Development and validation of a prognostic nomogram for predicting mortality risk in adult rheumatoid arthritis: an analysis of NHANES 1999–2018 data DOI Creative Commons
Xiao Chen,

Haibo Gong,

Jing Chen

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: April 17, 2025

This study aims to identify potential independent risk factors for rheumatoid arthritis (RA)- related mortality and develop a nomogram model predict individualized risk. included 310 RA patients from the National Health Nutrition Examination Survey (NHANES) during 1999 - 2018. We applied LASSO, univariate, multivariate logistic regression analyses determine in training cohort construct model. Calibration plots evaluated nomogram's accuracy. Finally, we established clinical utility through DCA performed internal validation within cohort. Of patients, 140 experienced deaths, corresponding rate of 45.16%. Within cohort, age, heart failure, systemic inflammatory response index (SIRI) emerged as predictors mortality. A model, constructed multivariable analysis, demonstrated an AUC 0. 852 (95% CI: 799 904) 904 846 963) The calibration curve revealed strong agreement between predicted actual probabilities. In both cohorts, highlighted significant net benefits predicting demonstrates SIRI's ability with good discrimination utility. gives clinicians simple tool quickly high promoting early intervention, personalized treatment, better prognosis.

Language: Английский

Development and validation of a prognostic nomogram for predicting mortality risk in adult rheumatoid arthritis: an analysis of NHANES 1999–2018 data DOI Creative Commons
Xiao Chen,

Haibo Gong,

Jing Chen

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: April 17, 2025

This study aims to identify potential independent risk factors for rheumatoid arthritis (RA)- related mortality and develop a nomogram model predict individualized risk. included 310 RA patients from the National Health Nutrition Examination Survey (NHANES) during 1999 - 2018. We applied LASSO, univariate, multivariate logistic regression analyses determine in training cohort construct model. Calibration plots evaluated nomogram's accuracy. Finally, we established clinical utility through DCA performed internal validation within cohort. Of patients, 140 experienced deaths, corresponding rate of 45.16%. Within cohort, age, heart failure, systemic inflammatory response index (SIRI) emerged as predictors mortality. A model, constructed multivariable analysis, demonstrated an AUC 0. 852 (95% CI: 799 904) 904 846 963) The calibration curve revealed strong agreement between predicted actual probabilities. In both cohorts, highlighted significant net benefits predicting demonstrates SIRI's ability with good discrimination utility. gives clinicians simple tool quickly high promoting early intervention, personalized treatment, better prognosis.

Language: Английский

Citations

0