The efficacy and safety of different Janus kinase inhibitors as monotherapy in rheumatoid arthritis: A Bayesian network meta-analysis.

OBJECTIVE: This study aims to evaluate the efficacy and safety of JAK inhibitors in the treatment of patients with RA. METHODS: The databases CNKI, VIP, Wanfang, CBM, and PubMed, Embase, Cochrane Library and Web of Science were searched to identify relevant randomized controlled trials (RCTs), all from the time of database creation to April 2024. Screening, data extraction, and risk of bias assessment (using Review Manager-5.3 software) were independently performed by at least two authors. The network meta-analysis was conducted using R 4.1.3 software. PROSPERO registration number: CRD42022370444. RESULTS: Thirty-three RCTs included 15,961 patients The experimental groups involved six JAK inhibitors (filgotinib, tofacitinib, decernotinib, baricitinib, upadacitinib and peficitinib) and 12 interventions (different doses of the six JAK inhibitors), and the control group involved adalimumab (ADA) and placebo. Compared with placebo, all JAK inhibitors showed a significant increase in efficacy measures (ACR20/50/70). Compared with ADA, only tofacitinib, low-dose decernotinib, and high-dose peficitinib showed a significant increase in ACR20/50/70. Decernotinib ranked first in the SUCRA ranking of ACR20/50/70. In terms of safety indicators, only those differences between low-dose filgotinib and high-dose upadacitinib, low-dose tofacitinib and high-dose upadacitinib were statistically significant. Low-dose filgotinib ranked first in the SUCRA ranking with adverse events as safety indicators. Only the efficacy and safety of tofacitinib ranked higher among different SUCRA rankings. CONCLUSION: Six JAK inhibitors have better efficacy than placebo. The superior efficacy of decernotinib and safety of low-dose filgotinib can be found in the SUCRA. However, there are no significant differences in safety between the different JAK inhibitors. Head-to-head trials, directly comparing one against each other, are required to provide more certain evidence.

A rare case report: Myopathy related to the interaction between azathioprine and infliximab in the treatment of ulcerative colitis and ankylosing spondylitis.

Key Clinical Message: Administering azathioprine or infliximab for UC and AS treatment carries a significant risk of adverse reactions. Here, we present the case diagnosed with UC and AS, who received treatment with azathioprine and infliximab for 10 months, and subsequently developed drug-induced myopathy affecting the right vastus medialis muscle. Abstract: Drug-induced myopathy is an uncommon form of muscle injury that can arise in patients without preexisting muscle conditions when exposed to therapeutic doses of certain medications. Administering azathioprine or infliximab for ulcerative colitis (UC) and ankylosing spondylitis (AS) treatment carries a significant risk of adverse reactions, including drug-induced myopathy and increased susceptibility to opportunistic infections. However, occurrences of myopathy induced by the combination of azathioprine and infliximab are rarely reported in clinical practice. Here, we present the case of a 37-year-old male patient diagnosed with UC and AS, who received treatment with azathioprine and infliximab for 10 months. Despite the resolution of symptoms and improvement in intestinal mucosal inflammation observed via endoscopy, the patient subsequently developed drug-induced myopathy affecting the right vastus medialis muscle.

Effects of Microtopography on Soil Microbial Community Structure and Abundance in Permafrost Peatlands.

Soil microorganisms play crucial roles in the stability of the global carbon pool, particularly in permafrost peatlands that are highly sensitive to climate change. Microtopography is a unique characteristic of peatland ecosystems, but how microtopography affects the microbial community structures and their functions in the soil is only partially known. We characterized the bacterial and fungal community compositions by amplicon sequencing and their abundances via quantitative PCR at different soil depths in three microtopographical positions (hummocks, flats, and hollows) in permafrost peatland of the Greater Xing'an Mountains in China. The results showed that the soil of hummocks displayed a higher microbial diversity compared to hollows. Microtopography exerted a strong influence on bacterial community structure, while both microtopography and soil depth greatly impacted the fungal community structure with variable effects on fungal functional guilds. Soil water content, dissolved organic carbon, total phosphorus, and total nitrogen levels of the soil mostly affected the bacterial and fungal communities. Microtopography generated variations in the soil water content, which was the main driver of the spatial distribution of microbial abundances. This information stressed that the hummock-flat-hollow microtopography of permafrost peatlands creates heterogeneity in soil physicochemical properties and hydrological conditions, thereby influencing soil microbial communities at a microhabitat scale. Our results imply that changes to the water table induced by climate warming inducing permafrost degradation will impact the composition of soil microbes in peatlands and their related biogeochemical functions, eventually providing feedback loops into the global climate system.

