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Background: The prediction model of intravenous immunoglobulin (IVIG) resistance in Kawasaki disease can calculate the probability of IVIG resistance and provide a basis for clinical decision-making. We aim to assess the quality of these models developed in the children with Kawasaki disease., Methods: Studies of prediction models for IVIG-resistant Kawasaki disease were identified through searches in the PubMed, Web of Science, and Embase databases. Two investigators independently performed literature screening, data extraction, quality evaluation, and discrepancies were settled by a statistician. The checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) was used for data extraction, and the prediction models were evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST)., Results: Seventeen studies meeting the selection criteria were included in the qualitative analysis. The top three predictors were neutrophil measurements (peripheral neutrophil count and neutrophil %), serum albumin level, and C-reactive protein (CRP) level. The reported area under the curve (AUC) values for the developed models ranged from 0.672 (95% confidence interval [CI]: 0.631-0.712) to 0.891 (95% CI: 0.837-0.945); The studies showed a high risk of bias (ROB) for modeling techniques, yielding a high overall ROB., Conclusion: IVIG resistance models for Kawasaki disease showed high ROB. An emphasis on improving their quality can provide high-quality evidence for clinical practice., Impact Statement: This study systematically evaluated the risk of bias (ROB) of existing prediction models for intravenous immunoglobulin (IVIG) resistance in Kawasaki disease to provide guidance for future model development meeting clinical expectations. This is the first study to systematically evaluate the ROB of IVIG resistance in Kawasaki disease by using PROBAST. ROB may reduce model performance in different populations. Future prediction models should account for this problem, and PROBAST can help improve the methodological quality and applicability of prediction model development., (© 2023. The Author(s).)

Although national health-related quality of life population norms had been published based on the EuroQol 5-Dimensions 5-levels scale, China is a vast country with diverse cultural and social development in various regions. Therefore, regional population norms may better reflect the health status of residents in a given area. The purpose of the study was to derive the HRQoL population norm for adult general population in southern Jiangsu Province using the EQ-5D-5L scale and explore potential influencing factors. The data were based on a cross-sectional survey conducted in Liyang City from March 2019 to July 2020. EQ-5D-5L utility scores based on Chinese value set and EQ-VAS scores were used to assess HRQoL. The Tobit regression model and generalized linear model were performed to identify the association among potential covariates and HRQoL. The means (95% confidence interval) of the EQ-5D-5L utility scores and EQ-VAS scores were 0.981(0.980-0.983) and 83.6(83.2-83.9), respectively. Younger people (≤ 40 years old) were more likely to experience problems with anxiety or depression. Additionally, women had lower HRQoL scores although multivariate analysis found no statistical difference between the sexes. Lower HRQoL was associated with advanced age, lower socioeconomic status, no spouse, lack of regular physical activities, smoking cessation, and chronic non-communicable diseases. Subjects who declared that they were afflicted by diseases presented significantly lower utility scores, ranging from 0.823 (0.766-0.880) for memory-related diseases to 0.978 (0.967-0.989) for hepatic diseases. Regional population norms of HRQoL are needed in the health economic study owing to the great socioeconomic differences across regions in China. The present study provides HRQoL population norms for adults in southern Jiangsu. These norm values could help policy makers better allocate limited health resources and prioritize service plans., (© 2022. The Author(s).)

There have been few investigations of cancer prognosis models based on Bayesian hierarchical models. In this study, we used a novel Bayesian method to screen mRNAs and estimate the effects of mRNAs on the prognosis of patients with lung adenocarcinoma. Based on the identified mRNAs, we can build a prognostic model combining mRNAs and clinical features, allowing us to explore new molecules with the potential to predict the prognosis of lung adenocarcinoma. The mRNA data (n = 594) and clinical data (n = 470) for lung adenocarcinoma were obtained from the TCGA database. Gene set enrichment analysis (GSEA), univariate Cox proportional hazards regression, and the Bayesian hierarchical Cox proportional hazards model were used to explore the mRNAs related to the prognosis of lung adenocarcinoma. Multivariate Cox proportional hazard regression was used to identify independent markers. The prediction performance of the prognostic model was evaluated not only by the internal cross-validation but also by the external validation based on the GEO dataset (n = 437). With the Bayesian hierarchical Cox proportional hazards model, a 14-gene signature that included CPS1, CTPS2, DARS2, IGFBP3, MCM5, MCM7, NME4, NT5E, PLK1, POLR3G, PTTG1, SERPINB5, TXNRD1, and TYMS was established to predict overall survival in lung adenocarcinoma. Multivariate analysis demonstrated that the 14-gene signature (HR 3.960, 95% CI 2.710-5.786), T classification (T 1 , reference; T 3 , HR 1.925, 95% CI 1.104-3.355) and N classification (N 0 , reference; N 1 , HR 2.212, 95% CI 1.520-3.220; N 2 , HR 2.260, 95% CI 1.499-3.409) were independent predictors. The C-index of the model was 0.733 and 0.735, respectively, after performing cross-validation and external validation, a nomogram was provided for better prediction in clinical application. Bayesian hierarchical Cox proportional hazards models can be used to integrate high-dimensional omics information into a prediction model for lung adenocarcinoma to improve the prognostic prediction and discover potential targets. This approach may be a powerful predictive tool for clinicians treating malignant tumours., (© 2022. The Author(s).)

