Rupal Mehta1, Xuan Cai2, Jungwha Lee2, Dawei Xie3, Xue Wang3, Julia Scialla4, Amanda H Anderson5, Jon Taliercio6, Mirela Dobre7, Jing Chen5, Michael Fischer8, Mary Leonard9, James Lash10, Chi-Yuan Hsu11, Ian H de Boer12, Harold I Feldman13, Myles Wolf4, Tamara Isakova14. 1. Division of Nephrology and Hypertension, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL; Center for Translational Metabolism and Health, Institute of Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL; Jesse Brown Veterans Administration Medical Center, Chicago, IL. Electronic address: rupal.mehta@northwestern.edu. 2. Center for Translational Metabolism and Health, Institute of Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL. 3. Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, PA; Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, PA. 4. Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, NC; Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC. 5. Department of Medicine, Tulane University School of Medicine, New Orleans, LA. 6. Department of Nephrology and Hypertension, Cleveland Clinic, Cleveland, OH. 7. Division of Nephrology and Hypertension, University Hospitals, Cleveland Medical Center, Cleveland, OH. 8. Jesse Brown Veterans Administration Medical Center, Chicago, IL; Division of Nephrology, Department of Medicine, University of Illinois at Chicago College of Medicine and Center of Innovation for Complex Chronic Healthcare, Chicago, IL. 9. Department of Pediatrics, Stanford University, Stanford, CA; Department of Medicine, Stanford University, Stanford, CA. 10. Division of Nephrology, Department of Medicine, University of Illinois at Chicago College of Medicine and Center of Innovation for Complex Chronic Healthcare, Chicago, IL. 11. Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, CA. 12. Division of Nephrology and Kidney Research Institute, University of Washington, Seattle, WA. 13. Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, PA; Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, PA; Renal Electrolyte and Hypertension Division, Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, PA. 14. Division of Nephrology and Hypertension, Department of Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL; Center for Translational Metabolism and Health, Institute of Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL.
Abstract
RATIONALE & OBJECTIVE: Studies using a single measurement of fibroblast growth factor 23 (FGF-23) suggest that elevated FGF-23 levels are associated with increased risk for requirement for kidney replacement therapy (KRT) in patients with chronic kidney disease. However, the data do not account for changes in FGF-23 levels as kidney disease progresses. STUDY DESIGN: Case-cohort study. SETTING & PARTICIPANTS: To evaluate the association between serial FGF-23 levels and risk for requiring KRT, our primary analysis included 1,597 individuals in the Chronic Renal Insufficiency Cohort Study who had up to 5 annual measurements of carboxy-terminal FGF-23. There were 1,135 randomly selected individuals, of whom 266 initiated KRT, and 462 individuals who initiated KRT outside the random subcohort. EXPOSURE: Serial FGF-23 measurements and FGF-23 trajectory group membership. OUTCOMES: Incident KRT. ANALYTICAL APPROACH: To handle time-dependent confounding, our primary analysis of time-updated FGF-23 levels used time-varying inverse probability weighting in a discrete time failure model. To compare our results with prior data, we used baseline and time-updated FGF-23 values in weighted Cox regression models. To examine the association of FGF-23 trajectory subgroups with risk for incident KRT, we used weighted Cox models with FGF-23 trajectory groups derived from group-based trajectory modeling as the exposure. RESULTS: In our primary analysis, the HR for the KRT outcome per 1 SD increase in the mean of natural log-transformed (ln)FGF-23 in the past was 1.94 (95% CI, 1.51-2.49). In weighted Cox models using baseline and time-updated values, elevated FGF-23 level was associated with increased risk for incident KRT (HRs per 1 SD ln[FGF-23] of 1.18 [95% CI, 1.02-1.37] for baseline and 1.66 [95% CI, 1.49-1.86] for time-updated). Membership in the slowly and rapidly increasing FGF-23 trajectory groups was associated with ∼3- and ∼21-fold higher risk for incident KRT compared to membership in the stable FGF-23 trajectory group. LIMITATIONS: Residual confounding and lack of intact FGF-23 values. CONCLUSIONS: Increasing FGF-23 levels are independently associated with increased risk for incident KRT.
RATIONALE & OBJECTIVE: Studies using a single measurement of fibroblast growth factor 23 (FGF-23) suggest that elevated FGF-23 levels are associated with increased risk for requirement for kidney replacement therapy (KRT) in patients with chronic kidney disease. However, the data do not account for changes in FGF-23 levels as kidney disease progresses. STUDY DESIGN: Case-cohort study. SETTING & PARTICIPANTS: To evaluate the association between serial FGF-23 levels and risk for requiring KRT, our primary analysis included 1,597 individuals in the Chronic Renal Insufficiency Cohort Study who had up to 5 annual measurements of carboxy-terminal FGF-23. There were 1,135 randomly selected individuals, of whom 266 initiated KRT, and 462 individuals who initiated KRT outside the random subcohort. EXPOSURE: Serial FGF-23 measurements and FGF-23 trajectory group membership. OUTCOMES: Incident KRT. ANALYTICAL APPROACH: To handle time-dependent confounding, our primary analysis of time-updated FGF-23 levels used time-varying inverse probability weighting in a discrete time failure model. To compare our results with prior data, we used baseline and time-updated FGF-23 values in weighted Cox regression models. To examine the association of FGF-23 trajectory subgroups with risk for incident KRT, we used weighted Cox models with FGF-23 trajectory groups derived from group-based trajectory modeling as the exposure. RESULTS: In our primary analysis, the HR for the KRT outcome per 1 SD increase in the mean of natural log-transformed (ln)FGF-23 in the past was 1.94 (95% CI, 1.51-2.49). In weighted Cox models using baseline and time-updated values, elevated FGF-23 level was associated with increased risk for incident KRT (HRs per 1 SD ln[FGF-23] of 1.18 [95% CI, 1.02-1.37] for baseline and 1.66 [95% CI, 1.49-1.86] for time-updated). Membership in the slowly and rapidly increasing FGF-23 trajectory groups was associated with ∼3- and ∼21-fold higher risk for incident KRT compared to membership in the stable FGF-23 trajectory group. LIMITATIONS: Residual confounding and lack of intact FGF-23 values. CONCLUSIONS: Increasing FGF-23 levels are independently associated with increased risk for incident KRT.
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