Literature DB >> 31445926

Single Measurements of Carboxy-Terminal Fibroblast Growth Factor 23 and Clinical Risk Prediction of Adverse Outcomes in CKD.

Daniel Edmonston1, Daniel Wojdyla2, Rupal Mehta3, Xuan Cai4, Claudia Lora5, Debbie Cohen6, Raymond R Townsend6, Jiang He7, Alan S Go8, John Kusek9, Matthew R Weir10, Tamara Isakova3, Michael Pencina11, Myles Wolf12.   

Abstract

RATIONALE &
OBJECTIVE: An elevated fibroblast growth factor 23 (FGF-23) level is independently associated with adverse outcomes in populations with chronic kidney disease, but it is unknown whether FGF-23 testing can improve clinical risk prediction in individuals. STUDY
DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Participants in the Chronic Renal Insufficiency Cohort (CRIC) Study (n = 3,789). EXPOSURE: Baseline carboxy-terminal FGF-23 (cFGF-23) level. OUTCOMES: All-cause and cardiovascular (CV) mortality, incident end-stage renal disease (ESRD), heart failure (HF) admission, and atherosclerotic events at 3, 5, and 8 years. ANALYTICAL APPROACH: We assessed changes in model performance by change in area under the receiver operating characteristic curve (ΔAUC), integrated discrimination improvement (IDI), relative IDI, and net reclassification index (NRI) above standard clinical factors. We performed sensitivity analyses, including an additional model comparing the addition of phosphate rather than cFGF-23 level and repeating our analyses using an internal cross-validation cohort.
RESULTS: Addition of a single baseline value of cFGF-23 to a base prediction model improved prediction of all-cause mortality (ΔAUC, 0.017 [95% CI, 0.001-0.033]; IDI, 0.021 [95% CI, 0.006-0.036]; relative IDI, 32.7% [95% CI, 8.5%-56.9%]), and HF admission (ΔAUC, 0.008 [95% CI, 0.0004-0.016]; IDI, 0.019 [95% CI, 0.004-0.034]; relative IDI, 10.0% [95% CI, 1.8%-18.3%]), but not CV mortality, ESRD, or atherosclerotic events at 3 years of follow-up. The NRI did not reach statistical significance for any of the 3-year outcomes. The incremental predictive utility of cFGF-23 level diminished in analyses of the 5- and 8-year outcomes. The cFGF-23 models outperformed the phosphate model for each outcome. LIMITATIONS: Power to detect increased CV mortality likely limited by low event rate. The NRI is not generalizable without accepted prespecified risk thresholds.
CONCLUSIONS: Among individuals with CKD, single measurements of cFGF-23 improve prediction of risks for all-cause mortality and HF admission but not CV mortality, ESRD, or atherosclerotic events. Future studies should evaluate the predictive utility of repeated cFGF-23 testing.
Copyright © 2019 National Kidney Foundation, Inc. All rights reserved.

Entities:  

Keywords:  Fibroblast growth factor 23 (FGF23); atherosclerotic disease; biomarker; cardiovascular mortality; chronic kidney disease (CKD); clinical risk prediction; end-stage renal disease (ESRD); heart failure (HF); mortality

Mesh:

Substances:

Year:  2019        PMID: 31445926      PMCID: PMC6875624          DOI: 10.1053/j.ajkd.2019.05.026

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   8.860


  48 in total

1.  Intact fibroblast growth factor 23 levels predict incident cardiovascular event before but not after the start of dialysis.

Authors:  Chikako Nakano; Takayuki Hamano; Naohiko Fujii; Yoshitsugu Obi; Isao Matsui; Kodo Tomida; Satoshi Mikami; Kazunori Inoue; Akihiro Shimomura; Yasuyuki Nagasawa; Noriyuki Okada; Yoshiharu Tsubakihara; Hiromi Rakugi; Yoshitaka Isaka
Journal:  Bone       Date:  2012-03-06       Impact factor: 4.398

2.  Fibroblast growth factor 23 and risks of mortality and end-stage renal disease in patients with chronic kidney disease.

Authors:  Tamara Isakova; Huiliang Xie; Wei Yang; Dawei Xie; Amanda Hyre Anderson; Julia Scialla; Patricia Wahl; Orlando M Gutiérrez; Susan Steigerwalt; Jiang He; Stanley Schwartz; Joan Lo; Akinlolu Ojo; James Sondheimer; Chi-yuan Hsu; James Lash; Mary Leonard; John W Kusek; Harold I Feldman; Myles Wolf
Journal:  JAMA       Date:  2011-06-15       Impact factor: 56.272

3.  Fibroblast growth factor-23 and cardiovascular events in CKD.

Authors:  Julia J Scialla; Huiliang Xie; Mahboob Rahman; Amanda Hyre Anderson; Tamara Isakova; Akinlolu Ojo; Xiaoming Zhang; Lisa Nessel; Takayuki Hamano; Juan E Grunwald; Dominic S Raj; Wei Yang; Jiang He; James P Lash; Alan S Go; John W Kusek; Harold Feldman; Myles Wolf
Journal:  J Am Soc Nephrol       Date:  2013-10-24       Impact factor: 10.121