To examine the prospective associations between total cholesterol (TC) variability and cognitive function in a large sample of Chinese participants aged 45 years and above. A total of 6,377 people who participated in the China Health and Retirement Longitudinal Study (CHARLS) were included. TC variability was defined as the intra-individual standard deviation over two blood tests in CHARLS 2011 and 2015 (Wave 1 and Wave 3). Cognitive function was assessed by a global cognition score, which included three tests: episodic memory, figure drawing and Telephone Interview of Cognitive Status (TICS). Multivariate linear regression models (MRLMs) and generalized estimating equation (GEE) were used to investigate associations between TC variability and cognitive scores. After adjusting for potential confounders, male participants with higher visit-to-visit TC variability showed lower global cognition scores (β = - 0.71, P < 0.001). After further adjustment for baseline cognition, the association remained statistically significant (β = - 0.68, P < 0.001). The domains with declines were focused on episodic memory (β = - 0.22, P = 0.026) and TICS (β = - 0.44, P = 0.004). However, these associations were not found in women (β = - 0.10, P = 0.623). For men, the rates of decline in global cognition increased by 0.14 (β = - 0.14, P = 0.009) units per year while TC variability increased by 1 mmol/L. For males, higher visit-to-visit TC variability correlated with lower cognitive function and an increased rate of decreases in memory. More attention should be paid to cognitive decline in males with high TC variability, and particularly, on decreases in memory, calculation, attention and orientation.

Dietary quality is an important factor influencing prediabetes, but few studies have applied the Chinese Diet Balance Index (DBI-16) to evaluate the dietary quality of individuals with prediabetes and explore the associations between dietary quality and prediabetes. In our study, the lower-bound score, higher-bound score and diet quality distance, were respectively calculated to assess dietary quality based on each food group. Logistic regression was used to calculate the odds ratio (OR) and 95% confidence interval (95%CI) of unfavorable dietary quality leading to prediabetes in every subgroup. The results were shown that individuals with prediabetes had excessive intake in the categories of cereals, salt and inadequate intake in vegetables, fish and diet variety than participants without prediabetes (all P < 0.01). Unfavourable dietary quality was significantly associated with an increased risk of prediabetes (OR: 1.45, 95%CI: 1.29-1.63), especially among the subjects who lived in rural areas (OR: 1.63, 95%CI: 1.25-1.76), those who had abdominal obesity (OR: 1.58, 95%CI: 1.36-1.85), those who smoked (OR: 1.58, 95%CI: 1.30-1.93), those who consumed alcohol (OR: 1.57, 95%CI: 1.28-1.93) and those who did not drink tea (OR: 1.64, 95%CI: 1.42-1.88). In Conclusion, unfavourable dietary quality was significantly associated with an increased risk of prediabetes.

Multimorbidity has posed a major challenge to health care systems worldwide, but little is known about its association with biological factors. This study represents the first one to examine the association of serum levels of alanine aminotransferase (ALT) with multimorbidity. The baseline category logistic regression model was used to estimate the odds ratio (OR) between ALT and multimorbidity, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the classification utility of ALT. Serum ALT levels were associated, in a dose-response manner, with multimorbidity. Compared with the first quartile, the adjusted OR (95% confidence interval) of the fourth quartile for multimorbidity was 4.71 (3.56-6.23). In addition, the AUC value for distinguishing the multimorbidity group from the control group reached 0.7185. In conclusion, high levels of ALT were significantly correlated with multimorbidity and this association was independent of other potential risk factors. Serum ALT might be a useful marker for identifying individuals with multimorbidity.

