Abstract

Rationale & ObjectiveSingle measurements of urinary biomarkers reflecting kidney tubule health are associated with chronic kidney disease (CKD) risk in HIV infection, but the prognostic value of repeat measurements over time is unknown.Study DesignCohort study.Setting & Participants647 women living with HIV infection enrolled in the Women’s Interagency Health Study.Exposures14 urinary biomarkers of kidney tubule health measured at 2 visits over a 3-year period.OutcomeIncident CKD, defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 at two 6-month visits and an average eGFR decline ≥ 3% per year.Analytical ApproachWe used multivariable generalized estimating equations adjusting for CKD risk factors to evaluate baseline, time-updated, and change-over-time biomarker associations with incident CKD. We compared CKD discrimination between models with and without a parsimoniously selected set of biomarkers.ResultsDuring a median 7 years of follow-up, 9.7% (63/647) developed CKD. In multivariable-adjusted analyses, 3 of 14 baseline biomarkers associated with incident CKD. In contrast, 10 of 14 time-updated biomarkers and 9 of 14 biomarkers modeled as change over time associated with incident CKD. Urinary epidermal growth factor (EGF), α1-microglobulin (A1M), and albumin were selected using penalized regression methods. In the time-updated model, lower urinary EGF (risk ratio [RR] per 2-fold higher time-updated biomarker levels, 0.69; 95% CI, 0.58-0.81), higher urinary A1M (RR, 1.47; 95% CI, 1.25-1.73), and higher urinary albumin excretion (RR, 1.21; 95% CI, 1.03-1.42) were jointly associated with increased risk for CKD. Compared with a base model (C statistic, 0.75), CKD discrimination improved after adding urinary EGF, A1M, and albumin values across baseline (C = 0.81), time-updated (C = 0.83), and change-over-time (C = 0.83) models (P < 0.01 for all).LimitationsObservational design, incident CKD definition limited to eGFR.ConclusionsRepeat urinary biomarker measurements for kidney tubule health have stronger associations with incident CKD compared with baseline measurements and moderately improve CKD discrimination in women living with HIV infection.

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