2018
DOI: 10.1186/s12882-017-0804-2
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A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model

Abstract: BackgroundAutosomal dominant polycystic kidney disease (ADPKD) is the leading inheritable cause of end-stage renal disease (ESRD); however, the natural course of disease progression is heterogeneous between patients. This study aimed to develop a natural history model of ADPKD that predicted progression rates and long-term outcomes in patients with differing baseline characteristics.MethodsThe ADPKD Outcomes Model (ADPKD-OM) was developed using available patient-level data from the placebo arm of the Tolvaptan… Show more

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Cited by 45 publications
(40 citation statements)
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“…Through ionic mechanisms presented herein, it or other structurally similar non-peptide compounds that can be preferentially used for oral intake, is able to influence the functional activities of endocrine or renal tubular cells, if similar findings occur in vivo . Our findings also highlight an important alternative aspect that needs to be taken into account, inasmuch as the aquaretic effects of TLV in different pathologic disorders including polycystic kidney disease, cirrhosis or heart failure, are evaluated (Ghali et al, 2009; Graziani et al, 2012; Mancinelli et al, 2016; Clark et al, 2017; Sweeney and Avner, 2017; (Torres et al, 2017; van Gastel and Torres, 2017; Wu et al, 2017a; Chebib et al, 2018; Edwards et al, 2018; Imamura and Kinugawa, 2018; Matsukawa et al, 2018; McEwan et al, 2018; Müller et al, 2018; Oguro et al, 2018b; Poch et al, 2018; Sen et al, 2018; Takimura et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Through ionic mechanisms presented herein, it or other structurally similar non-peptide compounds that can be preferentially used for oral intake, is able to influence the functional activities of endocrine or renal tubular cells, if similar findings occur in vivo . Our findings also highlight an important alternative aspect that needs to be taken into account, inasmuch as the aquaretic effects of TLV in different pathologic disorders including polycystic kidney disease, cirrhosis or heart failure, are evaluated (Ghali et al, 2009; Graziani et al, 2012; Mancinelli et al, 2016; Clark et al, 2017; Sweeney and Avner, 2017; (Torres et al, 2017; van Gastel and Torres, 2017; Wu et al, 2017a; Chebib et al, 2018; Edwards et al, 2018; Imamura and Kinugawa, 2018; Matsukawa et al, 2018; McEwan et al, 2018; Müller et al, 2018; Oguro et al, 2018b; Poch et al, 2018; Sen et al, 2018; Takimura et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Another prediction instrument is the ADPKD Outcomes Model (ADPKD-OM), a fixed-time increment stochastic simulation model based on disease progression equations for HtTKV and estimated glomerular filtration rate (eGFR). The model was internally validated with data from the placebo arm of the TEMPO (Tolvaptan Efficacy and Safety in Management of Autosomal Dominant Polycystic Kidney Disease and Its Outcomes) 3:4 tolvaptan study [43]. Finally, a neural network for eGFR prediction was suggested.…”
Section: Early Identification Of Patients For Future Therapy: Whom Anmentioning
confidence: 99%
“…The model showed that differences in baseline TKV can markedly affect time to ESRD, and that younger patient cohorts with large kidneys would enter ESRD at a younger age. For example, the predicted age of progression to ESRD in a patient aged 30 with eGFR 110 mL/min/1.73 m 2 and a TKV of 1,000 mL, would be 49-54 years, compared with 60-65 years for a patient aged 45 years with eGFR 80 mL/ min/1.73 m 2 and a TKV of 1,000 mL [54].…”
Section: Adpkd Outcomes Modelmentioning
confidence: 99%
“…The APDKD outcomes model was developed using TKV and eGFR progression rates derived from the placebo arm of the TEMPO 3: 4 trial [54]. The model simulates disease progression of hypothetical patient cohorts over prespecified time horizons, taking into account covariates including age, sex, and baseline TKV.…”
Section: Adpkd Outcomes Modelmentioning
confidence: 99%