Tree-based subgroup discovery using electronic health record data: heterogeneity of treatment effects for DTG-containing therapies.

The rich longitudinal individual level data available from electronic health records (EHRs) can be used to examine treatment effect heterogeneity. However, estimating treatment effects using EHR data poses several challenges, including time-varying confounding, repeated and temporally non-aligned measurements of covariates, treatment assignments and outcomes, and loss-to-follow-up due to dropout. Here, we develop the subgroup discovery for longitudinal data algorithm, a tree-based algorithm for discovering subgroups with heterogeneous treatment effects using longitudinal data by combining the generalized interaction tree algorithm, a general data-driven method for subgroup discovery, with longitudinal targeted maximum likelihood estimation. We apply the algorithm to EHR data to discover subgroups of people living with human immunodeficiency virus who are at higher risk of weight gain when receiving dolutegravir (DTG)-containing antiretroviral therapies (ARTs) versus when receiving non-DTG-containing ARTs.

Impact of Subgroup Distribution on Seasonality of Human Respiratory Syncytial Virus: A Global Systematic Analysis.

BACKGROUND: Previous studies reported inconsistent findings regarding the association between respiratory syncytial virus (RSV) subgroup distribution and timing of RSV season. We aimed to further understand the association by conducting a global-level systematic analysis. METHODS: We compiled published data on RSV seasonality through a systematic literature review, and unpublished data shared by international collaborators. Using annual cumulative proportion (ACP) of RSV-positive cases, we defined RSV season onset and offset as ACP reaching 10% and 90%, respectively. Linear regression models accounting for meteorological factors were constructed to analyze the association of proportion of RSV-A with the corresponding RSV season onset and offset. RESULTS: We included 36 study sites from 20 countries, providing data for 179 study-years in 1995-2019. Globally, RSV subgroup distribution was not significantly associated with RSV season onset or offset globally, except for RSV season offset in the tropics in 1 model, possibly by chance. Models that included RSV subgroup distribution and meteorological factors explained only 2%-4% of the variations in timing of RSV season. CONCLUSIONS: Year-on-year variations in RSV season onset and offset are not well explained by RSV subgroup distribution or meteorological factors. Factors including population susceptibility, mobility, and viral interference should be examined in future studies.

Identifying subgroups of eating behavior traits unrelated to obesity using functional connectivity and feature representation learning.

Eating behavior is highly heterogeneous across individuals and cannot be fully explained using only the degree of obesity. We utilized unsupervised machine learning and functional connectivity measures to explore the heterogeneity of eating behaviors measured by a self-assessment instrument using 424 healthy adults (mean ± standard deviation [SD] age = 47.07 ± 18.89 years; 67% female). We generated low-dimensional representations of functional connectivity using resting-state functional magnetic resonance imaging and estimated latent features using the feature representation capabilities of an autoencoder by nonlinearly compressing the functional connectivity information. The clustering approaches applied to latent features identified three distinct subgroups. The subgroups exhibited different levels of hunger traits, while their body mass indices were comparable. The results were replicated in an independent dataset consisting of 212 participants (mean ± SD age = 38.97 ± 19.80 years; 35% female). The model interpretation technique of integrated gradients revealed that the between-group differences in the integrated gradient maps were associated with functional reorganization in heteromodal association and limbic cortices and reward-related subcortical structures such as the accumbens, amygdala, and caudate. The cognitive decoding analysis revealed that these systems are associated with reward- and emotion-related systems. Our findings provide insights into the macroscopic brain organization of eating behavior-related subgroups independent of obesity.

Benefit of adjuvant chemotherapy in lymph node-negative, T1b and T1c triple-negative breast cancer.

