A Health Survey-Based Prediction Equation for Incident CKD.


Journal

Clinical journal of the American Society of Nephrology : CJASN
ISSN: 1555-905X
Titre abrégé: Clin J Am Soc Nephrol
Pays: United States
ID NLM: 101271570

Informations de publication

Date de publication:
01 01 2023
Historique:
received: 12 05 2022
accepted: 17 10 2022
pmc-release: 01 01 2024
entrez: 31 1 2023
pubmed: 1 2 2023
medline: 3 2 2023
Statut: ppublish

Résumé

Prediction tools that incorporate self-reported health information could increase CKD awareness, identify modifiable lifestyle risk factors, and prevent disease. We developed and validated a survey-based prediction equation to identify individuals at risk for incident CKD (eGFR <60 ml/min per 1.73 m2), with and without a baseline eGFR. A cohort of adults with an eGFR ≥70 ml/min per 1.73 m2 from Ontario, Canada, who completed a comprehensive general population health survey between 2000 and 2015 were included (n=22,200). Prediction equations included demographics (age, sex), comorbidities, lifestyle factors, diet, and mood. Models with and without baseline eGFR were derived and externally validated in the UK Biobank (n=15,522). New-onset CKD (eGFR <60 ml/min per 1.73 m2) with ≤8 years of follow-up was the primary outcome. Among Ontario individuals (mean age, 55 years; 58% women; baseline eGFR, 95 (SD 15) ml/min per 1.73 m2), new-onset CKD occurred in 1981 (9%) during a median follow-up time of 4.2 years. The final models included lifestyle factors (smoking, alcohol, physical activity) and comorbid illnesses (diabetes, hypertension, cancer). The model was discriminating in individuals with and without a baseline eGFR measure (5-year c-statistic with baseline eGFR: 83.5, 95% confidence interval [CI], 82.2 to 84.9; without: 81.0, 95% CI, 79.8 to 82.4) and well calibrated. In external validation, the 5-year c-statistic was 78.1 (95% CI, 74.2 to 82.0) and 66.0 (95% CI, 61.6 to 70.4), with and without baseline eGFR, respectively, and maintained calibration. Self-reported lifestyle and health behavior information from health surveys may aid in predicting incident CKD. This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast.aspx?p=CJASN&e=2023_01_10_CJN05650522.mp3.

Sections du résumé

BACKGROUND
Prediction tools that incorporate self-reported health information could increase CKD awareness, identify modifiable lifestyle risk factors, and prevent disease. We developed and validated a survey-based prediction equation to identify individuals at risk for incident CKD (eGFR <60 ml/min per 1.73 m2), with and without a baseline eGFR.
METHODS
A cohort of adults with an eGFR ≥70 ml/min per 1.73 m2 from Ontario, Canada, who completed a comprehensive general population health survey between 2000 and 2015 were included (n=22,200). Prediction equations included demographics (age, sex), comorbidities, lifestyle factors, diet, and mood. Models with and without baseline eGFR were derived and externally validated in the UK Biobank (n=15,522). New-onset CKD (eGFR <60 ml/min per 1.73 m2) with ≤8 years of follow-up was the primary outcome.
RESULTS
Among Ontario individuals (mean age, 55 years; 58% women; baseline eGFR, 95 (SD 15) ml/min per 1.73 m2), new-onset CKD occurred in 1981 (9%) during a median follow-up time of 4.2 years. The final models included lifestyle factors (smoking, alcohol, physical activity) and comorbid illnesses (diabetes, hypertension, cancer). The model was discriminating in individuals with and without a baseline eGFR measure (5-year c-statistic with baseline eGFR: 83.5, 95% confidence interval [CI], 82.2 to 84.9; without: 81.0, 95% CI, 79.8 to 82.4) and well calibrated. In external validation, the 5-year c-statistic was 78.1 (95% CI, 74.2 to 82.0) and 66.0 (95% CI, 61.6 to 70.4), with and without baseline eGFR, respectively, and maintained calibration.
CONCLUSIONS
Self-reported lifestyle and health behavior information from health surveys may aid in predicting incident CKD.
PODCAST
This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast.aspx?p=CJASN&e=2023_01_10_CJN05650522.mp3.

Identifiants

pubmed: 36720027
doi: 10.2215/CJN.0000000000000035
pii: 01277230-202301000-00008
pmc: PMC10101574
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

28-35

Informations de copyright

Copyright © 2023 by the American Society of Nephrology.

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Auteurs

Ariana J Noel (AJ)

Department of Medicine, University of Ottawa, Ottawa, Canada.

Anan Badder Eddeen (AB)

Institute for Clinical Evaluative Sciences, Ontario, Canada.

Douglas G Manuel (DG)

Department of Medicine, University of Ottawa, Ottawa, Canada.
Institute for Clinical Evaluative Sciences, Ontario, Canada.
The Ottawa Hospital Research Institute, Ottawa, Canada.
Department of Family Medicine, University of Ottawa, Ottawa, Canada.
Statistics Canada, Ottawa, Canada.
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Division of Nephrology, Seven Oaks Hospital, Winnipeg, Canada.
Division of Nephrology, the Ottawa Hospital, Ottawa, Canada.

Emily Rhodes (E)

The Ottawa Hospital Research Institute, Ottawa, Canada.

Navdeep Tangri (N)

Division of Nephrology, Seven Oaks Hospital, Winnipeg, Canada.

Gregory L Hundemer (GL)

Department of Medicine, University of Ottawa, Ottawa, Canada.
The Ottawa Hospital Research Institute, Ottawa, Canada.
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Division of Nephrology, the Ottawa Hospital, Ottawa, Canada.

Peter Tanuseputro (P)

Institute for Clinical Evaluative Sciences, Ontario, Canada.
The Ottawa Hospital Research Institute, Ottawa, Canada.
Department of Family Medicine, University of Ottawa, Ottawa, Canada.
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.

Gregory A Knoll (GA)

Department of Medicine, University of Ottawa, Ottawa, Canada.
Institute for Clinical Evaluative Sciences, Ontario, Canada.
The Ottawa Hospital Research Institute, Ottawa, Canada.
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Division of Nephrology, the Ottawa Hospital, Ottawa, Canada.

Ranjeeta Mallick (R)

The Ottawa Hospital Research Institute, Ottawa, Canada.

Manish M Sood (MM)

Department of Medicine, University of Ottawa, Ottawa, Canada.
The Ottawa Hospital Research Institute, Ottawa, Canada.
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada.
Division of Nephrology, the Ottawa Hospital, Ottawa, Canada.

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