Hertzel C Gerstein1, Guillaume Paré2,3, Matthew J McQueen2, Shun Fu Lee2, Shrikant I Bangdiwala2, Aimo Kannt4, Sibylle Hess. 1. Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada gerstein@mcmaster.ca. 2. Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada. 3. Thrombosis and Atherosclerosis Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, Ontario, Canada. 4. Sanofi Aventis Deutschland GmbH Research and Development, Frankfurt, Germany.
Abstract
OBJECTIVE: Diabetes is a major risk factor for renal function decline and failure. The availability of multiplex panels of biochemical markers provides the opportunity to identify novel biomarkers that can better predict changes in renal function than routinely available clinical markers. RESEARCH DESIGN AND METHODS: The concentration of 239 biochemical markers was measured in stored serum from participants in the biomarker substudy of Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Repeated-measures mixed-effects models were used to compute the annual change in eGFR (measured as mL/min/1.73 m2/year) for the 7,482 participants with a recorded baseline and follow-up eGFR. Linear regression models using forward selection were used to identify the independent biomarker determinants of the annual change in eGFR after accounting for baseline HbA1c, baseline eGFR, and routinely measured clinical risk factors. The incidence of the composite renal outcome (i.e., renal replacement therapy, renal death, renal failure, albuminuria progression, doubling of serum creatinine) and death within each fourth of change in eGFR predicted from these models was also estimated. RESULTS: During 6.2 years of median follow-up, the median annual change in eGFR was -0.18 mL/min/1.73 m2/year. Fifteen biomarkers independently predicted eGFR decline after accounting for cardiovascular risk factors, as did 12 of these plus 1 additional biomarker after accounting for renal risk factors. Every 0.1 mL/min/1.73 m2 predicted annual fall in eGFR predicted a 13% (95% CI 12, 14%) higher mortality. CONCLUSIONS: Adding up to 16 biomarkers to routinely measured clinical risk factors improves the prediction of annual change in eGFR in people with dysglycemia.
OBJECTIVE:Diabetes is a major risk factor for renal function decline and failure. The availability of multiplex panels of biochemical markers provides the opportunity to identify novel biomarkers that can better predict changes in renal function than routinely available clinical markers. RESEARCH DESIGN AND METHODS: The concentration of 239 biochemical markers was measured in stored serum from participants in the biomarker substudy of Outcome Reduction With Initial Glargine Intervention (ORIGIN) trial. Repeated-measures mixed-effects models were used to compute the annual change in eGFR (measured as mL/min/1.73 m2/year) for the 7,482 participants with a recorded baseline and follow-up eGFR. Linear regression models using forward selection were used to identify the independent biomarker determinants of the annual change in eGFR after accounting for baseline HbA1c, baseline eGFR, and routinely measured clinical risk factors. The incidence of the composite renal outcome (i.e., renal replacement therapy, renal death, renal failure, albuminuria progression, doubling of serum creatinine) and death within each fourth of change in eGFR predicted from these models was also estimated. RESULTS: During 6.2 years of median follow-up, the median annual change in eGFR was -0.18 mL/min/1.73 m2/year. Fifteen biomarkers independently predicted eGFR decline after accounting for cardiovascular risk factors, as did 12 of these plus 1 additional biomarker after accounting for renal risk factors. Every 0.1 mL/min/1.73 m2 predicted annual fall in eGFR predicted a 13% (95% CI 12, 14%) higher mortality. CONCLUSIONS: Adding up to 16 biomarkers to routinely measured clinical risk factors improves the prediction of annual change in eGFR in people with dysglycemia.
Authors: Federica Storti; Jennifer Pulley; Pascal Kuner; Markus Abt; Ulrich F O Luhmann Journal: Transl Vis Sci Technol Date: 2021-10-04 Impact factor: 3.283