Sema4D as a biomarker for Predicting rheumatoid arthritis disease activity.

OBJECTIVE: The semaphorins are membrane or secreted proteins first identified in neural development. Semaphorin 4D (Sema4D) is the first family member found to have immune properties. We evaluated the potential of Sema4D as a marker for rheumatoid arthritis (RA) disease activity, singly and in combination with other known biomarkers including rheumatoid factor (RF) and C-reactive protein (CRP). METHODS: Three hundred and eleven RA patients were enrolled. The patients were divided into three groups based on their disease activity in 28 joints (DAS28): mild, moderate, and severe. The healthy group included 40 healthy individuals. SerumSema4D was measured by quantitative ELISA and the specificity and sensitivity of biomarkers were evaluated by generating a receiver operating characteristic (ROC) curve to analyze their diagnostic accuracy. RESULTS: Serum Sema4D levels in the moderate and severe RA groups were elevated significantly above those of the controls (P < 0.01), while levels in the mild RA and control groups did not differ significantly (P > 0.05). The Sema4D cutoff threshold was 15.7 ng/ml when the DAS28 was applied as a reference. Compared to the erythrocyte sedimentation rate (ESR and CRP, Sema4D had the highest specificity (96.8%) and area under the curve (0.80) for diagnosing RA activity. The highest specificity (100%) for the biomarker combinations was obtained when Sema4D was combined with CRP and anti-CCP, the combination of the Sema4D combined with ESR and anti-CCP had the highest sensitivity (99.35%). According to this result, a new model for jointly calculating RA activity of Sema4D,anti-CCP and CRP was constructed. Meanwhile another model is established by using the method of multivariate analysis.Model comparison results showed the the multiple regression algorithm method fitted the patients' disease activity better. CONCLUSION: The serum Sema 4D level effectively reflects moderate to severe RA activity. Sema4D levels can be used together with conventional RA biomarkers to increase the diagnostic power of RA activity. The multiple regression algorithm method is promising in disease activity calculation.

Comparative effectiveness of ustekinumab vs. vedolizumab for anti-TNF-naïve or anti-TNF-exposed Crohn's disease: a multicenter cohort study.

Background: Ustekinumab and vedolizumab are both effective for treating Crohn's disease (CD). However, no head-to-head trials have been conducted thus far. We aimed to compare the effectiveness of ustekinumab and vedolizumab in CD patients either naïve or exposed to tumor necrosis factor-alpha inhibitors (TNFi). Methods: Patients treated with vedolizumab or ustekinumab for luminal CD were included from six centers in China from May 2020 to July 2023. Steroid-free remission, clinical remission, objective response, and remission at Weeks 26 and 52 were evaluated in a retrospective multicenter propensity score-weighted cohort. Findings: A total of 536 patients were included (386 ustekinumab, and 150 vedolizumab). After adjustment, ustekinumab showed higher rates of clinical remission (56.4% vs. 47.8%, P = 0.005), steroid-free remission (55.4% vs. 46.1%, P = 0.003), and objective response (67.8% vs. 42.7%, P < 0.001) than vedolizumab at Week 26. At Week 52, ustekinumab exhibited significantly higher rates of clinical remission (65.8% vs. 37.5%, P < 0.001), steroid-free remission (65.8% vs. 37.5%, P < 0.001), objective response (66.7% vs. 23.8%, P < 0.001), and objective remission (31.4% vs. 12.7%, P < 0.001). Subgroup analyses revealed that ustekinumab had higher rates of clinical remission, steroid-free remission, and objective response at Weeks 26 and 52, and objective remission at Week 52 in TNFi-exposed patients, while ustekinumab showed higher rates of objective response at Weeks 26 and 52 and clinical remission, steroid-free remission and objective remission at Week 52 in TNFi-naïve patients. Adverse event rates were similar between the groups (4.9% ustekinumab vs. 6.7% vedolizumab, P = 0.423). Interpretation: Ustekinumab showed superior clinical and objective outcomes compared to vedolizumab, with comparable safety outcomes. The therapeutic superiority was observed in both short-term and long-term phases in TNFi-exposed patients, and the long-term phase in TNFi-naïve patients. Funding: National Natural Science Foundation of China, Guangdong Basic and Applied Basic Research Foundation, Key Research Projects of the Sixth Affiliated Hospital, Sun Yat-sen University, the program of Guangdong Provincial Clinical Research Center for Digestive Diseases, and National Key Clinical Discipline.