INTRODUCTION: Current guidelines recommendations regarding chemotherapy in small (T1b and T1c), node-negative triple-negative breast cancer (TNBC) differ due to lack of high-quality data. Our study aimed to assess the benefit of adjuvant chemotherapy in patients with T1bN0M0 and T1cN0M0 TNBC. METHODS: We obtained data from the Surveillance, Epidemiology, and End Results database for patients with node-negative, T1b/T1c TNBC diagnosed between 2010 and 2020. Logistic regresion models assessed variables associated with chemotherapy administration. We evaluated the effect of chemotherapy on overall survival (OS) and breast cancer specific survival (BCSS) with Kaplan-Meier methods and Cox proportional hazards methods. RESULTS: We included 11,510 patients: 3,388 with T1b and 8,122 with T1c TNBC. During a median follow-up of 66 months, 305 patients with T1b and 995 with T1c died. After adjusting for clinicopathological, demographic and treatment factors, adjuvant chemotherapy improved OS in T1b TNBC (HR, 0.52; 95% CI, 0.41-0.68 p < 0.001) but did not improve BCSS (HR, 0.70; 95% CI, 0.45-1.07; p = 0.10); the association between chemotherapy and BCSS was not statistically significant in any subgroup. In T1c TNBC, adjuvant chemotherapy improved OS (HR, 0.54; 95% CI, 0.47-0.62; p < 0.001) and BCSS (HR, 0.79; 95% CI, 0.63-0.99; p = 0.043); the benefit of chemotherapy in OS varied by age (Pinteraction=0.024); moreover, the benefit in BCSS was similar in all subgroups. CONCLUSIONS: Our study results support the use of adjuvant chemotherapy in patients with node-negative, T1c TNBC. Patients with node-negative, T1b TNBC had excellent long-term outcomes; furthermore, chemotherapy was not associated with improved BCSS in these patients.

miR-155 facilitates the synergistic replication between avian leukosis virus subgroup J and reticuloendotheliosis virus by targeting a dual pathway.

IMPORTANCE: The synergy of two oncogenic retroviruses is an essential phenomenon in nature. The synergistic replication of ALV-J and REV in poultry flocks increases immunosuppression and pathogenicity, extends the tumor spectrum, and accelerates viral evolution, causing substantial economic losses to the poultry industry. However, the mechanism of synergistic replication between ALV-J and REV is still incompletely elusive. We observed that microRNA-155 targets a dual pathway, PRKCI-MAPK8 and TIMP3-MMP2, interacting with the U3 region of ALV-J and REV, enabling synergistic replication. This work gives us new targets to modulate ALV-J and REV's synergistic replication, guiding future research on the mechanism.

Efficacy and safety of dolutegravir/lamivudine in virologically suppressed female participants: week 48 data from the pooled TANGO and SALSA studies.

OBJECTIVES: Women represent >50% of people with HIV globally but have historically been underrepresented in clinical trials. We evaluated the efficacy and safety of switching to dolutegravir/lamivudine (DTG/3TC) vs continuing their current antiretroviral regimen (CAR) by sex assigned at birth (female and male) in virologically suppressed adults with HIV-1 without prior virological failure in a pooled analysis of two randomized controlled trials. METHODS: This analysis included 48-week data from the phase 3 TANGO and SALSA studies. Primary and key secondary endpoints included proportions of participants with HIV-1 RNA ≥50 and <50 copies/mL at week 48, respectively. Safety was also assessed. RESULTS: Of 1234 participants, 250 (DTG/3TC, n = 133; CAR, n = 117) were female at birth. Week 48 proportions of participants with Snapshot HIV-1 RNA ≥50 copies/mL were similar regardless of sex at birth (DTG/3TC vs CAR: female, <1% [1/133] vs 2% [2/117]; male, <1% [1/482] vs <1% [3/502]). Proportions with HIV-1 RNA <50 copies/mL were high across sexes and treatment groups (DTG/3TC vs CAR: female, 91% [121/133] vs 89% [104/117]; male, 94% [455/482] vs 94% [471/502]). Immunological response with DTG/3TC was slightly higher in female participants. Incidences of adverse events leading to withdrawal and serious adverse events were low and comparable between treatment groups and across sexes. Weight gain was higher with DTG/3TC than with CAR among female participants aged ≥50 years (treatment difference 2.08 kg [95% confidence interval 0.40-3.75]). CONCLUSIONS: Results confirm the robustness of DTG/3TC as a switch option in virologically suppressed females with HIV-1, with outcomes similar to those in males.

