Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Objective:To describe the clinical characteristics of a possible rare syndrome, the granulomatous mastitis(GM), erythema nodosum and arthritis syndrome (GMENA syndrome), by retrospective analyzing patients with both GM and erythema nodosum, with or without arthritis, and provide clinical evidence for further researchstudy.Methods:This study analyzed the demographic general information, clinical manifestations, laboratory tests results, medications, operations, and the first visits of cases collected from the Affiliated Hospital of Qingdao University between January 2015 and February 2024. All patients were diagnosed with both GM and erythema nodosum, with or without arthritis. The frequency, means and standard deviation were used to perform descriptive analysis.Results:Among the 22 cases, all of the GM were unilateral, and nodular erythema mainly appeared in both lower limbs 17 (77%). Eight (67%) patients had arthritis. Sixteen cases (80%) were reported forwith elevated white blood cells count, and 16 (84%) with elevated C-reactive protein level, 12(86%) patients were with elevated erythrocyte sedimentation rate. Two cases were associated with hyperprolactinemia. In the bacterial tests of the breast abscess, C orynebacterium kroppenstedtii, and one Staphylococcus epidermidis were detected in 1 case respectively. The department of breast surgery was the most frequently first visit (86%) medical service, and 14 cases (64%) visited the department of rheumatology and immunology. Four cases (18%) underwent abscess incision and drainage after ineffective medication and none of them were treated with glucocorticoids. Five cases with glucocorticoids and followed-up by the department of rheumatology and immunology were not operated and four in of them without recurrenc. Conclusion:GMENA syndrome may be a syndrome characterized by high inflammatory activity, cytokine activation, and often involves the breast, skin, and joint. The pathogenesis and treatment of this syndrome need to be investigated further.

Objective:This study aimed to construct a prediction model for diagnosis of proliferative lupus nephritis based on a machine learning algorithm. Additionally, a user-friendly platform was developed to propose a non-invasive method to assist the pathologic classification of lupus nephritis.Methods:A retrospective analysis was conducted on clinical and pathological data of lupus nephritis patients confirmed by renal biopsy at Zhengzhou University People′s Hospital from January 2017 to August 2023. The study population was randomly divided into training and testing sets in a 7∶3 ratio. Utilizing six machine learning algorithms, classification models were developed. The predictive performance of each model was assessed using metrics such as accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). The optimal model, once identified, was deployed as a web-based calculator for convenient model application. SPSS 25.0 and R 4.2.2 were used to analyze the data.Results:The study included a total of 212 patients, with 138 cases with proliferative lupus nephritis and 74 cases with non-proliferative lupus nephritis. The AUC values for the six models, namely logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting, and light gradient boosting machine, were 0.79, 0.62, 0.79, 0.88, 0.81, and 0.77, respectively; the accuracy rates were 82.54%, 65.08%, 74.60%, 85.71%, 69.84%, 71.43%, respectively. Among them, the support vector machine model demonstrated the optimal performance. This model had deployed as a web-based calculator. Based on feature importance scores, the top 10 influencing factors were identified, including anti URNP antibody, immunoglobulin G, serum globulin, estimated glomerular filtration rate, anti Smith antibody, BMI index, anti dsDNA antibody, uric acid, anti-Rib.p antibody, and gender.Conclusion:A prediction model based on machine learning algorithms was successfully established, and a web calculator was developed to offer a simple and non-invasive method for diagnosing proliferative lupus nephritis. This can assist clinicians in evaluating the risk-benefit ratio of kidney biopsy in patients with lupus nephritis.