The prognostic value of whole-genome DNA methylation in response to Leflunomide in patients with Rheumatoid Arthritis.

Objective: Although Leflunomide (LEF) is effective in treating rheumatoid arthritis (RA), there are still a considerable number of patients who respond poorly to LEF treatment. Till date, few LEF efficacy-predicting biomarkers have been identified. Herein, we explored and developed a DNA methylation-based predictive model for LEF-treated RA patient prognosis. Methods: Two hundred forty-five RA patients were prospectively enrolled from four participating study centers. A whole-genome DNA methylation profiling was conducted to identify LEF-related response signatures via comparison of 40 samples using Illumina 850k methylation arrays. Furthermore, differentially methylated positions (DMPs) were validated in the 245 RA patients using a targeted bisulfite sequencing assay. Lastly, prognostic models were developed, which included clinical characteristics and DMPs scores, for the prediction of LEF treatment response using machine learning algorithms. Results: We recognized a seven-DMP signature consisting of cg17330251, cg19814518, cg20124410, cg21109666, cg22572476, cg23403192, and cg24432675, which was effective in predicting RA patient's LEF response status. In the five machine learning algorithms, the support vector machine (SVM) algorithm provided the best predictive model, with the largest discriminative ability, accuracy, and stability. Lastly, the AUC of the complex model(the 7-DMP scores with the lymphocyte and the diagnostic age) was higher than the simple model (the seven-DMP signature, AUC:0.74 vs 0.73 in the test set). Conclusion: In conclusion, we constructed a prognostic model integrating a 7-DMP scores with the clinical patient profile to predict responses to LEF treatment. Our model will be able to effectively guide clinicians in determining whether a patient is LEF treatment sensitive or not.

Variations in soil microbial community structure and extracellular enzymatic activities along a forest-wetland ecotone in high-latitude permafrost regions.

Permafrost degradation by global warming is expected to alter the hydrological processes, which results in changes in vegetation species composition and gives rise to community succession. Ecotones are sensitive transition areas between ecosystem boundaries, attract particular interest due to their ecological importance and prompt responses to the environmental variables. However, the characteristics of soil microbial communities and extracellular enzymes along the forest-wetland ecotone in high-latitude permafrost region remain poorly understood. In this study, we evaluated the variations of soil bacterial and fungal community structures and soil extracellular enzymatic activities of 0-10 cm and 10-20 cm soil layers in five different wetland types along environmental gradients, including Larix gmelinii swamp (LY), Betula platyphylla swamp (BH), Alnus sibirica var. hirsute swamp (MCY), thicket swamp (GC), and tussock swamp (CC). The relative abundances of some dominant bacterial (Actinobacteria and Verrucomicrobia) and fungal (Ascomycota and Basidiomycota) phyla differed significantly among different wetlands, while bacterial and fungal alpha diversity was not strongly affected by soil depth. PCoA results showed that vegetation type, rather than soil depth explained more variation of soil microbial community structure. ß-glucosidase and ß-N-acetylglucosaminidase activities were significantly lower in GC and CC than in LY, BH, and MCY, while acid phosphatase activity was significantly higher in BH and GC than LY and CC. Altogether, the data suggest that soil moisture content (SMC) was the most important environmental factor contributing to the bacterial and fungal communities, while extracellular enzymatic activities were closely related to soil total organic carbon (TOC), nitrate nitrogen (NO3--N) and total phosphorus (TP).

Effects of Empagliflozin on Gut Microbiota in Heart Failure with a Preserved Ejection Fraction: The Design of a Pragmatic Randomized, Open-Label Controlled Trial (EMPAGUM).