Impact of Removal of Lymph Nodes on Survival in Stage I-III Gastric Signet-Ring Cell Cancer: The More, the Better?

BACKGROUND: There is an ongoing debate over the prognostic value of the number of examined lymph nodes (ELNs) in cases of gastric signet-ring cell cancer (GSRCC). In this study, we sought to evaluate the correlation between the number of ELNs and the prognosis of GSRCC and identify the optimal number of ELNs. METHODS: A total of 1020 patients diagnosed with GSRCC between 2011 and 2018 in the National Cancer Center database were identified. Clinicopathological characteristics were retrospectively collected, and optimal cutoff values of ELNs were calculated by using X-tile. The impact of different ELNs on overall survival (OS) was compared by using Kaplan-Meier curves. We used univariate and multivariate Cox and subgroup analyses to explore the relationship between ELNs and OS. Furthermore, nonlinear correlations were investigated by using restricted cubic splines (RCSs). RESULTS: X-tile showed that the optimal cutoff value of ELNs was 22. The 5-year OS was higher for patients with ELNs > 22 (vs. ELNs ≤ 22, 66.9% vs. 74.9%, P = 0.026). Multivariate Cox analyses showed that high ELNs were associated with superior OS (hazard ratio = 0.56, 95% confidence interval 0.43-0.74, P < 0.001). In subgroup analyses, the significant association between tumor size > 4 cm, and TNM III stage was still observed. The RCS regression model showed a U-shaped dose-response nonlinear relationship between ELNs and OS; the inflection point, as well as the lowest risk points, corresponded to 44-52 ELNs. CONCLUSIONS: A U-shaped, nonlinear correlation with inflection points of 44-52 ELNs between ELNs and prognosis in GSRCC was identified.

Efficacy Assessment of Post-nephrectomy Adjuvant Therapies in Patients with Renal Cell Carcinoma.

OBJECTIVE: The objective of our study was to integrate the efficacy results of post-nephrectomy adjuvant therapies in renal cell carcinoma (RCC) patients with risk of recurrence, and attempt to determine the optimal intervention choice. METHODS: We performed standard meta-analysis procedures in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The PubMed, Embase, and Cochrane Library databases were searched from inception to 22 September 2022. Randomized controlled trials reporting overall survival (OS) or disease-free survival (DFS) of adjuvant therapies, including immune checkpoint inhibitors (ICIs) and targeted therapies, in adult post-nephrectomy RCC patients were eligible for inclusion. RESULTS: Seven studies involving 7548 participants were included in our analyses. In contrast with placebo, DFS benefit with ICIs was only observed in female RCC patients and RCC patients with high programmed death-ligand 1 (PD-L1) expression (≥ 1%), sarcomatoid features, and M0 intermediate-high risk. Network meta-analyses demonstrated that pembrolizumab exhibited both DFS and OS benefit compared with placebo, sunitinib, sorafenib, and girentuximab, and only DFS benefit compared with atezolizumab and nivolumab plus ipilimumab. CONCLUSIONS: Our results suggest that post-nephrectomy RCC patients with sarcomatoid differentiation and high PD-L1 expression were more responsive to ICIs. Furthermore, pembrolizumab monotherapy exhibited superior DFS and OS results over other adjuvant therapies.

Macrophage migration inhibitory factor: A noval biomarker upregulates in myasthenia gravis and correlates with disease severity and relapse.

