (16.7%) met the criterion of a ney function with not very large kidneys. As retrospective de- PROPKD score of >6 and were considered to have RP. Of these cline in eGFR is not useful in patients with normal kidney func- patients, 25 (92.6%) were MC 1C–1E. tion and retrospective TKV data are often unavailable, there is a need for prediction tools. Although several prediction tools have Family history been proposed for the assessment of the progression of ADPKD, we chose MC as the gold standard for the definition of RP, ac- A total of 24 patients who did not have family members reach- cepting its limitations. The reason for this decision is that only ing KRT and 11 without available data on family history were ex- imaging tools are able to discriminate RP at early stages of the cluded. Twelve patients were identified as de novo cases. Of the disease, and MC has been shown to perform very accurately for remaining 117 patients, 44 (37.6%) had at least two family mem- this purpose [15, 20]. bers reaching KRT before 58 years of age and were considered A recent study comparing the various decision algorithms to have RP. Thirty-five (79.5%) of these patients were MC 1C–1E. showed a high variability in treatment selection among differ- Eighty-one (69.2%) had at least one family member who reached ent countries [12]. We previously demonstrated how the ERA KRT before the age of 58 years. Sixty (74.1%) of these patients WGIKD/ERBP algorithm, with eGFR stratified by age cut-off, is too were MC 1C–1E. stringent in the clinical setting, preventing RP from being con- sidered in a significant percentage of young patients [16]. In the Sensitivity and specificity of the different tools to present cohort, application of less restrictive eGFR and age crite- predict RP ria resulted in a significant increase in the percentage of patients identified as having RP, confirming that the original algorithm The sensitivity and specificity of the different predictive models misses a substantial number of cases of RP. compared with the MC-based definition of RP as categories 1C– When considering eGFR decline, we observed that an eGFR 1E are shown in Figure 6. decline of ≥5 mL/min/1.73 m2 within 1 year does not seem to be a good criterion for RP. In our cohort, 93.6% of patients had DISCUSSION an eGFR decline ≥5 mL/min/1.73 m2 within 1 year at some point during the follow-up regardless of MC, indicating this eGFR de- Although certain factors are well known to influence the pro- cline to be a very unspecific criterion. An average annual eGFR gression of ADPKD [11], the reasons for the huge interfamilial decline over a certain period seems more reliable to avoid fluctu- Comparative analysis of tools in ADPKD 919 Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 FIGURE 6: Forest plot of sensitivity and specificity estimates. The proportion estimates (percentage) and [AUROC] were pooled according to (1) the ERA WGIKD/ERBP algorithm [0.512], (2) the ERA WGIKD/ERBP algorithm with less restrictive age and eGFR [0.599], (3) TKV >750 mL [0.888], (4) TKV >1500 mL [0.735], (5) kidney length >16.5 cm on MRI and age <45 years [0.718], (6) kidney length >16.5 cm on US and age <45 years [0.726], (7) MC by US [0.874], (8) eGFR decline ≥5 mL/min/1.73 m2 in 1 year [0.510], (9) eGFR decline ≥2.5 mL/min/1.73 m2 /year over 5 years [0.637], (10) eGFR decline ≥3 mL/min/1.73 m2 /year over 5 years [0.659], (11) based only on age and eGFR [0.656], (12) PROPKD >6 [0.586], (13) family history (≥2 family members reaching KRT before the age of 58 years) [0.566] and (14) family history (≥1 family member reaching KRT before the age of 58 years) [0.585]. ations in creatinine. In line with the findings of Irazabal et al. [20], to RP according to MC by MRI. However, classification as MC a more pronounced eGFR decline was observed with increasing 1B and 1C by US did not perform well enough to discriminate MC. In our opinion, an eGFR decline of 2.5 mL/min/1.73 m2 /year between RP and non-RP. In hospitals where access to MRI is is below the threshold for RP (–2.63 for MC 1C according to Iraz- complicated, MC by US could be used to guide the decision to abal et al. [20] and –3.57 in the present study). This is why