Programmed death 1 (PD-1) and PD ligand 1 (PD-L1) inhibitors have demonstrated varying effectiveness in treating esophageal or gastric/gastroesophageal junction (G/GEJ) cancer. Hence, this systematic review and meta-analysis evaluated the efficacy and safety of anti-PD-1/PD-L1 treatment in patients with esophageal or G/GEJ cancer by analyzing the types of medications. Randomized controlled trials comparing anti-PD-1/PD-L1 to control therapy were identified by searching PubMed, EMBASE, and ClinicalTrials.gov. The outcomes included overall survival (OS), progression-free survival (PFS) rates, and serious adverse events (SAEs), evaluating the differences in therapy types, including a comparison between PD-1 and PD-L1 inhibitors. Eight studies were included in the analysis. PD-1/PD-L1 inhibitors affected the overall OS rate increment without influencing the PFS rate (HR, 0.837; 95% CI, 0.753–0.929; p = 0.001; HR 0.991; 95% CI, 0.778–1.263; p = 0.942, respectively). Anti-PD-1 was significantly more beneficial for increasing OS and PFS than PD-L1 inhibitors. Anti-PD-1 and PD-L1 use was not significantly associated with SAE development in esophageal or G/GEJ cancer patients. PD-1/PD-L1 inhibitor use was associated with improved OS and PFS rate increase among PD-1 and PD-L1 inhibitors. Considering response variations to anti-PD-1/PD-L1 usage, more individualized treatments should be introduced in clinical practice.

To investigate the effect of sodium-glucose cotransporter 2 (SGLT-2) inhibitors and glucagon-like peptide 1 (GLP-1) agonists on glycemic variability (GV), the mean amplitude of glucose excursion (MAGE), mean blood glucose (MBG) levels, and percentage of time maintaining euglycemia were evaluated. Randomized controlled trials evaluating the efficacy of SGLT-2 inhibitors and GLP-1 agonists for treating people with diabetes were selected through searches of PubMed, EMBASE, and other databases. Sixteen studies were finally analyzed. There were no differences in the reductions in MAGE after treatment with SGLT-2 inhibitors or GLP-1 agonists (standardized mean difference (SMD) = −0.59, 95% CI = −0.82 to −0.36 vs. SMD = −0.43, 95% CI = −0.51 to −0.35, respectively), and treatment with SGLT-2 inhibitors was associated with an increased reduction in MBG levels (SMD = −0.56, 95% CI = −0.65 to −0.48, p < 0.00001). Monotherapy and add-on therapy with medications were correlated with MAGE and MBG level reductions. In conclusion, SGLT-2 inhibitors and GLP-1 agonists were associated with a reduction in GV and could be alternatives for treating people with diabetes.

Highly prevalent hepatitis B and hepatitis C virus (HBV and HCV) infections have been reported among individuals with diabetes. Given the frequently asymptomatic nature of hepatitis and the challenges associated with screening in some vulnerable populations such as diabetes patients, we conducted an investigation into the performance of various machine learning models for the identification of hepatitis in diabetic patients while also evaluating the significance of features. Analyzing NHANES data from 2013 to 2018, machine learning models were evaluated; random forest (RF), support vector machine (SVM), eXtreme Gradient Boosting (XGBoost), and least absolute shrinkage and selection operator (LASSO) along with stacked ensemble model. We performed hyperparameter tuning to improve the performance of the model, and selected important predictors using the best performance model. LASSO showed the highest predictive performance (AUC-ROC = 0.810) rather than other models. Illicit drug use, poverty, and race were highly ranked as predictive factors for developing hepatitis in diabetes patients. Our study demonstrated that a machine-learning-based model performed optimally in the detection of hepatitis among diabetes patients, achieving high performance. Furthermore, models and predictors evaluated from the current study, we expect, could be supportive information for developing screening or treatment methods for hepatitis care in diabetes patients.

This study aimed to identify the development of hepatitis B or C infection in diabetes patients compared to those without and to elucidate factors associated with the prevalence of hepatitis B or C infection in diabetes. We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) 2013–2018. As evaluation factors, we included variables such as age, race, illicit drug use, and poverty. The diabetic group had a significantly higher prevalence of hepatitis B or C infection than the non-diabetic group (odds ratio (OR) = 1.73; 95% confidence interval (CI), 1.36–2.21, p < 0.01). In multivariate Cox regression, non-poverty and non-illicit drug use were lower risk factors contributing to hepatitis development in diabetes (hazard ratio (HR) = 0.50; 95% CI, 0.32–0.79, p < 0.01, and HR = 0.05; 95% CI, 0.03–0.08, p < 0.01, respectively). Logistic regression also showed that these factors were significant contributors to hepatitis development in the diabetic group (p < 0.01). In patients with diabetes, the development of hepatitis was higher than that in those without, and hepatitis development was influenced by poverty and illicit drug use. This may provide supporting evidence of response strategies for diabetes to care for hepatitis development in advance.

Objectives: We conducted a meta-analysis of recently published randomized controlled trials (RCTs) to identify the most effective and safe etanercept dosing regimen and duration of therapy for the treatment of patients with ankylosing spondylitis (AS).Methods: We systematically reviewed PubMed, Embase, Cochrane Library, and Web of Science databases for RCTs. The proportion of patients attaining 20 percent improvement (according to the Spondyloarthritis International Society response criteria [ASAS 20]) was evaluated as a primary outcome. Secondary outcomes included 50 percent increase in the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI 50) used for evaluating efficacy, as well as the BASDAI/Bath Ankylosing Spondylitis Functional Index (BASFI) scores and adverse events.Results: ASAS 20 indicated that the efficacy of etanercept did not differ amongst dosing regimens (25 mg twice-weekly versus 50 mg once-weekly: relative risk [RR], 2.18, 95 percent confidence interval [CI], 1.78–2.67 versus RR, 2.00, 95 percent CI, 1.70–2.37). The ASAS 20 reported subgroup differences among treatment durations of less than 12 weeks (RR, 2.70; 95 percent CI, 2.09–3.49); 12 weeks (RR, 1.74; 95 percent CI, 1.37–2.22); and more than 12 weeks (RR, 2.56; 95 percent CI, 1.88–3.48). Other outcomes included BASDAI, BASDAI 50, and BASFI. Drug safety differed according to the treatment regimen and duration.Conclusion: Our meta-analysis found that there was no significant efficacy difference between 50 mg once-weekly and 25 mg twice-weekly dosing for the treatment of AS, and a dosing duration of less than 12 weeks was more effective for treating AS patients.

Clinical audits are essential to ensure that clinical research processes align with regulatory standards and best practices. Despite this, there has been no error assessment of the relationship between the errors in investigational medicinal product (IMP) management and clinical trial workers with audit experience. This study surveyed stakeholders with experience being audited to evaluate errors in IMP management and accountability during clinical trials through online survey system. The survey focused on errors in IMP export, dosing, storage, shipping, and labeling. Errors related to IMP management or accountability were evaluated with 22 specific criteria. Analysis included descriptive statistics and Pearson’s correlation. A total of 41 participants experiencing audits in clinical trial were enrolled in the current survey. The survey results revealed that the most frequent errors occurred in missing essential documents for shipment during IMP shipping and errors in label information, each accounting for 24 cases (58%). Additionally, a significant correlation was found between participants’ age, work experience, and audit experience (coefficient = 0.77, p value < 0.05). A survey of individuals with auditing experience identified common errors in IMP management, particularly missing shipment documents and incorrect labeling. To address these issues, clinical trial systems should implement regular error monitoring, standardized procedures, and comprehensive staff training to ensure safer and more efficient trials.