OBJECTIVE: To explore the relationship between macrophage migration inhibitory factor (MIF) and disease severity and relapse in patients with myasthenia gravis (MG). METHODS: 145 MG patients including 79 new-onset patients, 30 remission patients and 36 relapse patients were enrolled in this study. The detailed characteristics of all enrolled MG patients were routinely recorded, including gender, age, type, MGFA classification, antibody, thymic status, clinical score, treatment, MGFA-PIS and B cell subsets (memory B cells, plasmablast cells and plasma cells) detected by flow cytometry. Serum MIF levels were measured by enzyme-linked immunosorbent assay (ELISA) kit. The correlation of MIF levels with clinical subtypes, disease severity and B cell subsets were investigated. Moreover, logistic regression analysis was applied to assess the factors affecting relapse of generalized MG (GMG). RESULTS: Serum MIF levels were higher in new-onset MG patients than those in controls and were positively associated with QMG score, MGFA classification and memory B cells. Subgroup analysis revealed that MIF levels were increased in GMG patients than in ocular MG (OMG), as well as elevated in MGFA III/IV compared with MGFA I/II. With the remission of the disease, the expression of serum MIF decreased. The multivariate logistic regression models indicated that high MIF and thymoma was a risk factor for relapse of GMG, and rituximab could prevent disease relapse. CONCLUSIONS: MIF can be used as a novel biomarker to reflect disease severity and predict disease relapse in MG patients.

Temporal change of DNA methylation subclasses between matched newly diagnosed and recurrent glioblastoma.

The longitudinal transition of phenotypes is pivotal in glioblastoma treatment resistance and DNA methylation emerged as an important tool for classifying glioblastoma phenotypes. We aimed to characterize DNA methylation subclass heterogeneity during progression and assess its clinical impact. Matched tissues from 47 glioblastoma patients were subjected to DNA methylation profiling, including CpG-site alterations, tissue and serum deconvolution, mass spectrometry, and immunoassay. Effects of clinical characteristics on temporal changes and outcomes were studied. Among 47 patients, 8 (17.0%) had non-matching classifications at recurrence. In the remaining 39 cases, 28.2% showed dominant DNA methylation subclass transitions, with 72.7% being a mesenchymal subclass. In general, glioblastomas with a subclass transition showed upregulated metabolic processes. Newly diagnosed glioblastomas with mesenchymal transition displayed increased stem cell-like states and decreased immune components at diagnosis and exhibited elevated immune signatures and cytokine levels in serum. In contrast, tissue of recurrent glioblastomas with mesenchymal transition showed increased immune components but decreased stem cell-like states. Survival analyses revealed comparable outcomes for patients with and without subclass transitions. This study demonstrates a temporal heterogeneity of DNA methylation subclasses in 28.2% of glioblastomas, not impacting patient survival. Changes in cell state composition associated with subclass transition may be crucial for recurrent glioblastoma targeted therapies.

Difelikefalin in Black/African American Hemodialysis Patients with Moderate-to-Severe Pruritus: Post hoc Analysis of KALM-1 and KALM-2.

INTRODUCTION: Black and African American (AA) people are over-represented in the kidney failure population; therefore, the safety and efficacy of difelikefalin in Black/AA patients was evaluated. METHODS: This was a post hoc, pooled exploratory subgroup analysis of the Phase 3 KALM-1 and -2 studies. Patients undergoing hemodialysis (HD) who had moderate-to-severe chronic kidney disease-associated pruritus (CKD-aP) at enrollment were stratified into self-reported Black/AA or White subgroups. Patients were randomized (1:1) to receive intravenous (IV) difelikefalin 0.5 µg/kg or placebo for 12 weeks. Difelikefalin efficacy was assessed with validated patient-reported outcome questionnaires: 24-h Worst Itch Numerical Rating Scale (WI-NRS), 5-D itch, and Skindex­10. RESULTS: There were 249 (29.3%) patients from the KALM studies that self-identified as Black/AA (n = 135 difelikefalin; n = 114 placebo). Clinically meaningful (≥3-point) reduction in WI-NRS score was achieved by 47.9% of Black/AA patients with difelikefalin versus 24.6% with placebo (p < 0.001). More Black/AA patients achieved a ≥5-point 5-D itch total improvement (54.9% vs. 35.7%; p = 0.013) and a ≥15-point Skindex-10 score improvement with difelikefalin versus placebo (49.0% vs. 28.9%; p = 0.006) compared with White patients. Incidence of treatment-emergent adverse events (TEAEs) was higher for Black/AA patients (difelikefalin: 78.5%; placebo: 70.8%) versus White patients (difelikefalin: 64.8%; placebo: 61.8%). CONCLUSION: In this post hoc analysis, difelikefalin was efficacious in the Black/AA population and had an acceptable safety profile.