Although empagliflozin has been recommended for individuals with heart failure, its effects on heart failure with preserved ejection fraction (HFpEF) remain uncertain from a physiopathological standpoint. The metabolites produced by gut microbiota have been shown to have a crucial role in the development of heart failure. Sodium-glucose cotransporter-2 inhibitors (SGLT2) have been shown to change the make-up of the gut microbiota in rodent studies. There is mixed evidence from similar studies investigating whether or not SGLT2 can affect the microbiota in the human gut. This trial is a pragmatic, randomized, open-label controlled study with empagliflozin as an intervention. We will enroll 100 patients with HFpEF and randomly assign them to one of two groups to receive either empagliflozin or a placebo. Patients in the Empagliflozin group will be given 10 mg of the drug daily, while those in the Control group will not be given empagliflozin or any other SGLT2. The purpose of the trial is to validate the changes that occur in gut microbiota in patients with HFpEF who take empagliflozin and to investigate the function of gut microbiota and their metabolites in the process.

Diversity and Distribution Characteristics of Soil Microbes across Forest-Peatland Ecotones in the Permafrost Regions.

Permafrost peatlands are a huge carbon pool that is uniquely sensitive to global warming. However, despite the importance of peatlands in global carbon sequestration and biogeochemical cycles, few studies have characterized the distribution characteristics and drivers of soil microbial community structure in forest-peatland ecotones. Here, we investigated the vertical distribution patterns of soil microbial communities in three typical peatlands along an environmental gradient using Illumina high-throughput sequencing. Our findings indicated that bacterial richness and diversity decreased with increasing soil depth in coniferous swamp (LT) and thicket swamp (HT), whereas the opposite trend was observed in a tussock swamp (NT). Additionally, these parameters decreased at 0-20 and 20-40 cm and increased at 40-60 cm along the environmental gradient (LT to NT). Principal coordinate analysis (PCoA) indicated that the soil microbial community structure was more significantly affected by peatland type than soil depth. Actinomycetota, Proteobacteria, Firmicutes, Chloroflexota, Acidobacteriota, and Bacteroidota were the predominant bacterial phyla across all soil samples. Moreover, there were no significant differences in the functional pathways between the three peatlands at each depth, except for amino acid metabolism, membrane transport, cell motility, and signal transduction. Redundancy analysis (RDA) revealed that pH and soil water content were the primary environmental factors influencing the bacterial community structure. Therefore, this study is crucial to accurately forecast potential changes in peatland ecosystems and improve our understanding of the role of peat microbes as carbon pumps in the process of permafrost degradation.

Clinical guideline for the diagnosis and treatment of cutaneous warts (2022).

AIM: Cutaneous warts caused by human papillomavirus are benign proliferative lesions that occur at any ages in human lives. Updated, comprehensive and systematic evidence-based guidelines to guide clinical practice are urgently needed. METHODS: We collaborated with multidisciplinary experts to formulate this guideline based on evidences of already published literature, focusing on 13 clinical questions elected by a panel of experts. We adopted Grading of Recommendations Assessment, Development and Evaluation (GRADE) system to form classification of recommendations as well as the improved Delphi method to retain respective recommendations with a consensus degree of over 80%. RESULTS: Our guideline covered aspects of the diagnosis and treatment of cutaneous warts such as diagnostic gold standard, transmission routes, laboratory tests, treatment principle, clinical cure criterion, definitions, and treatments of common warts, flat warts, plantar warts, condyloma acuminatum, and epidermodysplasia verruciformis. Recommendations about special population such as children and pregnant women are also listed. In total, 49 recommendations have been obtained. CONCLUSIONS: It is a comprehensive and systematic evidence-based guideline and we hope this guideline could systematically and effectively guide the clinical practice of cutaneous warts and improve the overall levels of medical services.

Machine learning to identify immune-related biomarkers of rheumatoid arthritis based on WGCNA network.

