Objective:Screening factors that might influence rheumatoid arthritis (RA) complicating interstitial lung diseases (ILD) by constructing and validating a model for early diagnostic.Methods:The study subjects were composed of 712 RA patients in the Department of Rheumatology and Immunology of the Second Hospital of Shanxi Medical University during December 2019 to October 2022. Fifty-two variables such as their demographic data, clinical symptoms, and laboratory indexes were collected. Patients were categorized into RA-only group and RA-ILD group with or without the occurrence of ILD disease. After data preprocessing, subjects were randomly assigned to the modeling and validation groups in a 7:3 ratio.Univariate analysis comparing baseline characteristics of the two groups of patients. Feature selection was performed using LASSO and SVM-RFE regression algorithms.Screening indicators were analyzed by logistic regression and the results were used to develop a nomograms model for the early diagnosis of RA complicating interstitial lung disease; and the modeling group was evaluated for its performance for internal assessment of the model and internal validation using data from the validation group.Results:A total of 712 subjects participated in the study, of which 498 in the modeling group and 214 in the validation group. Univariate analysis showed that the differences between the two groups were statistically significant ( P<0.05) in 18 characteristic indexes, including male, gender, age, smoking history, drinking history, number of swollen joints, number of painful joints, use of prednisone, WBC, ESR, CRP, IL-2, IL-10, IL-17, TNF-α, INF-γ, AFA family, APF, and serum albumin. The LASSO algorithm identified 13 risk variables for RA-ILD, the SVM-RFE algorithm identified 12 variables for RA-ILD, and the intersecting risk variables were male, age, history of alcohol consumption, number of painful joints, prednisone acetate, IL-2, AFA family, TNF-α, serum albumin, and IL-10. The results of multifactorial logistic regression analysis confirmed that the differences between males [ OR(95% CI)=3.61(2.11, 6.18)], gender, age [ OR(95% CI)=1.05(1.03, 1.08)], number of painful joints [ OR(95% CI)=1.03(1.01, 1.06)], IL-2 [ OR(95% CI)=0.91 (0.84, 0.99)], and TNF-α[ OR (95% CI)=1.06 (1.02, 1.10)] were statistically significant ( P<0.05) and were independently influences on ILD complicated by RA. The modeling and validation groups that were used to construct early diagnostic Nomograms had high calibration curve accuracies, and the model had a high diagnostic power, which was mainly demonstrated by the receiver operating characteristic (ROC) area under the curve (AUC) and decision curve analysis(DCA), the model modeling group had an AUC of 0.76 (95% CI=0.71, 0.81), with net benefit rates of 3%~82% and 93%~99%, whereas the model validation group had an AUC of 0.71 (95% CI=0.64, 0.79), with net benefit rates of 5%~11%, 14%~60% and 85%~89%. Conclusion:Male, gender, age, number of painful joints, IL-2, and TNF-α are independent factors for RA complicated with ILD, and the Nomogram model constructed has good performance in early diagnosis of the disease.

Objective:To compare the efficacy and safety of different dosages of new drugs in the treatment of PsA by using network meta-analysis.Methods:Three medical databases (PubMed, Web of Science, Cochrane Library) were searched for the studies that compared the efficacy and safety of 4 new drugs (secukinumab, ixekizumab, apremilast, tofacitinib) with different dosages in the treatment of PsA. Data from included studies were analyzed by Stata 15.0.Results:A total of 16 RCTs were included. The results of the network meta-analysis showed that: (1) Among the overall patients, in terms of ACR20 response rate, the larger the surface under the cumulative ranking (SUCRA), the more effective it is. Secukinumab 300 mg Q4W(96.1%) had the best efficacy, followed by ixekizumab 80 mg Q4W(79.0%), ixekizumab 80 mg Q2W(75.1%), secukinumab 150 mg Q4W(73.2%), apremilast 30 mg BID(50.6%), apremilast 20 mg BID(38.6%), tofacitinib 5 mg BID(18.1%), tofacitinib 10 mg BID(17.7%) and placebo(2.0%). (2) In terms of PASI75 response rate, the larger the area under the SUCRA curve, the more effective it is. Ixekizumab 80 mg Q4W(96.1%) had the best efficacy, followed by ixekizumab 80 mg Q2W(88.7%), secukinumab 300 mg Q4W(75.6%), secukinumab 150 mg Q4W(63.3%), apremilast 30 mg BID(44.5%), apremilast 20 mg BID(38.4%), tofacitinib 10 mg BID(30.0%), tofacitinib 5 mg BID(12.5%) and placebo(1.0%). (3) Among the overall patients, in terms of safety, the smaller the area under the SUCRA curve, the higher the safety it is. Secukinumab 300 mg Q4W (17.3%) has the best safety. (4) The results of subgroup analysis showed that in terms of ACR20 response rate, ixekizumab 80 mg Q2W(85.3%) had the best efficacy in bDMARDs-na?ve patients, while in bDMARDs-IR patients, secukinumab 300 mg Q4W(83.9%) had the best efficacy.Conclusion:Among all patients, secukinumab 300 mg Q4W is the best in terms of ACR20 response rate and safety, but ixekizumab 80 mg Q4W is more effective in improving PsA lesions comparing yo other drugs.