COVID-19 in three waves in a tertiary referral hospital in Belgium: a comparison of patient characteristics, management, and outcome.

PURPOSE: Few studies have compared patient characteristics, clinical management, and outcome of patients with COVID-19 between the different epidemic waves. In this study, we describe patient characteristics, treatment, and outcome of patients admitted for COVID-19 in the Antwerp University Hospital over the first three epidemic waves of 2020-2021. METHODS: Retrospective observational study of COVID-19 patients in a Belgian tertiary referral hospital. All adult patients with COVID-19, hospitalized between February 29, 2020, and June 30, 2021, were included. Standardized routine medical data was collected from patient records. Risk factors were assessed with multivariable logistic regression. RESULTS: We included 722 patients, during the first (n = 179), second (n = 347) and third (n = 194) wave. We observed the lowest disease severity at admission during the first wave, and more elderly and comorbid patients during the second wave. Throughout the subsequent waves we observed an increasing use of corticosteroids and high-flow oxygen therapy. In spite of increasing number of complications throughout the subsequent waves, mortality decreased each wave (16.6%,15.6% 11.9% in 1st, 2nd and 3rd wave respectively). C-reactive protein above 150 mg/L was predictive for the need for intensive care unit admission (odds ratio (OR) 3.77, 95% confidence interval (CI) 2.32-6.15). A Charlson comorbidity index ≥ 5 (OR 5.68, 95% CI 2.54-12.70) and interhospital transfers (OR 3.78, 95% CI 2.05-6.98) were associated with a higher mortality. CONCLUSIONS: We observed a reduction in mortality each wave, despite increasing comorbidity. Evolutions in patient management such as high-flow oxygen therapy on regular wards and corticosteroid use may explain this favorable evolution.

Efficient testing of the biomarker positive and negative subgroups in a biomarker-stratified trial.

In many randomized placebo-controlled trials with a biomarker defined subgroup, it is believed that this subgroup has the same or higher treatment effect compared with its complement. These subgroups are often referred to as the biomarker positive and negative subgroups. Most biomarker-stratified pivotal trials are aimed at demonstrating a significant treatment effect either in the biomarker positive subgroup or in the overall population. A major shortcoming of this approach is that the treatment can be declared effective in the overall population even though it has no effect in the biomarker negative subgroup. We use the isotonic assumption about the treatment effects in the two subgroups to construct an efficient way to test for a treatment effect in both the biomarker positive and negative subgroups. A substantial reduction in the required sample size for such a trial compared with existing methods makes evaluating the treatment effect in both the biomarker positive and negative subgroups feasible in pivotal trials especially when the prevalence of the biomarker positive subgroup is less than 0.5.

Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data.

In this paper, we review recent advances in statistical methods for the evaluation of the heterogeneity of treatment effects (HTE), including subgroup identification and estimation of individualized treatment regimens, from randomized clinical trials and observational studies. We identify several types of approaches using the features introduced in Lipkovich et al (Stat Med 2017;36: 136-196) that distinguish the recommended principled methods from basic methods for HTE evaluation that typically rely on rules of thumb and general guidelines (the methods are often referred to as common practices). We discuss the advantages and disadvantages of various principled methods as well as common measures for evaluating their performance. We use simulated data and a case study based on a historical clinical trial to illustrate several new approaches to HTE evaluation.

Finding the best subgroup with differential treatment effect with multiple outcomes.

Precision medicine aims to identify specific patient subgroups that may benefit the most from a particular treatment than the whole population. Existing definitions for the best subgroup in subgroup analysis are based on a single outcome and do not consider multiple outcomes; specifically, outcomes of different types. In this article, we introduce a definition for the best subgroup under a multiple-outcome setting with continuous, binary, and censored time-to-event outcomes. Our definition provides a trade-off between the subgroup size and the conditional average treatment effects (CATE) in the subgroup with respect to each of the outcomes while taking the relative contribution of the outcomes into account. We conduct simulations to illustrate the proposed definition. By examining the outcomes of urinary tract infection and renal scarring in the RIVUR clinical trial, we identify a subgroup of children that would benefit the most from long-term antimicrobial prophylaxis.