OBJECTIVES: This study was designed to identify the potential diagnostic biomarkers of rheumatoid arthritis (RA) and to explore the potential pathological relevance of immune cell infiltration in this disease. METHODS: Three previously published datasets containing gene expression data from 35 RA patients and 29 controls (GSE55235, GSE55457, and GSE12021) were downloaded from the GEO database, after which a weighted correlation network analysis (WGCNA) approach was utilized to clarify differentially abundant genes. Candidate biomarkers of RA were then identified via the use of a LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) analyses. Data were validated based upon the area under the receiver operating characteristic curve (AUC) values, with hub genes being identified as those with an AUC > 85% and a P value < 0.05. Lastly, the CIBERSORT algorithm was used to assess immune cell infiltration of RA tissues, and correlations between immune cell infiltration and disease-related diagnostic biomarkers were assessed. RESULTS: The green-yellow module containing 87 genes was found to be highly correlated with RA positivity. FADD, CXCL2, and CXCL8 were identified as potential RA diagnostic biomarkers (AUC > 0.85), and these results were validated using the GSE77298 dataset. Immune cell infiltration analyses revealed the expression of hub genes to be correlated with mast cells, monocytes, activated NK cells, CD8 T cells, resting dendritic cells, and plasma cells. CONCLUSION: These data indicate that FADD, CXCL2, and CXCL8 are valuable diagnostic biomarkers of RA, offering new insight that can guide future studies of RA incidence and progression.

Prognostic value of nicotinamide adenine dinucleotide (NAD+) metabolic genes in patients with stomach adenocarcinoma based on bioinformatics analysis.

Background: Because stomach adenocarcinoma (STAD) has a poor prognosis, it is necessary to explore new prognostic genes to stratify patients to guide existing individualized treatments. Methods: Survival and clinical information, RNA-seq data and mutation data of STAD were acquired from The Cancer Genome Atlas (TCGA) database. Fifty-one nicotinamide adenine dinucleotide (NAD+) metabolism-related genes (NMRGs) were obtained from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases. Differentially expressed NMRGs (DE-NMRGs) between STAD and normal samples were screened, and consistent clustering analysis of STAD patients was performed based on the DE-NMRGs. Survival analysis, Gene Set Enrichment Analysis (GSEA), mutation frequency analysis, immune microenvironment analysis and drug prediction were performed among different clusters. Additionally, the differentially expressed genes (DEGs) among different clusters were selected, and the intersections of DEGs and DE-NMRGs were selected as the prognostic genes. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was performed on a human gastric mucosa epithelial cell line and cancer cell line to verify the expression of the prognostic genes. Results: A total of 27 DE-NMRGs and two clusters were selected. There was a difference in survival between clusters 1 and 2. Furthermore, 18 DE-NMRGs were significantly different between clusters 1 and 2. The different Gene Ontology (GO) biological processes and KEGG pathways between clusters 1 and 2 were mainly enriched in cyclic nucleotide mediated signaling, synaptic signaling and hedgehog signaling pathway, etc. The somatic mutation frequencies were different between the two clusters, and TTN was the highest mutated gene in the patients of the clusters 1 and 2. Additionally, eight immune cells, immune score, stromal score, and estimate score were different between clusters 1 and 2. The patients in cluster 2 were sensitive to CTLA4 inhibitor treatment. Furthermore, the top five drugs (AP.24534, BX.795, Midostaurin, WO2009093927 and CCT007093) were significantly higher in cluster 1 than in cluster 2. Finally, three genes (AOX1, NNMT and PTGIS) were acquired as prognostic, and their expressions were consistent with the results of bioinformatics analysis. Conclusions: Three prognostic genes related to NAD+ metabolism in STAD were screened out, which provides a theoretical basis and reference value for future treatment and prognosis of STAD.

Obstructive Sleep Apnoea in Stanford Type B Aortic Dissection Is Associated With Multiple Imaging Signs Related to Late Aortic Events.

