Agalsidase Beta Treatment Slows Estimated Glomerular Filtration Rate Loss In Classic Fabry Disease Patients: Results From An Individual Patient Data Meta-Analysis

CLINICAL KIDNEY JOURNAL(2021)

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摘要
Background. Fabry disease is a rare, X-linked genetic disorder that, if untreated in patients with the Classic phenotype, often progresses to end-stage kidney disease. This meta-analysis determined the effect of agalsidase beta on loss of estimated glomerular filtration rate (eGFR) in the Classic phenotype using an expansive evidence base of individual patient-level data.Methods. The evidence base included four Sanofi-Genzyme studies and six studies from a systematic literature review. These were restricted to Classic Fabry patients meeting the eligibility criteria from Phases III and IV agalsidase beta trials, including 315 patients (161 treated). Linear regression was first used to model annual change in eGFR for each patient and the resulting annualized eGFR slopes were modelled with treatment and covariates using quantile regression. These results were then used to estimate median annualized eGFR change in agalsidase beta treated versus untreated groups.Results. Imbalances across treatment groups were found in baseline age, sex and proteinuria, but not in the use of renin- angiotensin system blockers. The adjusted model suggests that treated (agalsidase beta) patients experienced a slower median eGFR decrease [2.46 mL/min/1.73 m(2)/year slower; 95% confidence interval (CI) 0.63-4.29; P = 0.0087] than comparable untreated patients. The median eGFR decrease was 2.64 mL/min/1.73 m(2)/year slower (95% CI 0.53-4.78; P = 0.0141) in treated Classic males.Conclusions. Using an expansive evidence base and robust modelling approach, these data indicate that agalsidase betatreated patients with the Classic phenotype conserve their renal function better than untreated patients.
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关键词
agalsidase beta, chronic kidney disease outcomes, classic phenotype, Fabry disease, glomerular filtration rate, individual patient data meta-analysis
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