A unified Bayesian framework for bias adjustment in multiple comparisons from clinical trials.

In clinical trials, multiple comparisons arising from various treatments/doses, subgroups, or endpoints are common. Typically, trial teams focus on the comparison showing the largest observed treatment effect, often involving a specific treatment pair and endpoint within a subgroup. These findings frequently lead to follow-up pivotal studies, many of which do not confirm the initial positive results. Selection bias occurs when the most promising treatment, subgroup, or endpoint is chosen for further development, potentially skewing subsequent investigations. Such bias can be defined as the deviation in the observed treatment effects from the underlying truth. In this article, we propose a general and unified Bayesian framework to address selection bias in clinical trials with multiple comparisons. Our approach does not require a priori specification of a parametric distribution for the prior, offering a more flexible and generalized solution. The proposed method facilitates a more accurate interpretation of clinical trial results by adjusting for such selection bias. Through simulation studies, we compared several methods and demonstrated their superior performance over the normal shrinkage estimator. We recommended the use of Bayesian Model Averaging estimator averaging over Gaussian Mixture Models as the prior distribution based on its performance and flexibility. We applied the method to a multicenter, randomized, double-blind, placebo-controlled study investigating the cardiovascular effects of dulaglutide.

In-depth analysis of data from the RAS-ALS study reveals new insights in rasagiline treatment for amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: In 2016, we concluded a randomized controlled trial testing 1 mg rasagiline per day add-on to standard therapy in 252 amyotrophic lateral sclerosis (ALS) patients. This article aims at better characterizing ALS patients who could possibly benefit from rasagiline by reporting new subgroup analysis and genetic data. METHODS: We performed further exploratory in-depth analyses of the study population and investigated the relevance of single nucleotide polymorphisms (SNPs) related to the dopaminergic system. RESULTS: Placebo-treated patients with very slow disease progression (loss of Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised [ALSFRS-R] per month before randomization of ≤0.328 points) showed a per se survival probability after 24 months of 0.85 (95% confidence interval = 0.65-0.94). The large group of intermediate to fast progressing ALS patients showed a prolonged survival in the rasagiline group compared to placebo after 6 and 12 months (p = 0.02, p = 0.04), and a reduced decline of ALSFRS-R after 18 months (p = 0.049). SNP genotypes in the MAOB gene and DRD2 gene did not show clear associations with rasagiline treatment effects. CONCLUSIONS: These results underline the need to consider individual disease progression at baseline in future ALS studies. Very slow disease progressors compromise the statistical power of studies with treatment durations of 12-18 months using clinical endpoints. Analysis of MAOB and DRD2 SNPs revealed no clear relationship to any outcome parameter. More insights are expected from future studies elucidating whether patients with DRD2CC genotype (Rs2283265) show a pronounced benefit from treatment with rasagiline, pointing to the opportunities precision medicine could open up for ALS patients in the future.

Different subtypes of chronic fatigue in childhood cancer survivors: A DCCSS LATER study.

INTRODUCTION: The aim of the current study was to investigate whether subtypes of chronic fatigue (CF) can be identified in childhood cancer survivors (CCS), and if so, to determine the characteristics of participants with a specific subtype. METHODS: Participants were included from the nationwide DCCSS LATER cohort. The Checklist Individual Strength (CIS) was completed to assess fatigue. Participants with CF (scored ≥35 on the fatigue severity subscale and indicated to suffer from fatigue for ≥6 months) were divided into subgroups using two-step cluster analysis based on the CIS concentration, motivation, and physical activity subscales. Differences between groups on demographics, psychosocial, lifestyle, and treatment-related variables were determined using ANOVA and chi-square analyses (univariable) and multinomial regression analysis (multivariable). RESULTS: A total of 1910 participants participated in the current study (n = 450 with CF; n = 1460 without CF). Three CF subgroups were identified: Subgroup 1 (n = 133, 29% of participants) had CF with problems in physical activity; Subgroup 2 (n = 111, 25% of participants) had CF with difficulty concentrating; and Subgroup 3 (n = 206, 46% of participants) had multi-dimensional CF. Compared to Subgroup 1, Subgroup 2 more often reported sleep problems, limitations in social functioning, and less often have more than two comorbidities. Subgroup 3 more often reported depression, sleep problems, a lower self-esteem, and limitations in social functioning and a lower educational level compared to Subgroup 1. CONCLUSION: Different subgroups of CCS with CF can be identified based on fatigue dimensions physical activity, motivation and concentration. Results suggest that different intervention strategies, tailored for each subgroup, might be beneficial.