we order an MRI to assess disease progression. In line with the tested our cohort using a 3 mL/min/1.73 m2 /year eGFR decline. use of US, and as shown in previous studies [24], we obtained a The AUROC improved when the yearly eGFR decline increased high level of agreement with MRI when the kidney length was from 2.5 to 3 mL/min/1.73 m2 /year. The moderate performance <16.5 cm. Based on the results of Bhutani et al. [24], the ERA of the retrospective eGFR decline may be attributed both to the WGIKD/ERBP algorithm proposed that patients <45 years old variability of the creatinine measurement and to the possibility with a kidney length of >16.5 cm on US should be classified as that TKV does not always correlate with eGFR. Larger studies are having RP. In our cohort, 92% of patients who met this criterion needed to define the eGFR decline threshold that performs best were classified as having RP by MC. This could be considered in predicting RP as eventually what will lead the patient to KRT a very specific criterion for the determination of RP, but its is eGFR and not TKV. sensitivity is not so good because it does not detect young Indexing eGFR by age could represent an easy prognostic tool. patients who still have normal-sized kidneys. Interestingly in In the present study, stratification of patients based on age and our cohort, 94.4% of patients with a kidney length of <13 cm and eGFR proved to be very specific. It has the advantage that it is aged >30 years corresponded to non-RP patients according to always available, but also the limitation of not being useful in MC, while 97.1% of patients with a kidney length of >15 cm and young patients with preserved kidney function. aged <50 years were classified as having RP by MC. As expected, all imaging prediction tools were in closer The PROPKD score has been proved to be an excellent pre- agreement with MC than the other prediction models. Many of dictor of RP [26, 34]. In patients with early presentation of hyper- our patients who underwent MRI were patients with enlarged tension or urological events, it seems wise to perform a genetic kidneys on US. In the present cohort, having a TKV of >750 mL on test in order to use the PROPKD score. In our cohort, 95% of pa- MRI (the selection criterion used in the TEMPO trial [8]) identi- tients who had a PROPKD score of >6 were considered to have fied 94.9% of patients classified as having RP by MC. Six patients RP according to MC, this being the most specific but least sen- classified as having RP by MC and with a TKV <750 mL were sitive non-imaging prediction tool. Interestingly, presenting hy- young and their kidneys had still not reached this volume. Also, pertension before the age of 35 years showed a good correlation, a TKV >1500 mL on MRI was analysed as a criterion for RP; it by itself, with MC 1C–1E. This single item of clinical data could was found to be very specific but had low sensitivity. Conse- draw attention to a high possibility of RP. quently, one may conclude that MC performs much better than It is well known that intrafamilial variability is less pro- TKV alone. nounced than interfamilial variability, and it is therefore ex- Although MRI is known to be a more accurate technique than pected that age at the onset of KRT in relatives would be highly US for measuring kidney size, it is still expensive and difficult to predictive of RP. However, there is evidence of marked intrafa- access in many hospitals. For this reason, we explored, for the milial variability, highlighting the complexity of the factors de- first time to our knowledge, the use of TKV measurement by US termining RP [35, 36]. Although family history can be of help in order to calculate MC. The AUROC of MC on US showed an ex- in suggesting RP, by itself it lacks sufficient sensitivity and cellent performance, particularly in extreme MC, i.e. classes 1A, specificity. 