Immune related adverse events and treatment discontinuation in patients older and younger than 75 years with advanced melanoma receiving nivolumab or pembrolizumab

BackgroundProgrammed cell-death 1 antibodies (PD-1 Ab) improve overall survival (OS) for patients with advanced melanoma in trials; however, safety data in patients ≥75 years are lacking. The prognostic significance of and risk factors for PD-1 Ab discontinuation due immune related adverse events (irAE) are also uncertain.MethodsPatients with advanced melanoma receiving frontline PD-1 Ab at British Columbia Cancer outside of clinical trials between 10/2015–10/2019 were retrospectively analyzed. The incidence and subtypes of irAE were compared between age subgroups <75 and ≥ 75 years. Univariable logistic regression identified variables associated with treatment discontinuation within four months of PD-1 Ab initiation. Cox proportional hazard regression models were used to determine factors significantly associated with OS.Results302 patients were identified, of whom 126 (41.7%) were ≥ 75 years. During all follow-up, 15.9% of patients experienced irAE grade 3/4 and 27.2% of the cohort stopped PD-1 Ab due to immune toxicity. irAE incidence, hospitalization, and need for steroids by the four-month landmark were similar amongst age groups. Advanced age was not associated with risk of PD-1 Ab discontinuation from irAE on logistic regression. For the entire cohort, pre-treatment factors associated with shorter OS on multivariable analysis were ECOG performance status ≥1, M1d stage, lactate dehydrogenase >224, and neutrophil/ lymphocyte ratio ≥ 5. On four-month landmark multivariable analysis, treatment discontinuation due to irAE was significantly associated with worse OS.ConclusionPatients aged ≥75 years experienced similar irAE rates and treatment discontinuation for immune toxicity compared to younger patients. As PD-1 Ab discontinuation due to irAE was associated with shorter OS, efforts to treat irAE early are warranted to potentially avoid therapy cessation.     

Mendelian randomization as a tool to gain insights into the mosaic causes of autoimmune diseases

Autoimmune diseases (ADs) are a broad range of disorders which are characterized by long-term inflammation and tissue damage arising from an immune response against one's own tissues. It is now widely accepted that the causes of ADs include environmental factors, genetic susceptibility and immune dysregulation. However, the exact etiology of ADs has not been fully elucidated to date. Because observational studies are plagued by confounding factors and reverse causality, no firm conclusions can be drawn about the etiology of ADs. Over the years, Mendelian randomization (MR) analysis has come into focus, offering unique perspectives and insights into the etiology of ADs and promising the discovery of potential therapeutic interventions. In MR analysis, genetic variation (alleles are randomly dispensed during meiosis, usually irrespective of environmental or lifestyle factors) is used instead of modifiable exposure to explore the link between exposure factors and disease or other outcomes. Therefore, MR analysis can provide a valuable method for exploring the causal relationship between different risk factors and ADs when its inherent assumptions and limitations are fully considered. This review summarized the recent findings of MR in major ADs, including systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), multiple sclerosis (MS), and type 1 diabetes mellitus (T1DM), focused on the effects of different risk factors on ADs risks. In addition, we also discussed the opportunities and challenges of MR methods in ADs research.     

Value of Assessment of Different Neoplasias in the Adnexa in the Differential Diagnosis of Malignant Ovarian Tumor and Benign Ovarian Tumor: A Meta-analysis

To evaluate the accuracy of the assessment of different neoplasias in the adnexa (ADNEX) model in the differential diagnosis of malignant and benign ovarian tumors, the optimal cutoff value and the accuracy in diagnosing ovarian tumors at different stages, PubMed, Web of Science and Cochrane Library databases were retrieved to search literature with per-patient analysis until publication of the last study in November 2021. STATA 14.1, Meta-Disc 1.4 and Revman software 5.3 were used in the performance of meta-analysis. To explore sources of heterogeneity, a subgroup analysis was conducted for the ADNEX model. The pooled sensitivity, specificity, diagnostic odds ratio, positive likelihood, negative likelihood ratio and area under the summary receiver operating characteristic curve were 0.91 (95% confidence interval [CI]: 0.89–0.93), 0.84 (95% CI: 0.80–0.88), 55.55 (95% CI: 40.47–76.26), 5.71 (95% CI: 4.49–7.26), 0.10 (95% CI: 0.08–0.13) and 0.94 (95% CI: 0.92–0.96) in differentiating benign and malignant ovarian tumors, respectively. The area under the curve in identifying benign, borderline, stage I and stages II–IV were 0.93, 0.73, 0.27 and 0.92. The ADNEX model had high diagnostic performance was influential in the diagnosis of benign and stage II–IV ovarian tumors.     

