Switching From TDF to TAF in HIV/HBV-Coinfected Individuals With Renal Dysfunction

A Prospective Cohort Study

Bernard Surial, MD; Charles Béguelin, MD; Jean-Philippe Chave, MD; Marcel Stöckle, MD; Noémie Boillat-Blanco, MD; Thanh Doco-Lecompte, MD; Enos Bernasconi, MD; Jan Fehr, MD; Huldrych F. Günthard, MD; Patrick Schmid, MD; Laura N. Walti, MD; Hansjakob Furrer, MD; Andri Rauch, MD; Gilles Wandeler, MD

Disclosures

J Acquir Immune Defic Syndr. 2020;85(2):227-232. 

In This Article

Methods

Study Design and Population

This multicenter prospective cohort study included all HIV/HBV-coinfected individuals with an eGFR below 90 mL/min/1.73 m2, who had TDF replaced by TAF. The SHCS (www.shcs.ch) is a national cohort that enrolls close to 80% of all adults living with HIV currently receiving ART in Switzerland.[10] All data including laboratory measurements, changes in ART, and co-administered medications are recorded prospectively at enrollment and every 6 months thereafter. Eligible participants were 18 years or older, had a positive hepatitis B surface antigen (HBsAg) or detectable HBV DNA, a suppressed HIV viral load (<200 cp/mL), were on a TDF-containing ART regimen for at least 6 months, and had an eGFR below 90 mL/min/1.73 m2. Pregnant women and individuals with decompensated liver cirrhosis were excluded. Data were collected between January 2014 and February 2020. Local ethical committees of all cohort centers approved this study, and all patients provided written informed consent.

Outcomes and Definitions

Primary outcomes were changes in eGFR [calculated using the chronic kidney disease epidemiology collaboration (CKD-EPI) formula[11]] and urine protein-to-creatinine ratio (normal <15 mg/mmol) in the year before and the year after switch from TDF to TAF. Secondary outcomes were HBV and HIV suppression and HBsAg loss 1 year after the switch, as well as changes in serum ALT in the year before and the year after the switch. We considered all data collected at protocol-defined follow-up visits within 2 years before and 18 months after switching to TAF. Normal ALT levels were defined as ≤25 IU/L for women and ≤35 IU/L for men.[12] Liver fibrosis was assessed using transient elastography (TE) or aspartate aminotransferase-to-platelet ratio index (APRI) if TE was unavailable. Significant fibrosis was defined as liver stiffness >7.0 kPa or APRI >1.5, and cirrhosis as liver stiffness >11.0 kPa or APRI >2.0. Diabetes mellitus was defined as HbA1c ≥6.5% or current antidiabetic treatment, hepatitis C virus infection (HCV) as having a detectable HCV viral load before switch, and hepatitis D virus (HDV) coinfection as having a positive HDV serology. Hazardous alcohol use was assessed using the Alcohol Use Disorders Identification Test Consumption score and defined as ≥3 points in women and ≥4 points in men.[13]

Statistical Analysis

Baseline characteristics were presented using descriptive statistics, and Fisher exact test or Wilcoxon rank sum tests were used for group wise comparisons. Correlation coefficients were calculated using Spearman's rank correlation coefficient. We used linear mixed-effect models with interrupted time series to compare changes in eGFR, urine protein-to-creatinine ratio, and ALT levels between the year before and the year after the switch to TAF.[14] Analyses for eGFR and urine protein-to-creatinine ratio were adjusted for baseline age, sex, ethnicity, diabetes, and treatment for arterial hypertension. Use of integrase inhibitors, atazanavir, lopinavir, rilpivirine, cobicistat, and cotrimoxazole were added as time-varying covariates in renal analyses to account for their potential impact on eGFR. Urine protein-to-creatinine ratio analyses were further adjusted for eGFR at baseline. Analyses of ALT changes were adjusted for baseline age, sex, body mass index, HIV transmission group (persons who inject drugs, men who have sex with men, and others), HCV infection, and HBV replication status. In the latter analysis, hazardous alcohol consumption and the use of efavirenz (EFV) were included as time-varying covariates. All analyses were performed using R version 3.6.2.

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