Objective:To explore the relationship between gut microbiota and giant cell arteritis (GCA), and to identifyits potential therapeutic strategies.Methods:Gut microbiota data were obtained from the MiBioGen consortium genome-wide association study (GWAS), and GCA data were obtained from the FinnGen consortium public GWAS. Causal associations between gut microbiota and GCA were assessed using two-sample Mendelian randomization (MR) analyses, including inverse-variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods. Heterogeneity and horizontal pleiotropy were evaluated, and false positive results were excluded by using the Benjamini-Hochberg (BH) method of multiple hypothesis testing. All analyses were completed using the TwoSampleMR and MRPRESSO software packages (version 4.3.0) in R language. The analysis of the intestinal flora data, followed by conducting network pharmacology analysis were carried out by Cytoscape 3.9.1 and perform molecular docking verification was performed with AutoDock Vina software.Results:IVW simulations revealed 13 gut microbiota taxa were associated with GCA, of which Lachnospiraceae was significantly negatively associated with GCA risk[nSNP=16, OR(95% CI)=0.32(0.16, 0.63), β=-1.15, Se=0.35, P=0.001, FDR<0.05], and there was no heterogeneity (Cochran′s Q test, Q=13.42, P=0.490) as well as horizontal pleiotropy ( P=0.370). Further literature search and computer simulation docking analysis showed that genistein binds to MMP2 with a binding energy of -43.1 kJ/mol. Conclusion:Lachnospiraceae in the gut microbiota was is negatively associated with GCA, and genistein may be able to regulate the abundance of Lachnospiraceae through the MMP2 target to treat GCA, providing a new therapeutic approach for giant cell arteritis.

Objective:To analyze the influencing factors of mood state of common rheumatic (rheumatoid arthritis; systemic lupus erythematosus; ankylosing spondylitis) patients and find out the common characteristics of patients with negative emotions, so as to identify and treat rheumatic patients with anxiety and depression in clinical practice.Methods:A total of 205 patients with rheumatism (83 with rheumatoid arthritis, 74 with systemic lupus erythematosus, 48 with ankylosing spondylitis) admitted to the Shandong Provincial Hospital Affiliated to Shandong University from April to May 2023 were included. The general condition and POMS of patients were collected. All patients were divided into 3 groups of low-TMD/ middle-TMD/ high-TMD(TMD≤90 scores; 90 scores105 scores). The χ2 test was used for categorical variables, and the continuous variables were tested for normal distribution. If they followed a normal distribution, the independent sample t test (for homogeneous variance) or the Welch′s t test (for unequal variance) was used for comparison between the two groups, and one-way analysis of variance was used for comparison between multiple groups; if they did not follow a normal distribution, the Kruskal-Wallis H test was used for comparison between groups. Patients with TMD>90 scores were defined as the negative emotion group. Gender, age, education level, economic income status, and TMD were included in the two-step cluster analysis (TCA) to obtain three cluster groups and analyze the differences between the groups. Logistic regression was used to analyze the risk factors. Results:The study found that patients with rheumatic diseases with low serum albumin levels ( F=6.26, P=0.003), low education level ( χ2=8.36, P=0.015), low economic level ( χ2=15.59, P<0.001), short disease course ( H=28.01, P<0.001), and high disease activity ( χ2=56.93, P<0.001) had higher TMD scores, which was not related to the type of disease ( χ2=4.81, P=0.090). The negative mood group had a higher proportion of females (57.6% vs. 73.4%, χ2=5.16, P=0.023), a shorter course of disease [24(12, 48) months vs. 48(24, 93) months, Z=13.58, P<0.001], and a lower serum albumin [(42.2±4.0) g/L vs. (44.0±3.4)g/L, t=-14.09, P=0.002], low level of education ( χ2=9.04, P=0.029), low level of income ( χ2=10.29, P=0.036), high disease activity ( χ2=61.91, P<0.001). The results of cluster analysis indicated that the above factors were significantly different among the three cluster groups except the course of disease. It is noteworthy that age ( F=19.25, P<0.001) and serum albumin ( F=5.64, P=0.004) had the lowest value and the highest TMD score ( F=5.64, P<0.001). Regression analysis showed that gender, disease course and disease activity were related factors to the occurrence of negative emotions, and high disease activity was a risk factor [ OR(95% CI) =26.58(4.53, 156.09), P<0.001]. Men [ OR(95% CI)=0.20 (0.08, 0.50), P=0.001) and the course of [ OR(95% CI)=0.99 (0.98, 1.00), P=0.007) as the protective factors. Conclusion:Male, serum albumin level, education level, income level, disease course and disease activity were the main factors affecting the mood state of patients with rheumatism, in which high disease activity was the risk factor, male and long disease course were the protective factors.

