A systematic review of the predictors of disease progression in patients with autosomal dominant polycystic kidney disease

Abstract

BackgroundAutosomal dominant polycystic kidney disease (ADPKD) is a genetic disorder characterised by progressive renal cyst formation leading to renal failure in the majority of patients. The likelihood and rate of ADPKD progression is difficult to predict and there is a clear need to identify prognostic indicators that could be used to anticipate ADPKD progression, to aid the management of patients in clinical practice.MethodsA systematic literature review was conducted to identify publications detailing the natural history of ADPKD, including diagnosis, prognosis and progression. Publications were identified and filtered, and data were extracted, based on a predefined research protocol.ResultsThe review identified 2799 journal articles and 444 conference abstracts; 254 articles, including observational studies, clinical trials and reviews, proceeded to data extraction. Disease progression was associated with a variety of prognostic indicators, most commonly age and total kidney volume (TKV). In the identified clinical trials, the absence of a consistent measure of disease progression led to variation in the primary endpoints used. Consequently, there was difficulty in consistently and effectively demonstrating and comparing the efficacy of investigational treatments across studies. More consistency was found in the observational studies, where disease progression was most frequently measured by TKV and glomerular filtration rate.ConclusionsThis systematic review identified age and TKV as the most commonly cited prognostic indicators in the published ADPKD literature. It is envisaged that this review may inform future research, trial design and predictive models of ADPKD natural history, helping to optimise patient care.Electronic supplementary materialThe online version of this article (doi:10.1186/s12882-015-0114-5) contains supplementary material, which is available to authorized users.

A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model

“…To identify relationships between TKV, eGFR and available patient risk factors, exploratory analysis of patient-level data from the TEMPO 3:4 placebo arm (Table 1 ) was conducted using R version 2.12.2. Candidate prognostic variables assessed within a multivariable regression framework included those identified in the literature [ 10 ], agreed upon by clinical experts in ADPKD management, and available within the TEMPO 3:4 dataset: baseline age, gender, child bearing age, ethnicity, region, country, TKV (analysed at baseline, 12, 24 and 36 months) and eGFR (analysed at corresponding timepoints). Candidate variables were entered into the model simultaneously, and the step AIC approach [ 14 ] was used to identify candidate models and test for interactions between covariates.…”

“…Early identification of ADPKD patients with rapidly progressing disease may facilitate the selection of those most likely to benefit from treatment in clinical trials and clinical practice; thus, improving the cost-effectiveness and benefit-to-risk ratio of novel therapies in a population with high unmet need [ 1 , 8 , 9 ]. A systematic literature review by Woon et al identified age at diagnosis and total kidney volume (TKV) as the most commonly cited prognostic indicators associated with rapid ADPKD progression [ 10 ]; additional factors reported in the literature include baseline GFR, male gender and PKD1 mutation [ 1 , 3 , 10 ].…”

“…The development of therapies that delay ADPKD progression drive the requirement for resources that identify patients eligible for treatment and optimise clinical decision-making. Since early-stage ADPKD is largely undiagnosed, and disease progression towards ESRD is heterogeneous and prolonged over several decades, the size and length of clinical trials in ADPKD are insufficient to capture the natural history of the disease [ 10 ]. Alternatively, simulation modelling can predict disease progression over time horizons longer than that feasible in clinical trials, and may therefore represent a useful tool to model the natural rate of renal decline, particularly when measurable and/or observable patient characteristics are used as inputs.…”

KIM-1 and Kidney Disease Progression in Autosomal Dominant Polycystic Kidney Disease: HALT-PKD Results

“…The covariates adjusted for in the analysis included: age, gender, PKD genotype (PKD 1 or PKD 2), baseline systolic and diastolic BP, baseline BMI, baseline eGFR (for HtTKV analysis only), and baseline uACR. These variables were chosen for inclusion due to their strong epidemiologic associations with progression of disease in ADPKD [20].…”

Recommendations for the use of tolvaptan in autosomal dominant polycystic kidney disease: a position statement on behalf of the ERA-EDTA Working Groups on Inherited Kidney Disorders and European Renal Best Practice

“…A number of studies have tried to identify markers that can predict rapid progression to ESRD in ADPKD [ 24 , 25 ]. Figure 1 shows that a wide variety of markers has been considered, but in the present article we will concentrate on those that are better validated (highlighted in Figure 1 ), bearing in mind that not all factors are independent.…”