A NEWLY developed nomogram model accurately predicts arthritis risk using easily accessible health indicators, offering potential for early intervention. Arthritis is a highly prevalent musculoskeletal condition affecting over 300 million people worldwide, leading to pain, disability, and reduced quality of life. Despite its widespread impact, there are currently no effective treatments to halt its progression, making early identification of at-risk individuals crucial for prevention and management. A study aimed to create and validate a predictive model for arthritis risk using commonly available health data, helping to improve early diagnosis and targeted interventions.
Data were collected from 3,660 participants in the 2021–2023 National Health and Nutrition Examination Survey. The model was developed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression analysis, incorporating nine independent predictors: age, sex, family poverty-income ratio, race, diabetes status, vitamin D levels, systemic immunity-inflammation index (SII), and waist-to-height ratio (WHtR). Model validation demonstrated strong predictive performance. Notably, both SII and WHtR were identified as key variables in arthritis risk assessment. The model presents its findings as an easy-to-use nomogram chart, which allows individuals and healthcare professionals to estimate arthritis risk based on these factors.
The results highlight the potential of this predictive model in clinical practice, as all included variables are routinely collected during standard health assessments. By identifying high-risk individuals early, targeted interventions such as reducing waist circumference through physical activity or monitoring inflammation markers can be implemented to lower arthritis risk. The ability to predict arthritis risk using a simple, cost-effective model could reduce the burden on healthcare systems and improve patient outcomes by enabling early preventative measures.
Jenna Lorge, EMJ
Reference
Lin Y et al. Development and validation of a nomogram for arthritis: a cross-sectional study based on the NHANES. Sci Rep. 2024;DOI:10.1038/s41598-025-92014-8.