1D and 1E. In the present cohort, all patients classified as MC 1A In summary, imaging prediction tools have more agreement by US corresponded to non-RP according to MC by MRI. On the with MC than the other prediction tools. MC by US performs very other hand, all patients with MC 1D or 1E on US corresponded well for MC 1A, 1D and 1E, and could replace MC by MRI in poorly 920 J. Naranjo et al. resourced hospitals. The eGFR decline is sensitive but not very 7. Barua M, Cil O, Paterson AD et al. Family history of renal dis- specific when compared with the MC, whereas the PROPKD score ease severity predicts the mutated gene in ADPKD. J Am Soc is very specific but has low sensitivity. Probably, the task of pre- Nephrol 2009; 20: 1833–1838 diction cannot be absolutely entrusted to a single tool, but the 8. Torres VE, Chapman AB, Devuyst O et al. Tolvaptan in pa- common sense of the nephrologist in conjunction with the use tients with autosomal dominant polycystic kidney disease. of several of the above-mentioned prediction tools, as well as N Engl J Med 2012; 367: 2407–2418 new ones based mostly on biomarkers, will help to identify the 9. Torres VE, Chapman AB, Devuyst O et al. Tolvaptan in later- subpopulation of ADPKD patients who will experience RP. stage autosomal dominant polycystic kidney disease. N Engl J Med 2017; 377: 1930–1942 Downloaded from https://academic.oup.com/ckj/article/15/5/912/6486458 by Fundacio Biblioteca Josep Laporte user on 20 December 2022 10. European Medicines Agency. Summary of medicinal prod- SUPPLEMENTARY DATA uct characteristics Jinarc. http://www.ema.europa.eu/docs/ Supplementary data are available at ckj online. en_GB/document_library/EPAR_-_Product_Information/ human/002788/WC500187921.pdf (10 April 2021, date last accessed) ACKNOWLEDGEMENTS 11. Schrier RW, Brosnahan G, Cadnapaphornchai MA et al. Pre- The study was approved by the Fundació Puigvert institutional dictors of autosomal dominant polycystic kidney disease review board. We acknowledge Xavier Alomar from Clínica Creu progression. J Am Soc Nephrol 2014; 25: 2399–2418 Blanca for technical support on MRI. We thank Anna Mata- 12. Wulfmeyer VC, Auber B, Haller H et al. Comparison of differ- mala from Fundació Puigvert for patient coordination and Ricard ent selection strategies for tolvaptan eligibility among au- Pellejero for his bibliographic assistance. We acknowledge the tosomal dominant polycystic kidney disease patients. Am J patients for taking part in this study. We thank Patricia Ruiz and Nephrol 2019; 50: 281–290 Laura Lorente from Fundació Puigvert for technical support for 13. Gansevoort RT, Arici M, Benzing T et al. Recommendations genetic testing. We also thank the Catalan Government (AGAUR for the use of tolvaptan in autosomal dominant polycystic 2017/SGR-00676) and IIB Sant Pau Biobank for providing some of kidney disease: a position statement on behalf of the ERA– the samples. EDTA Working Groups on Inherited Kidney Disorders and European Renal Best Practice. Nephrol Dial Transplant 2016; 31: 337–348 FUNDING 14. Lavu S, Vaughan LE, Senum SR et al. The value of genotypic and imaging information to predict functional and struc- This study was funded by the Instituto de Salud Carlos III/Fondo tural outcomes in ADPKD. JCI Insight 2020; 5: e138724 Europeo de Desarrollo Regional (FEDER) funds, RETIC REDINREN 15. Messchendorp AL, Meijer E, Visser FW et al. Rapid progres- RD16/0009/0019 FIS FEDER FUNDS (PI18/00362, PI19/01633) and sion of autosomal dominant polycystic kidney disease: uri- Plataforma ISCIII Biobancos PT20/00196. None of the funders had nary biomarkers as predictors. Am J Nephrol 2019; 50: 375–385 any role in study design, data collection, analysis, reporting or 16. Furlano M, Loscos I, Martí T et al. Autosomal dominant poly- the decision to submit for publication. cystic kidney disease: clinical assessment of rapid progres- sion. Am J Nephrol 2018; 48: 308–317 CONFLICT OF INTEREST STATEMENT 17. Perrone RD, Mouksassi MS, Romero K et al. Total kidney vol- ume is a prognostic biomarker of renal function decline and R.T. is member of the CKJ editorial board. The results pre- progression to end-stage renal disease in patients with au- sented in this paper have not been published previously tosomal dominant polycystic kidney disease. Kidney Int Rep in whole or part, except in abstract form in the XLIX 2017; 2: 442–450 Congreso de la S.E.N. 2019 in A Coruña, Spain (Spanish Congress 18. Chebib FT, Torres VE. 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