A Markov Multi-State model of lupus nephritis urine biomarker panel dynamics in children: Predicting changes in disease activity.

Adolescent Biomarkers / urine Ceruloplasmin / urine Child Female Humans Lupus Nephritis / diagnosis Male Markov Chains Orosomucoid / urine
Juvenile systemic lupus erythematosus Lupus Nephritis Markov Multi-State model Urine biomarker panel

Journal

Clinical immunology (Orlando, Fla.)
ISSN: 1521-7035
Titre abrégé: Clin Immunol
Pays: United States
ID NLM: 100883537

Informations de publication

Date de publication:
01 2019
Historique:
received: 06 07 2018
revised: 28 09 2018
accepted: 31 10 2018
pubmed: 6 11 2018
medline: 29 10 2019
entrez: 5 11 2018
Statut: ppublish

Résumé

A urine 'biomarker panel' comprising alpha-1-acid-glycoprotein, ceruloplasmin, transferrin and lipocalin-like-prostaglandin-D synthase performs to an 'excellent' level for lupus nephritis identification in children cross-sectionally. The aim of this study was to assess if this biomarker panel predicts lupus nephritis flare/remission longitudinally. The novel urinary biomarker panel was quantified by enzyme linked immunoabsorbant assay in participants of the United Kingdom Juvenile Systemic Lupus Erythematosus (UK JSLE) Cohort Study, the Einstein Lupus Cohort, and the South African Paediatric Lupus Cohort. Monocyte chemoattractant protein-1 and vascular cell adhesion molecule-1 were also quantified in view of evidence from other longitudinal studies. Serial urine samples were collected during routine care with detailed clinical and demographic data. A Markov Multi-State model of state transitions was fitted, with predictive clinical/biomarker factors assessed by a corrected Akaike Information Criterion (AICc) score (the better the model, the lower the AICc score). The study included 184 longitudinal observations from 80 patients. The homogeneous multi-state Markov model of lupus nephritis activity AICc score was 147.85. Alpha-1-acid-glycoprotein and ceruloplasmin were identified to be the best predictive factors, reducing the AICc score to 139.81 and 141.40 respectively. Ceruloplasmin was associated with the active-to-inactive transition (hazard ratio 0.60 (95% confidence interval [0.39, 0.93])), and alpha-1-acid-glycoprotein with the inactive-to-active transition (hazard ratio 1.49 (95% confidence interval [1.10, 2.02])). Inputting individual alpha-1-acid-glycoprotein/ceruloplasmin values provides 3, 6 and 12 months probabilities of state transition. Alpha-1-acid-glycoprotein was predictive of active lupus nephritis flare, whereas ceruloplasmin was predictive of remission. The Markov state-space model warrants testing in a prospective clinical trial of lupus nephritis biomarker led monitoring.

Sections du résumé

BACKGROUND
A urine 'biomarker panel' comprising alpha-1-acid-glycoprotein, ceruloplasmin, transferrin and lipocalin-like-prostaglandin-D synthase performs to an 'excellent' level for lupus nephritis identification in children cross-sectionally. The aim of this study was to assess if this biomarker panel predicts lupus nephritis flare/remission longitudinally.
METHODS
The novel urinary biomarker panel was quantified by enzyme linked immunoabsorbant assay in participants of the United Kingdom Juvenile Systemic Lupus Erythematosus (UK JSLE) Cohort Study, the Einstein Lupus Cohort, and the South African Paediatric Lupus Cohort. Monocyte chemoattractant protein-1 and vascular cell adhesion molecule-1 were also quantified in view of evidence from other longitudinal studies. Serial urine samples were collected during routine care with detailed clinical and demographic data. A Markov Multi-State model of state transitions was fitted, with predictive clinical/biomarker factors assessed by a corrected Akaike Information Criterion (AICc) score (the better the model, the lower the AICc score).
RESULTS
The study included 184 longitudinal observations from 80 patients. The homogeneous multi-state Markov model of lupus nephritis activity AICc score was 147.85. Alpha-1-acid-glycoprotein and ceruloplasmin were identified to be the best predictive factors, reducing the AICc score to 139.81 and 141.40 respectively. Ceruloplasmin was associated with the active-to-inactive transition (hazard ratio 0.60 (95% confidence interval [0.39, 0.93])), and alpha-1-acid-glycoprotein with the inactive-to-active transition (hazard ratio 1.49 (95% confidence interval [1.10, 2.02])). Inputting individual alpha-1-acid-glycoprotein/ceruloplasmin values provides 3, 6 and 12 months probabilities of state transition.
CONCLUSIONS
Alpha-1-acid-glycoprotein was predictive of active lupus nephritis flare, whereas ceruloplasmin was predictive of remission. The Markov state-space model warrants testing in a prospective clinical trial of lupus nephritis biomarker led monitoring.

