A predictive model for progression to clinical arthritis in at-risk individuals with arthralgia based on lymphocyte subsets and ACPA

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023728%3A_____%2F24%3AN0000008" target="_blank" >RIV/00023728:_____/24:N0000008 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00023728:_____/24:N0000001 RIV/00216208:11110/24:10483668 RIV/61384399:31140/24:00060340

Výsledek na webu

<a href="https://doi.org/10.1093/rheumatology/keae383" target="_blank" >https://doi.org/10.1093/rheumatology/keae383</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/rheumatology/keae383" target="_blank" >10.1093/rheumatology/keae383</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A predictive model for progression to clinical arthritis in at-risk individuals with arthralgia based on lymphocyte subsets and ACPA

Popis výsledku v původním jazyce

The presence of ACPA significantly increases the risk of developing RA. Dysregulation of lymphocyte subpopulations was previously described in RA. Our objective was to propose the predictive model for progression to clinical arthritis based on peripheral lymphocyte subsets and ACPA in individuals who are at risk of RA. Our study included 207 at-risk individuals defined by the presence of arthralgias and either additional ACPA positivity or meeting the EULAR definition for clinically suspect arthralgia. For the construction of predictive models, 153 individuals with symptom duration ≥12 months who have not yet progressed to arthritis were included. The lymphocyte subsets were evaluated using flow cytometry and anti-CCP using ELISA. Out of all individuals with arthralgia, 41 progressed to arthritis. A logistic regression model with baseline peripheral blood lymphocyte subpopulations and ACPA as predictors was constructed. The resulting predictive model showed that high anti-CCP IgG, higher percentage of CD4+ T cells, and lower percentage of T and NK cells increased the probability of arthritis development. Moreover, the proposed classification decision tree showed that individuals having both high anti-CCP IgG and low NK cells have the highest risk of developing arthritis. We propose a predictive model based on baseline levels of lymphocyte subpopulations and ACPA to identify individuals with arthralgia with the highest risk of progression to clinical arthritis. The final model includes T cells and NK cells, which are involved in the pathogenesis of RA. This preliminary model requires further validation in larger at-risk cohorts.

Název v anglickém jazyce

A predictive model for progression to clinical arthritis in at-risk individuals with arthralgia based on lymphocyte subsets and ACPA

Popis výsledku anglicky

The presence of ACPA significantly increases the risk of developing RA. Dysregulation of lymphocyte subpopulations was previously described in RA. Our objective was to propose the predictive model for progression to clinical arthritis based on peripheral lymphocyte subsets and ACPA in individuals who are at risk of RA. Our study included 207 at-risk individuals defined by the presence of arthralgias and either additional ACPA positivity or meeting the EULAR definition for clinically suspect arthralgia. For the construction of predictive models, 153 individuals with symptom duration ≥12 months who have not yet progressed to arthritis were included. The lymphocyte subsets were evaluated using flow cytometry and anti-CCP using ELISA. Out of all individuals with arthralgia, 41 progressed to arthritis. A logistic regression model with baseline peripheral blood lymphocyte subpopulations and ACPA as predictors was constructed. The resulting predictive model showed that high anti-CCP IgG, higher percentage of CD4+ T cells, and lower percentage of T and NK cells increased the probability of arthritis development. Moreover, the proposed classification decision tree showed that individuals having both high anti-CCP IgG and low NK cells have the highest risk of developing arthritis. We propose a predictive model based on baseline levels of lymphocyte subpopulations and ACPA to identify individuals with arthralgia with the highest risk of progression to clinical arthritis. The final model includes T cells and NK cells, which are involved in the pathogenesis of RA. This preliminary model requires further validation in larger at-risk cohorts.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30226 - Rheumatology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Rheumatology (Oxford).

ISSN

1462-0324

e-ISSN

1462-0332

Svazek periodika

63

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

9

Strana od-do

3155-3163

Kód UT WoS článku

001289018000001

EID výsledku v databázi Scopus

2-s2.0-85204479223