4.  Fibroblast growth factor 23 in patients undergoing peritoneal dialysis.

Authors:  Tamara Isakova; Huiliang Xie; Allison Barchi-Chung; Gabriela Vargas; Nicole Sowden; Jessica Houston; Patricia Wahl; Andrew Lundquist; Michael Epstein; Kelsey Smith; Gabriel Contreras; Luis Ortega; Oliver Lenz; Patricia Briones; Phyllis Egbert; T Alp Ikizler; Harald Jueppner; Myles Wolf
Journal:  Clin J Am Soc Nephrol       Date:  2011-09-08       Impact factor: 8.237

5.  High levels of serum fibroblast growth factor (FGF)-23 are associated with increased mortality in long haemodialysis patients.

Authors:  Guillaume Jean; Jean-Claude Terrat; Thierry Vanel; Jean-Marc Hurot; Christie Lorriaux; Brice Mayor; Charles Chazot
Journal:  Nephrol Dial Transplant       Date:  2009-04-25       Impact factor: 5.992

6.  Fibroblast growth factor 23 (FGF23) predicts progression of chronic kidney disease: the Mild to Moderate Kidney Disease (MMKD) Study.

Authors:  Danilo Fliser; Barbara Kollerits; Ulrich Neyer; Donna P Ankerst; Karl Lhotta; Arno Lingenhel; Eberhard Ritz; Florian Kronenberg; Erich Kuen; Paul König; Günter Kraatz; Johannes F E Mann; Gerhard A Müller; Hans Köhler; Peter Riegler
Journal:  J Am Soc Nephrol       Date:  2007-07-26       Impact factor: 10.121

7.  Fibroblast growth factor 23 and cardiovascular mortality after kidney transplantation.

Authors:  Leandro C Baia; Jelmer K Humalda; Marc G Vervloet; Gerjan Navis; Stephan J L Bakker; Martin H de Borst
Journal:  Clin J Am Soc Nephrol       Date:  2013-08-08       Impact factor: 8.237

8.  Chronic Renal Insufficiency Cohort (CRIC) Study: baseline characteristics and associations with kidney function.

Authors:  James P Lash; Alan S Go; Lawrence J Appel; Jiang He; Akinlolu Ojo; Mahboob Rahman; Raymond R Townsend; Dawei Xie; Denise Cifelli; Janet Cohan; Jeffrey C Fink; Michael J Fischer; Crystal Gadegbeku; L Lee Hamm; John W Kusek; J Richard Landis; Andrew Narva; Nancy Robinson; Valerie Teal; Harold I Feldman
Journal:  Clin J Am Soc Nephrol       Date:  2009-06-18       Impact factor: 8.237

Review 9.  Update on fibroblast growth factor 23 in chronic kidney disease.

Authors:  Myles Wolf
Journal:  Kidney Int       Date:  2012-05-23       Impact factor: 10.612

10.  Fibroblast growth factor-23 and incident coronary heart disease, heart failure, and cardiovascular mortality: the Atherosclerosis Risk in Communities study.

Authors:  Pamela L Lutsey; Alvaro Alonso; Elizabeth Selvin; James S Pankow; Erin D Michos; Sunil K Agarwal; Laura R Loehr; John H Eckfeldt; Josef Coresh
Journal:  J Am Heart Assoc       Date:  2014-06-10       Impact factor: 5.501

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  5 in total

1.  Association between albumin-to-globulin ratio and long-term mortality in patients with chronic kidney disease: a cohort study.

Authors:  Mengru Zeng; Yu Liu; Fuyou Liu; Youming Peng; Lin Sun; Li Xiao
Journal:  Int Urol Nephrol       Date:  2020-05-13       Impact factor: 2.370

Review 2.  Regulation of FGF23: Beyond Bone.

Authors:  Petra Simic; Jodie L Babitt
Journal:  Curr Osteoporos Rep       Date:  2021-11-10       Impact factor: 5.096

Review 3.  Fibroblast growth factor 23: are we ready to use it in clinical practice?

Authors:  Annet Bouma-de Krijger; Marc G Vervloet
Journal:  J Nephrol       Date:  2020-03-04       Impact factor: 3.902

Review 4.  Inflammation: a putative link between phosphate metabolism and cardiovascular disease.

Authors:  Jakob Voelkl; Daniela Egli-Spichtig; Ioana Alesutan; Carsten A Wagner
Journal:  Clin Sci (Lond)       Date:  2021-01-15       Impact factor: 6.124

5.  Improved cardiovascular risk prediction in patients with end-stage renal disease on hemodialysis using machine learning modeling and circulating microribonucleic acids.

Authors:  David de Gonzalo-Calvo; Pablo Martínez-Camblor; Christian Bär; Kevin Duarte; Nicolas Girerd; Bengt Fellström; Roland E Schmieder; Alan G Jardine; Ziad A Massy; Hallvard Holdaas; Patrick Rossignol; Faiez Zannad; Thomas Thum
Journal:  Theranostics       Date:  2020-07-09       Impact factor: 11.556

  5 in total

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