Identifiants

DOI: 10.1016/j.clim.2018.10.021 PMID: 30391651
pubmed: 30391651
pii: S1521-6616(18)30425-X
doi: 10.1016/j.clim.2018.10.021
pii:
doi:

Substances chimiques

Biomarkers 0
Orosomucoid 0
Ceruloplasmin EC 1.16.3.1

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

71-78

Subventions

Organisme : Medical Research Council
ID : JXR11948
Pays : United Kingdom
Organisme : FIC NIH HHS
ID : R25 TW009337
Pays : United States
Organisme : NCI NIH HHS
ID : U19 CA179564
Pays : United States
Organisme : NCATS NIH HHS
ID : UH2 TR000933
Pays : United States
Organisme : NCATS NIH HHS
ID : UH3 TR000933
Pays : United States
Organisme : NIAMS NIH HHS
ID : UH2 AR067689
Pays : United States
Organisme : Arthritis Research UK
Pays : United Kingdom
Organisme : Department of Health
Pays : United Kingdom

Informations de copyright

Copyright © 2018 Elsevier Inc. All rights reserved.

Auteurs

E M D Smith (EMD)

Department of Women's & Children's Health, University of Liverpool, Liverpool, UK; Department of Paediatric Rheumatology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK. Electronic address: esmith8@liverpool.ac.uk.

A Eleuteri (A)

Medical Physics and Clinical Engineering, and Department of Physics, University of Liverpool, Liverpool, UK. Electronic address: antonio.eleuteri@liv.ac.uk.

B Goilav (B)

Department of Paediatric Nephrology, Albert Einstein College of Medicine, New York, USA. Electronic address: bgoilav@montefiore.org.

L Lewandowski (L)

National Institute of Health, Maryland, USA. Electronic address: laura.lewandowski@nih.gov.

A Phuti (A)

Paediatric Rheumatology, University of Cape Town, Cape Town, South Africa. Electronic address: trubinst@montefiore.org.

T Rubinstein (T)

Department of Paediatric Rheumatology, Albert Einstein College of Medicine, New York, USA. Electronic address: trubinst@montefiore.org.

D Wahezi (D)

Department of Paediatric Rheumatology, Albert Einstein College of Medicine, New York, USA. Electronic address: DWAHEZI@montefiore.org.

C A Jones (CA)

Department of Paediatric Nephrology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK. Electronic address: Caroline.Jones@alderhey.nhs.uk.

S D Marks (SD)

Paediatric Nephrology, Great Ormond Street Hospital, London, UK. Electronic address: Stephen.Marks@gosh.nhs.uk.

R Corkhill (R)

Department of Women's & Children's Health, University of Liverpool, Liverpool, UK. Electronic address: rachel.corkhill@liverpool.ac.uk.

C Pilkington (C)

Paediatric Rheumatology, Great Ormond Street Hospital, London, UK. Electronic address: Clarissa.Pilkington@gosh.nhs.uk.

K Tullus (K)

Paediatric Nephrology, Great Ormond Street Hospital, London, UK. Electronic address: Kjell.Tullus@gosh.nhs.uk.

C Putterman (C)

Department of Rheumatology, Albert Einstein College of Medicine, New York, USA. Electronic address: Chaim.Putterman@einstein.yu.edu.

C Scott (C)

Paediatric Rheumatology, University of Cape Town, Cape Town, South Africa. Electronic address: chris.scott@uct.ac.za.

A C Fisher (AC)

Medical Physics and Clinical Engineering, and Department of Physics, University of Liverpool, Liverpool, UK. Electronic address: clfs12@liverpool.ac.uk.

M W Beresford (MW)

Department of Women's & Children's Health, University of Liverpool, Liverpool, UK; Department of Paediatric Rheumatology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK. Electronic address: m.w.beresford@liverpool.ac.uk.

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Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Adolescent › A Markov Multi-State model of lupus nephritis...
questionsmedicales.fr › Facteurs biologiques › Marqueurs biologiques › A Markov Multi-State model of lupus nephritis...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Métalloprotéines › Céruloplasmine › A Markov Multi-State model of lupus nephritis...
questionsmedicales.fr › Personnes › Tranches d'âge › Enfant › A Markov Multi-State model of lupus nephritis...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › A Markov Multi-State model of lupus nephritis...
questionsmedicales.fr › Maladies du système immunitaire › Maladies auto-immunes › Lupus érythémateux disséminé › Glomérulonéphrite lupique › A Markov Multi-State model of lupus nephritis...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Processus stochastiques › Chaines de Markov › A Markov Multi-State model of lupus nephritis...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Glycoprotéines › Mucoprotéines › Orosomucoïde › A Markov Multi-State model of lupus nephritis...