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A disease progression model estimating the benefit of tolvaptan on time to end-stage renal disease for patients with rapidly progressing autosomal dominant polycystic kidney disease.
Mader, Gregory; Mladsi, Deirdre; Sanon, Myrlene; Purser, Molly; Barnett, Christine L; Oberdhan, Dorothee; Watnick, Terry; Seliger, Stephen.
Afiliação
  • Mader G; RTI Health Solutions, Research Triangle Park, NC, USA.
  • Mladsi D; RTI Health Solutions, Research Triangle Park, NC, USA. dmladsi@rti.org.
  • Sanon M; Otsuka Pharmaceutical Development & Commercialization, Inc., Princeton, NJ, USA.
  • Purser M; RTI Health Solutions, Research Triangle Park, NC, USA.
  • Barnett CL; RTI Health Solutions, Research Triangle Park, NC, USA.
  • Oberdhan D; Otsuka Pharmaceutical Development & Commercialization, Inc., Princeton, NJ, USA.
  • Watnick T; University of Maryland School of Medicine, Baltimore, MD, USA.
  • Seliger S; University of Maryland School of Medicine, Baltimore, MD, USA.
BMC Nephrol ; 23(1): 334, 2022 10 18.
Article em En | MEDLINE | ID: mdl-36258169
BACKGROUND: Tolvaptan was approved in the United States in 2018 for patients with autosomal dominant polycystic kidney disease (ADPKD) at risk of rapid progression as assessed in a 3-year phase 3 clinical trial (TEMPO 3:4). An extension study (TEMPO 4:4) showed continued delay in progression at 2 years, and a trial in patients with later-stage disease (REPRISE) provided confirmatory evidence of efficacy. Given the relatively shorter-term duration of the clinical trials, estimating the longer-term benefit associated with tolvaptan via extrapolation of the treatment effect is an important undertaking. METHODS: A model was developed to simulate a cohort of patients with ADPKD at risk of rapid progression and predict their long-term outcomes using an algorithm organized around the Mayo Risk Classification system, which has five subclasses (1A through 1E) based on estimated kidney growth rates. The model base-case population represents 1280 patients enrolled in TEMPO 3:4 beginning in chronic kidney disease (CKD) stages G1, G2, and G3 across Mayo subclasses 1C, 1D, and 1E. The algorithm was used to predict longer-term natural history health outcomes. The estimated treatment effect of tolvaptan from TEMPO 3:4 was applied to the natural history to predict the longer-term treatment benefit of tolvaptan. For the cohort, analyzed once reflecting natural history and once assuming treatment with tolvaptan, the model estimated lifetime progression through CKD stages, end-stage renal disease (ESRD), and death. RESULTS: When treated with tolvaptan, the model cohort was predicted to experience a 3.1-year delay of ESRD (95% confidence interval: 1.8 to 4.4), approximately a 23% improvement over the estimated 13.7 years for patients not receiving tolvaptan. Patients beginning tolvaptan treatment in CKD stages G1, G2, and G3 were predicted to experience estimated delays of ESRD, compared with patients not receiving tolvaptan, of 3.8 years (21% improvement), 3.0 years (24% improvement), and 2.1 years (28% improvement), respectively. CONCLUSIONS: The model estimated that patients treated with tolvaptan versus no treatment spent more time in earlier CKD stages and had later onset of ESRD. Findings highlight the potential long-term value of early intervention with tolvaptan in patients at risk of rapid ADPKD progression.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 6_ODS3_enfermedades_notrasmisibles Base de dados: MEDLINE Assunto principal: Rim Policístico Autossômico Dominante / Tolvaptan / Falência Renal Crônica Tipo de estudo: Prognostic_studies Aspecto: Patient_preference Limite: Humans Idioma: En Revista: BMC Nephrol Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 6_ODS3_enfermedades_notrasmisibles Base de dados: MEDLINE Assunto principal: Rim Policístico Autossômico Dominante / Tolvaptan / Falência Renal Crônica Tipo de estudo: Prognostic_studies Aspecto: Patient_preference Limite: Humans Idioma: En Revista: BMC Nephrol Ano de publicação: 2022 Tipo de documento: Article