Waistline to thigh circumference ratio as a predictor of MAFLD: a health care worker study with 2-year follow-up.

BACKGROUND: This study aimed to determine whether the waist-to-thigh ratio (WTTR) is associated with the incidence of metabolic-associated fatty liver disease (MAFLD) in health care workers. METHODS: There were 4517 health care workers with baseline data and results from 2 follow-up examinations. We divided the subjects into 3 groups according to baseline WTTR and used the Cox hazard regression model to estimate MAFLD risk. RESULTS: The WTTRs were categorized by tertiles at baseline using the values 1.58 and 1.66. Patients with higher WTTR tended to have significantly greater values for the following factors, body mass index (BMI), fasting blood glucose (FPG), systolic blood pressure, diastolic blood pressure, total cholesterol (TC), triglycerides (TG), low-density lipoprotein-cholesterol (LDL-C) and neck circumference. The incidence of MAFLD significantly increased with increasing WTTR tertiles (5.74%, 12.75% and 22.25% for the first, second and third tertiles, respectively, P < 0.05 for trend). Kaplan-Meier(K-M) survival analysis revealed a significant tendency towards increased MAFLD risk with increasing WTTR tertile. In the fully adjusted model, the hazard ratios (95% CIs) for MAFLD in the second, third WTTR tertiles compared with the first quartile were 2.17(1.58,2.98), 3.63(2.70,4.89), respectively, third neck circumference tertiles compared with the first quartile were 2.84(1.89,4.25), 8.95(6.00,13.35), respectively. Compared with those of individuals with a BMI > 23 kg/m2, the associations between WTTR and MAFLD incidence were more pronounced in subjects with a BMI < 23 kg/m2. Similarly, the difference in neck circumference was more pronounced in these patients with a BMI < 23 kg/m2. CONCLUSIONS: Our results revealed that the WTTR is an independent risk factor for MAFLD, and there was a dose‒response relationship between the WTTR and MAFLD risk. The neck circumference was significantly different in subjects with a BMI < 23 kg/m2. This approach provides a new way to predict the incidence rate of MAFLD.

Rapid detection of human adenovirus subgroup B using recombinase polymerase amplification assay.

Human adenovirus subgroup B (HAdV B) is one of the major pathogens of human respiratory virus infections, which has considerable transmission and morbidity in a variety of populations. Therefore, rapid and specific detection of HAdV B in clinical samples is essential for diagnosis. This study aimed to develop a product for rapid nucleic acid detection of HAdV B using recombinase polymerase amplification assay (RPA) and validate the performance of this method by using clinical samples. Results showed that this method achieved a lower limit of detection (LOD) of 10 copies/µL and had no cross-reactivity with other adenovirus subgroups or respiratory pathogens. In addition to high sensitivity, it can be completed within 30 min at 40 °C. There is no need to perform nucleic acid extraction on clinical samples. Taking qPCR as the gold standard, the RPA assay possessed a high concordance (Cohen's kappa, 0.896; 95% CI 0.808-0.984; P < 0.001), with a sensitivity of 87.80% and a specificity of 100.00%. The RPA assay developed in this study provided a simple and highly specific method, making it an important tool for rapid adenovirus nucleic acid detection and facilitating large-scale population screening in resource-limited settings.