Background: Obstructive sleep apnoea (OSA) is highly prevalent in patients with Stanford type B aortic dissection (TBAD). Few studies have evaluated the effects of OSA on vascular changes in TBAD patients. This study aimed to explore the effect of OSA on aortic morphological changes in TBAD patients and its relation to late aortic events (LAEs). Methods: This case-control study included 143 TBAD patients. The diameters of different parts of the aorta were measured based on computed tomography angiography (CTA). According to the apnoea-hypopnoea index (AHI), OSA was classified as mild (5 ≤ AHI ≤ 15), moderate (15 < AHI ≤ 30), or severe (AHI > 30). The false lumen (FL) status was evaluated and classified as partially thrombosed, patent, or completely thrombosed. Results: The OSA prevalence in TBAD patients was 64.3%, and image differences related to LAEs between TBAD patients with and without OSA included the maximum aortic diameter at onset (37.3 ± 3.9 vs. 40.3 ± 4.5 mm, p < 0.001), the FL diameter of the proximal descending thoracic aorta (16.0 ± 6.8 vs. 20.3 ± 4.7 mm, p < 0.001), and the proportion of the FL that was partially thrombosed (39.2 vs. 64.1%, p = 0.004). Additionally, in the multivariable analysis of patients with OSA, the risks of an aortic diameter ≥40 mm, a proximal descending aorta FL ≥ 22 mm and a partially thrombosed FL were 4.611 (95% CI: 1.796-11.838, p = 0.001), 2.544 (95% CI: 1.050-6.165, p = 0.039), and 2.565 (95% CI: 1.167-5.637, p = 0.019), respectively, after adjustment for confounding factors. Trend tests showed that the risks of an aortic diameter ≥40 mm and a partially thrombosed FL increased with increasing OSA severity. Conclusions: TBAD patients with moderate to severe OSA have aortic dilatation in different parts of the aorta. OSA is an independent risk factor for multiple imaging signs related to LAEs, suggesting that OSA is an important factor affecting the prognosis of TBAD patients.

Development and validation of a nomogram for predicting stroke risk in rheumatoid arthritis patients.

We developed and validated a nomogram to predict the risk of stroke in patients with rheumatoid arthritis (RA) in northern China. Out of six machine learning algorithms studied to improve diagnostic and prognostic accuracy of the prediction model, the logistic regression algorithm showed high performance in terms of calibration and decision curve analysis. The nomogram included stratifications of sex, age, systolic blood pressure, C-reactive protein, erythrocyte sedimentation rate, total cholesterol, and low-density lipoprotein cholesterol along with the history of traditional risk factors such as hypertensive, diabetes, atrial fibrillation, and coronary heart disease. The nomogram exhibited a high Hosmer-Lemeshow goodness-for-fit and good calibration (P > 0.05). The analysis, including the area under the receiver operating characteristic curve, the net reclassification index, the integrated discrimination improvement, and clinical use, showed that our prediction model was more accurate than the Framingham risk model in predicting stroke risk in RA patients. In conclusion, the nomogram can be used for individualized preoperative prediction of stroke risk in RA patients.

Systematic analysis of the molecular mechanisms of methotrexate therapy for rheumatoid arthritis using text mining.

OBJECTIVES: The purpose of this study was to determine the expression of related genes in patients with rheumatoid arthritis (RA) treated with methotrexate (MTX), to identify hub genes, and to systematically analyse the functions, pathways, and networks of these genes. METHODS: The PubMed identifiers (PMIDs) of relevant publications were obtained from the PubMed database, and gene data were extracted from these documents using the text mining software PubTator. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to obtain enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway information. In addition, the STRING database was used to construct a protein-protein interaction (PPI) network. Genes with which at least 10 other genes interacted were identified as hub genes. RESULTS: A total of 216 genes were identified as being associated with treatment efficacy for MTX, of which 14 pathways exhibited significant correlation (p<0.05, FDR<0.05). In addition, the constructed MTX treatment-related network consisted of 267 interactions. Fourteen genes were found to interact with at least 10 other genes (p<0.05, FDR<0.05) and identified as hub genes in the PPI network. These genes were JAK1, MAPK1, JUN, AKT1, MAPK14, MAPK8, FGB, FN1, ALB, B2M, IL2RB, GGH, IL2RA, and TP53. CONCLUSIONS: This study will assist in elucidating the molecular mechanisms associated with the treatment efficacy of MTX for RA and provide a scientific rationale for guiding patient medication. However, the relationship between particular genes and the efficacy of MTX treatment for RA patients requires additional investigation.

Quality of life and influencing factors of patients with rheumatoid arthritis in Northeast China.