Interleukin-6 acts as both a pro-inflammatory cytokine and an anti-inflammatory myokine. IL-6/IL-6R signaling pathway, in particular, has been proposed to be a pivotal cytokine promoting ovarian cancer progression. This study aimed to elucidate potential clinical and biological function of IL-6R mRNA expression in ovarian cancer. We used the keywords "ovarian cancer" and searched through GEO database and finally a total of 7 studies together with TCGA database were incorporated in this analysis. We used Cutoff Finder to determine a cutoff point and stratified patients into two groups and found that high-expression of IL-6R mRNA in tumor tissues was a positive prognostic factor for overall survival. Simultaneously, high expression level of IL-6R mRNA correlates with better survival of patients who had additional chemotherapy treatment. These analyses suggested a possible role of tumoral expression of IL-6R in ovarian cancer. In conclusion, our results showed that mRNA levels of IL-6R in ovarian cancer was positively associated with better prognosis and sensitivity to chemotherapy and can potentially be used as a prognostic marker for this cancer.

Regulatory T cells (Tregs), a key mediator in regulating anti-tumor immune suppression, tumor immune escape, metastasis and relapse, are considered an important therapeutic target in immunotherapy of human cancers. In the present investigation, elevated CD19 + CD24 + CD38 + regulatory B cells (Bregs) were observed in PBMCs of invasive carcinoma of breast (IBCa) patients compared with that in patients with fibroadenoma (FIBma) or healthy individuals, and the positive correlation existed between Bregs and CD4 + CD25 + CD127 - Tregs (r = 0.316, P = 0.001). We found that PD-L1 expression was higher on Bregs in IBCa patients compared with patients with FIBma or healthy individuals (P < 0.05, respectively), and that a tight correlation exists between CD19 + CD24 + CD38 + PD-L1 + Bregs and CD19 + CD24 + CD38 + Bregs (r = 0.267, P = 0.007), poor TNM phases and up-regulated expression of PD-L1 on Bregs. The pattern of PD-1 expression on CD4 + T cells indicated that high level of PD-1 hi expressed on CD4 + CD25 + CD127 + effector T cells (P < 0.001). More importantly, the presence of PD-L1 on Bregs was positively correlated with Tregs (r = 0.299, P = 0.003), but negatively correlated with PD-1 hi effector T cells (r = -0.22, P = 0.031). Together, results of the present study indicated that PD-L1 is an important molecule on Bregs, mediated the generation of Tregs in IBCa.

To evaluate the burden of air pollution on years of life lost (YLL) in addition to mortality, we conducted a time series analysis based on the data on air pollution, meteorological conditions and 163,704 non-accidental deaths of Ningbo, China, 2009-2013. The mean concentrations of particulate matter with aerodynamic diameter <10 μm, particulate matter with aerodynamic diameter <2.5 μm, sulfur dioxide and nitrogen dioxide were 84.0 μg/m(3), 60.1 μg/m(3), 25.1 μg/m(3) and 41.7 μg/m(3), respectively. An increase of 10-μg/m(3) in particulate matter with aerodynamic diameter <10 μm, particulate matter with aerodynamic diameter <2.5 μm, sulfur dioxide and nitrogen dioxide was associated with 4.27 (95% confidence interval [CI] 1.17-7.38), 2.97 (95% CI -2.01-7.95), 29.98 (95% CI 19.21-40.76) and 16.58 (95% CI 8.19-24.97) YLL, respectively, and 0.53% (95% CI 0.29-0.76%), 0.57% (95% CI 0.20-0.95%), 2.89% (95% CI 2.04-3.76%), and 1.65% (95% CI 1.01-2.30%) increase of daily death counts, respectively. The impact of air pollution lasted for four days (lag 0-3), and were more significant in the elderly than in the young population for both outcomes. These findings clarify the burden of air pollution on YLL and highlight the importance and urgency of air pollution control in China.

Growing evidence indicates that nomogram combined with the biomarkers of systemic inflammation response could provide more accurate prediction than conventional staging systems in tumors. This study aimed to establish an effective prognostic nomogram for resectable thoracic esophageal squamous cell carcinoma (ESCC) based on the clinicopathological parameters and inflammation-based prognostic scores. We retrospectively investigated 916 ESCC patients who underwent radical esophagectomy. The predictive accuracy and discriminative ability of the nomogram were determined by concordance index (C-index) and calibration curve, and compared with the 6(th) and 7(th) AJCC TNM classifications. The neutrophil lymphocyte ratio (NLR), C-reactive protein albumin (CRP/Alb) ratio, histological grade, T stage and modified N stage were integrated in the nomogram. The C-index of the nomogram for predicting the survival was 0.72, which showed better predictive ability of OS than the 6(th) or 7(th) TNM stages in the primary cohort (P < 0.001). The calibration curve showed high consistency between the nomogram and actual observation. The decision curve analysis showed more potential of clinical application of the prediction models compared with TNM staging system. Moreover, our findings were supported by the validation cohort. The proposed nomogram showed more accurate prognostic prediction for patients with ESCC after radical esophagectomy.