Deep Phenotyping and Prediction of Long-term Cardiovascular Disease: Optimized by Machine Learning

BackgroundPrediction of cardiovascular disease (CVD) is important in clinical practice. Machine learning (ML) may offer an improved alternative to current CVD risk stratification in individual patients. We aim to identify important predictors and compare ML models with traditional models according to their prediction performance in a large long-term follow-up cohort.MethodsThe Atherosclerosis Risk in Communities (ARIC) study was designed to study the progression of subclinical disease to cardiovascular events over a 25-year follow-up period. All phenotypic variables at visit 1 were obtained. All-cause death, CVD, and coronary heart disease were the outcomes for analysis. The ML framework involved variable selection using the random survival forest (RSF) method, model building, and 5-fold cross-validation. Model performance was evaluated by discrimination using the Harrell concordance index (C-index), accuracy using the Brier score (BS), and interpretability using the number of variables in the model.ResultsOf the 14,842 participants in ARIC, the average age was 54.2 years, with 45.2% male and 26.2% Black participants. Thirty-eight unique variables were selected in the RSF top 20 importance ranking of all 6 outcomes. Aging, hypertension, glucose metabolism, renal function, coagulation, adiposity, and sodium retention dominated the predictions of all outcomes. The ML models outperformed the regression models and established risk scores with a higher C-index, lower BS, and varied interpretability.ConclusionsThe ML framework is useful for identifying important predictors of CVD and for developing models with robust performance compared with existing risk models.     

Impact of Bifrontal Home-Based Transcranial Direct Current Stimulation in Pain Catastrophizing and Disability due to Pain in Fibromyalgia: A Randomized,Double-Blind Sham-Controlled Study

This randomized, double-blind trial tested the hypothesis that 20 sessions of home-based anodal(a)-transcranial direct current stimulation (tDCS) (2mA for 20 minutes) bifrontal, with anodal on the left dorsolateral prefrontal cortex (l-DLPFC) would be better than sham-(s)-tDCS to reduce scores on Pain Catastrophizing Scale and disability-related to pain assessed by the Profile of Chronic Pain: Screen (primary outcomes). Secondary outcomes were depressive symptoms, sleep quality, heat pain threshold , heat pain tolerance , and serum brain-derived-neurotrophic-factor (BDNF). Forty-eight women with fibromyalgia, 30 to 65 years-old were randomized into 2:1 groups [a-tDCS (n = 32) or s-tDCS (n = 16)]. Post hoc analysis revealed that a-tDCS reduced the Pain Catastrophizing Scale total scores by 51.38% compared to 26.96% in s-tDCS, and a-tDCS reduced Profile of Chronic Pain: Screen total scores by 31.43% compared to 19.15% in s-tDCS. The a-tDCS improved depressive symptoms, sleep quality and increased the heat pain tolerance. The delta-value in the serum BDNF (mean post treatment end minus pretreatment) was conversely correlated with the a-tDCS effect in pain catastrophizing. In contrast, the a-tDCS impact on reducing the disability-related to pain at the treatment end was positively associated with a reduction in the serum BDNF and improvement of depressive symptoms, sleep quality and pain catastrophizing symptoms.PerspectiveHome-based bifrontal tDCS with a-tDCS on the l-DLPFC are associated with a moderate effect size (ES) in the following outcomes: 1) Decreased rumination and magnification of pain catastrophizing. 2) Improved the disability for daily activities due to fibromyalgia symptoms. Overall, these findings support the feasibility of self-applied home-based tDCS on DLPFC to improve fibromyalgia symptoms.     

Induction of tumor cell autosis by myxoma virus-infected CAR-T and TCR-T cells to overcome primary and acquired resistance

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Computer-Aided Diagnosis of Vertebral Compression Fractures Using Convolutional Neural Networks and Radiomics

Journal of Digital Imaging - Vertebral Compression Fracture (VCF) occurs when the vertebral body partially collapses under the action of compressive forces. Non-traumatic VCFs can be secondary to...     

The effectiveness of humanoid diagram teaching strategy on care capacity and retention in novice nurses

AimTo examine the effectiveness of a Humanoid Diagram Teaching Strategy (HDTS) on care capabilities and retention of novice nurses.BackgroundGuiding novice nurses in clinical practice is a matter of concern and the use of diagrams in assisting the learning process and to promote learning efficiency has been acknowledged.DesignThis is a quasi-experimental study with asynchronous repeated measurements for the experimental and control groups.MethodsThe study was conducted in a medical centre in southern Taiwan with 24 novice nurses. The intervention, Humanoid Diagrams Teaching Strategy, contained three parts: the head and neck; trunk; and limbs. The HDTS was applied three time weekly. Each session lasted approximately 30 min and the training lasted 4 weeks. The effectiveness of HDTS was measured using Mini-CEX, CbD and retention rates in the 3rd and 6th months of novice nurses’ experience.ResultsAfter the HDTS, although increases in mini-CEX and CbD scores in the experimental group were greater than the control group, these differences were not statistically significant after considering the time interaction. But the 3rd month and 6th month novice nurses’ retention rates were statistically significantly different by comparing the differences under the time interaction effects in both groups.ConclusionsThe Humanoid Diagram Teaching Strategy is an effective tool for preceptors to use in assisting novice nurses in learning, improving their nursing care knowledge and technical skills and to increase their retention rate.