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Chinese Journal of Joint Surgery(Electronic Edition) ›› 2024, Vol. 18 ›› Issue (05): 596-603. doi: 10.3877/ cma.j.issn.1674-134X.2024.05.006

• CLINICAL RESEARCHES • Previous Articles     Next Articles

Nomograph model for predicting risk of osteoporoticpatients with rheumatoid arthritis

Yanting Pu1,(), Cuixian Wu1, Yumei Lan1   

  1. 1.Jiangyou Second People's Hospital, Jiangyou 621701, China
  • Received:2023-12-19 Online:2024-10-01 Published:2024-11-28
  • Contact: Yanting Pu

Abstract:

Objective

To explore the risk factors of osteoporosis in patients with rheumatoid arthritis(RA) and build a prediction model.

Methods

A total of 520 RA patients admitted to the Second People's Hospital of Jiangyou City from January 2021 to June 2022 were selected as the study objects. All the patients underwent bone mineral density examination and volunteered to participate in the study. Exclusion criteria:renal or thyroid dysfunction, malignant tumors, endocrine diseases, osteoarthritis, pregnancy. The patients were randomly divided into modeling group (n=364) and verification group (n=156) according to the ratio of 7∶3. According to the occurrence of osteoporosis, the patients were divided into developing group and nondeveloping group. Clinical data such as age, gender, medical history, smoking, drinking, course of disease and laboratory indicators were collected. Univariate and multivariate logistic regression were used to analyze the risk factors affecting the occurrence of osteoporosis in RA patients. The calibration curve and Hosmer-LemeshowH-L) test were used to evaluate the calibration degree of the calibration model, and the receiver operating characteristic (ROC) curve was drawn to verify the differentiation of the model.

Results

The incidence of osteoporosis in 520 patients was 44.8% (233/520). The incidence of osteoporosis in the modeling group was 45.1% (164/364). The incidence of osteoporosis in the verification group was 44.2% (69/156). The results of multivariate logistic regression analysis showed that calcium intake[odds ratio (OR)=2.439], history of glucocorticoid use (OR=2.552), age (OR=1.151), body mass index (BMI) (OR=0.882), duration of disease(OR=1.071), erythrocyte sedimentation rate (ESR) level (OR=1.057), disease activity in 28 joints DAS28 score(OR=2.386) was an independent factor for the occurrence of osteoporosis (P<0.05). Based on the above risk factors, a nomogram model was established to predict the risk of osteoporosis in RA patients, and internal and external verification was carried out. The results showed that the calibration curve and ideal curve fit well in both the modeling group and the verification group, indicating that the risk of osteoporosis predicted by the model was basically consistent with the actual risk. The areas under ROC curve were 0.907[ 95% confidence interval (CI)(0.876, 0.939)]and 0.899[ 95%CI (0.8850, 0.948)]respectively, indicating that the prediction model had good prediction ability.

Conclusions

The factors influencing the development of osteoporosis in patients with RA include age, BMI, course of disease, history of glucocorticoid use, calcium intake level, ESR level, and DAS28 score. The prediction model based on the above risk factors can effectively predict the risk of osteoporosis in RA patients, which is helpful for clinicians to identify RA patients with early osteoporosis.

Key words: Rheumatoid arthritis; Osteoporosis; Nomograms

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