PURPOSE: Rheumatoid arthritis (RA) is a disease with a high disability rate, resulting in severe family and social burden. The aim of treatment is to improve the health-related quality of life (QoL) of patients. The purpose of this study was to evaluate the QoL of patients with RA in Northeast China and analyze its influencing factors. METHODS: The study group consisted of 200 patients diagnosed with RA. The control group consisted of 200 healthy subjects. All subjects were residents in Northeast China. The investigation was conducted by questionnaire survey and electronic medical record. The WHOQOL-BREF, The Short-Form 36 Health Survey (SF-36) and Quality of Life Instruments for Chronic Diseases-RA (QLICD-RA) were used as questionnaires. RESULTS: The QoL scores acquired by SF-36, WHOQOL-BREF and QLICD-RA scales showed significant differences between RA and control groups (P < 0.001). Multiple regression analysis showed that sleep duration (P = 0.001), psychological counseling (P < 0.001) and C4 level (P = 0.001) influenced the SF-36 scale evaluation model. IgA levels (P < 0.001) and being overweight (P = 0.030) were included in the WHOQOL-BREF evaluation model. Adequate sleep (P = 0.001) and psychological counseling(P = 0.050) entered the QLICD-RA scale evaluation model (P = 0.050), in which psychological counseling, normal C4 levels and being overweight were protective factors for RA, insufficient sleep and IgA levels were risk factors for RA. CONCLUSIONS: The QoL of RA patients is generally lower than those of healthy subjects in the Northeast China, Northeast China. Sleep duration, BMI (Body mass index), psychological counseling, C4 and IgA levels are factors that influence the QoL scores of RA patients.

Development and validation of a nomogram to predict coronary heart disease in patients with rheumatoid arthritis in northern China.

We developed and validated a nomogram to predict coronary heart disease (CHD) in patients with rheumatoid arthritis (RA) in northern China. We analyzed a cohort of RA patients admitted to the Department of Rheumatology and Immunology of the First Affiliated Hospital of China Medical University from 2011 to 2017. To select a high-performance model for clinical data prediction, we evaluated the F1-scores of six machine learning models. Based on the results, we selected multivariable logistic regression analysis for the development of a prediction model. We then generated an individualized prediction nomogram that included age, sex, hypertension, anti-cyclic citrullinated peptide antibody positivity, the erythrocyte sedimentation rate, and serum LDL-cholesterol, triglyceride and HDL-cholesterol levels. The prediction model exhibited better discrimination than the Framingham Risk Score in predicting CHD in RA patients. The area under the curve of the prediction model was 0.77, with a sensitivity of 63.9% and a specificity of 77.2%. The nomogram exhibited good calibration and clinical usefulness. In conclusion, our prediction model was more accurate than the Framingham Risk Score in predicting CHD in RA patients. Our nomogram combining various risk factors can be used for the individualized preoperative prediction of CHD in patients with RA.

A nomogram based on a gene signature for predicting the prognosis of patients with head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant tumors. The purpose of this study was to establish and validate a gene-expression-based prognostic signature in non-metastatic patients with HNSCC. MATERIALS AND METHODS: All the patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We randomly divided the GSE65858 samples into 70% (training cohort, n = 190) and 30% (internal validation cohort, n = 72). A total of 36 samples collected from the TCGA HNSCC databases were selected as an independent external validation cohort. The oligo package in R was used to normalize the raw data before analysis. Data characteristics were extracted, and a gene signature was built via the least absolute shrinkage and selection operator regression model. The predictive model was developed by multivariable Cox regression analysis. T stage, N stage, human papilloma virus status, and the gene signature were incorporated in this predictive model, which was shown as a nomogram. Calibration and discrimination were performed to assess the performance of the nomogram. The clinical utility of this nomogram was assessed by the decision curve analysis. RESULTS: Overall, 2001 significant messenger RNAs in HNSCC samples were identified compared with normal samples. The gene signature contained seven genes and significantly correlated with overall survival. The gene signature was also significant in subgroup analysis of the primary cohort. The calibration was plotted in the external cohort (C-index 0.90, 95% CI 0.85, 0.95) compared with the training (C-index 0.76, 95% CI 0.73, 0.79) and internal (C-index 0.71, 95% CI 0.66, 0.77) cohorts. In clinic, a decision curve analysis demonstrated that the model including the prognostic gene signature score status was better than that without it. CONCLUSION: This study developed and validated a predictive model, which can promote the individualized prediction of overall survival in non-metastatic patients with HNSCC.