Objective:The clinicalpathological features of TAFRO syndrome were analyzed to clarify the similarities and differences between TAFRO syndrome and autoimmune diseases and to establish differential diagnosis.Methods:Six patients diagnosed with TAFRO syndrome in Shanxi Bethune Hospital from January 2014 to March 2022 were collected. The clinical, examination, pathology and treatment of TAFRO syndrome were analyzed and compared with autoimmune diseases, especially systemic lupus erythematosus and Sj?gren′s syndrome.Results:Among the 6 patients, 4 were males and 2 were females, with an average age of (57.5 ±9.8) years. All the 6 patients had fever, edema (including chest and abdominal effusion and systemic edema), thrombocytopenia (3 main criteria) and more than 2 secondary criteria.ESR and CRP were significantly elevated in 6 patients. There were 1 case of elevated IgA and IgG (IgA 4.10 g/L, IgG19.05 g/L), 1 case of elevated igg (IgG 19.33 g/L), 3 cases of normal and 1 case of undetected. Serum IgG4 was negative in 4 cases and undetected in 2 cases. Autoantibodies: 4 cases were ANA positive, including 1 case with anti-SSA/Ro52(+), anti-SSA/Ro60(+), anti-SSB (+), 1 case with anti-SSA /Ro60(+), and 2 untested. Bone marrow cytological examination was performed in 6 cases, all of which showed active hyperplasia, 2 cases showed elevated megakaryocytes, and 1 case was accompanied by interstitial fibrosis. Pathological examination of lymph nodes: 5 cases were consistent with Castleman′s disease, and 1 case was suggestive of reactive hyperplasia of lymph nodes. Conclusion:Although the diagnostic criteria of TAFRO syndrome should exclude autoimmune diseases, TAFRO syndrome and autoimmune diseases can coexist, and the connective tissue disease complicated with TAFRO syndrome has its specific clinical characteristics and treatment plan, which needs to be identified clinically.

Objective:To detect the expression of autophagy-related genes (ATGs) involved in the late stage of autophagy in peripheral blood mononuclear cells (PBMCs) of patients with ankylosing spondylitis (AS), analyze the difference and explore its possible clinical significance.Methods:① Peripheral blood specimens and clinical data were collected from 90 AS patients (AS group) who attended the outpatient clinic of the Department of Rheumatology and Immunology of the Affiliated Hospital of North Sichuan Medical College from March 2022 to August 2023, among which 30 patients were treated with secukinumab monoclonal antibody for 24 weeks (the treatment group), and clinical data and peripheral blood specimens from 45 healthy individuals (the HC group) who had medical checkups in the Affiliated Hospital of Chuanbei Medical College during the same period were used as the control group. As the control group, the mRNA expression levels of six ATGs (ATG5, ATG7, LC3-Ⅱ, ATG4B, ATG2A, ATG10) involved in the late autophagy stage were detected in PBMCs of peripheral blood specimens by RT-qPCR, and were compared among different groups, and the measured data conformed to the normal distribution were analyzed using the paired t-test, and the abnormal distribution date were analyzed using the Wilcoxon signed-rank test. Wilcoxon signed-rank test was used for measurement data, and Spearman correlation analysis was used for correlation analysis. ② Receiver operating curve (ROC) was used to verify the difference in the expression of ATGs in the late stage of autophagy between AS group and HC group to evaluate its value in the diagnosis of AS and the inflammatory state of the disease. Results:① Compared with the HC group, ATG2A [2.00(1.10, 2.70)×10 -3, 7.50(4.60, 10.0)×10 -3, Z=-6.67, P<0.001], ATG5 [3.60 (2.30, 5.30)×10 -3, 7.20(5.50, 9.20)×10 -3, Z=-3.63, P=0.001], LC3Ⅱ[25.70(8.50, 35.00)×10 -3, 52.20(45.00, 69.10)×10 -3, Z=-5.87, P<0.001] and ATG7[5.50(3.20, 8.10)×10 -3, 8.30(5.20, 9.80)×10 -3, Z=-2.38, P=0.017] the mRNA expressions were significantly decreased in the AS group. ②ATG5 mRNA expression was negatively correlated with platelet count ( r=-0.35, P=0.008), LC3-Ⅱ was negatively correlated with estimated glomerular filtration rate ( r=-0.33, P=0.017), ATG7 was positively correlated with absolute basophil count ( r=0.33, P=0.011),ATG10 was negatively correlated with estimated glomerular filtration rate and C-reactive protein (CRP) was negatively correlated ( r=-0.30, P=0.032). ③ The area under the ROC curve (AUC) of ATG2A mRNA expression level for predicting AS was 0.910, and the sensitivity and specificity were 94.6% and 83.8% respectively. ④ After 24 weeks of treatment with secukinumab, the mRNA expression levels of ATG2A[2.00(1.20, 2.90)×10 -3, 4.90(0.10, 7.40)×10 -3, Z=-3.75, P<0.001] and LC3-Ⅱ[2.00(1.20, 2.90)×10 -3, 4.90(0.10, 7.40)×10 -3, Z=-3.75, P<0.001]were elevated in the AS patients. Conclusion:Late autophagy-related genes ATG2A, ATG5, LC3II, ATG7 may be involved in AS development.The AUC of ATG2A in AS is 0.91, suggesting that ATG2a is expected to be a biological indicator for early diagnosis of AS. Secukinumab may be involved in the regulation of autophagy by affecting the expression of late autophagy genes, but the specific mechanism needs to be further explored.

Objective:To investigate the immunological characteristics, particularly the alterations in peripheral blood lymphocyte subsets, including Th17 and Treg cells, cytokine dysregulation, and their clinical significance in patients with SAPHO syndrome.Methods:Fifty-three patients with SAPHO syndrome admitted to the Second Hospital of Shanxi Medical University from January 2012 to December 2023 in the department of dermatology and venereology and rheumatology with complete data were retrospectively analyzed as the study objects. At the same time, 55 healthy subjects matched by age and sex were included as healthy control group. General clinical data such as age, sex, clinical manifestations and results of laboratory tests were collected. We employed flow cytometry to assess the absolute counts of peripheral blood lymphocyte subsets and utilized cytokines detected by the flow cytometry-based multiplex protein quantification technique (CBA) to measure serum cytokine levels. We compared the differences in peripheral blood lymphocyte subsets and cytokine levels between the two groups using the rank-sum test and Spearman correlation analysis.Results:① Patients with SAPHO syndrome exhibited significantly elevated absolute counts of total B cells [240.77(180.65, 303.87)/μl vs. 165.00(132.00, 223.00)/μl, Z=-3.25, P<0.001], CD8 + T cells[504.6(381.43, 735.36)/μl vs. 429.00(357.00, 579.00)/μl, Z=-2.71, P=0.007], and CD4 + T cells 898.47(755.61, 1 019.68) vs. 637.00(544.00, 819.00), Z=-3.94, P<0.001], along with reduced NK cells[212.59(123.02, 307.72) vs. 283.00(189.00, 406.00), Z=2.95, P=0.003]. Compared with healthy controls, both Th1 [159.56(105.01, 233.09)/μl vs. 47.18(9.73, 99.12)/μl, Z=-6.52, P<0.001] and Th17 cells[17.88(12.97, 23.69)个/μl vs. 5.38(4.06, 7.42)/μl, Z=-7.11, P<0.001] and the Th17/Treg ratio[0.59(0.38, 0.84) vs. 0.17(0.13, 0.29), Z=-6.85, P<0.001] were significantly higher in the CD4 + T subset, with statistical significant difference; however, no significant differences was observed in Th2[13.09(7.98, 20.60)/μl vs. 10.22 (5.36, 15.60)/μl, Z=-1.73, P=0.084] and Treg cell [30.08(22.14, 45.16)/μl vs. 33.58(22.15, 42.13)/μl, Z=0.07, P=0.985] levels between the two groups. ② Subgroup analyses based on the presence of peripheral joint involvement and skin manifestations revealed no significant differences in lymphocyte subsets among the groups ( P>0.05). ③ No significant correlation was found between Th17, Treg cells, Th17/Treg ratio, and clinical data (ESR, CRP, skin manifestations, joint symptoms) in patients with SAPHO syndrome patients( P>0.05). ④ The serum IL-2 level in patients with SAPHO syndrome was significantly lower than in healthy controls [1.74 (1.18, 2.36)pg/ml vs. 2.73(1.76, 3.49)pg/ml, Z=4.00, P<0.001], while levels of IL-6[5.72(4.63, 7.75)pg/ml vs. 3.17(2.67, 4.06)pg/ml, Z=-7.13, P<0.001], IL-10[3.15(2.29, 4.15) pg/ml vs. 2.02(1.68, 3.13)pg/ml, Z=-0.40, P<0.001]、IL-17[8.11(4.31, 11.2)pg/ml vs. 1.47(1.15, 2.88)pg/ml, Z=-5.51, P<0.001]、IFN-γ[3.79(2.93, 5.05)pg/ml vs. 1.50(1.31, 2.09)pg/ml, Z=-7.12, P<0.001]、TNF-α[2.14 (1.56, 3.11)pg/ml vs. 0.27(0.00,1.43)pg/ml, Z=-6.84, P<0.001] were markedly elevated. ⑤Correlation analysis revealed a positive relationship between IL-17 and Th17 cells ( r=0.49, P<0.001) as well as between Th17/Treg ( r=0.37, P=0.006). Conclusion:Patients with SAPHO syndrome exhibit an increased ratio of proinflammatory Th17 cells leading to immune imbalance and disturbances in proinflammatory and anti-inflammatory cytokine levels, which may contribute to disease development. The reduction in IL-2 levels indicates a deficiency in IL-2 and decreased inhibition of Th17 cells, resulting in Th17/Treg immune imbalance, suggesting that low-dose IL-2 therapy could be beneficial to patients with SAPHO.

Objective:To investigate the occurrence of malignancy in psoriatic arthritis (PsA) patients, and further explore the factors related to malignancy.Methods:Based on the PsA prospective follow-up cohort (PKUPsA-PC) in our center, we collected the demographics and clinical characteristics of patients who visited from January 2016 to January 2024, especially those regarding the malignant tumor. The clinical characteristics of patients with and without malignant tumor were compared through the method of non-parametric tests and chi-square tests. Multivariate logistic regression was applied to analyze the factors related to malignant tumors.Results:Three hundred and eighty two patients with PsA were enrolled. The median follow-up duration was 6.0 (2.8,12.8) years. Twenty two (5.8%) patients were complicated with malignant tumors. The median age of confirmed tumors was 56.4 (45.8, 67.3) years. Among them, 14 (63.6%) patients were female, and 16 (72.7%) patients had malignant tumors after the diagnosis of PsA. As for the tumor types, solid tumors were great majority (21 cases, 95.5%), including breast cancer (7 cases), urinary system tumors (5 cases), skin cancer (3 cases), colorectal/rectal cancer (2 cases), and thyroid cancer, liver cancer, endometrial carcinoma in situ, retroperitoneal malignant tumor (1 case respectively). There was only 1 (4.5%) patient with hematological tumor (chronic lymphocytic leukemia). Compared with patients without malignant tumors, PsA patients with malignancy had a higher proportion of women (63.6% vs. 40.8%, χ2=4.42, P=0.035), older age [56.4 (45.8, 67.3)years vs. 47.0 (36.0, 56.6) years, Z=-2.94, P=0.003], had a longer duration of psoriasis [20.0 (11.2, 33.5)years vs. 14.0 (6.0, 23.0) years, Z=-2.02, P=0.043], a longer duration of arthritis [8.0 (4.0, 17.0)years vs. 3.0 (1.0, 7.0) years, Z=-2.65, P=0.008], and a higher proportion of HLA-B27 positivity (25.0% vs. 4.4%, χ2=3.98, P=0.046). Age[ OR(95% CI)=1.056(1.008, 1.107), P=0.023], duration of PsA [ OR(95% CI)=1.051( 1.068, 1.106), P=0.010], and HLA-B27 positivity [ OR(95% CI)=5.086(1.278, 20.238), P=0.021] were the factors related to the occurrence of malignancy in PsA patients. Conclusion:Malignancy is not rare in PsA patients. Breast cancer, urinary system tumors and skin cancer are relatively common. PsA patients with older age, longer duration of PsA and positive HLA-B27 are more likely to have malignancy, which arouses more alert.