Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials

AIMS/HYPOTHESIS

The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events.

METHODS

Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed.

RESULTS

For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period.

CONCLUSIONS/INTERPRETATION

Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk.

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.

Posterior open wound healing in immediate implant placement using reactive soft tissue versus absorbable collagen sponge: a retrospective cohort study

The soft and hard tissue healing of open wounds in immediate implant placement are yet to be explored. The aim of this study was to compare the clinical outcomes of open wound healing using reactive soft tissue (RST) and absorbable collagen sponge (ACS). Forty implants placed immediately in posterior sockets were included; autologous RST was used in 20 and ACS substitute was used in 20. Soft tissue healing was primarily assessed through a novel scoring system and the evaluation of gingival recession. The horizontal bone width (HBW) and interproximal marginal bone level (MBL) were measured on radiographs to observe the hard tissue healing. No significant difference in total soft tissue healing score was observed at 2 weeks postoperatively. Notably, the ACS group showed better tissue colour (P = 0.016) but worse fibrous repair (P = 0.043) scores than the RST group. Gingival recession levels were comparable in the two groups, both before tooth extraction and after placement of the restoration. Regarding hard tissue, HBW and MBL changes showed no intergroup differences. Within the limitations of this study, both RST and ACS seemed effective for open wound closure, achieving ideal soft and hard tissue healing in immediate implant placement.

[Challenges and optimization strategies for clinical research and the development of new drugs for liver fibrosis]

Liver fibrosis is a key step in the developmental process of various chronic liver diseases, including cirrhosis. Therefore, the focus and difficulty of liver disease research have always been on how to reverse liver fibrosis. However, due to complex mechanisms, difficulties in endpoint evaluation, a lack of non-invasive diagnostic methods, and other factors, the research and development of new drugs are hindered and lengthy. Currently, some new drugs are being researched and developed, which signifies the prospect is optimistic.

[Risk factors of cytomegalovirus infection in patients with failed corneal grafts]

Objective: To investigate the levels of cytomegalovirus (CMV) infection and associated risk factors in corneal transplant recipients who experienced transplant failure. Methods: This was a case-control study. Clinical data from 576 cases (576 eyes) of patients who underwent repeat corneal transplant surgery at the Department of Ophthalmology, Peking University Third Hospital, due to corneal transplant failure from January 2016 to May 2022 were collected. Of these, 305 were male and 271 were female, with a median age of 44.0 (0.7, 91.0) years. The CMV infection rate was analyzed based on the detection of CMV DNA in aqueous humor or corneal tissue during corneal transplant surgery. Patients were divided into the CMV group (CMV DNA positive) and the control group (herpes virus DNA negative). The main research indicators included the CMV infection rate, clinical characteristics, and risk factors in corneal transplant recipients. Chi-square tests and binary logistic analysis were used to compare differences between the two groups in general information, systemic diseases, ocular lesions, ocular surgical history, and local and systemic medications. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for each CMV infection risk factor. Results: The overall CMV infection rate was 21.9%(126/576), with annual rates ranging from 10.9% to 37.7% from 2016 to 2021. After applying inclusion and exclusion criteria, 378 patients were included in the control trial, with 126 in the CMV group and 252 in the control group. Statistically significant differences between the two groups were observed in systemic immune-related corneal lesions [CMV group: 38 (30.2%), control group: 26 (10.3%)], local immune and inflammatory corneal lesions [CMV group: 46 (36.5%), control group: 40 (15.9%)], congenital corneal opacity [CMV group: 46 (36.5%), control group: 48 (19.0%)] total number of corneal transplants (CMV group: 178 times, control group: 276 times), corneal deep neovascularization crossing the graft [CMV group: 104 (82.5%), control group: 68 (27.0%)] and severe opacity [CMV group: 44 (34.9%), control group: 30 (11.0%)]. Binary logistic regression analysis showed that systemic immune-related corneal lesions (OR=4.044, 95%CI 1.810-9.033, P<0.001), local immune and inflammatory corneal lesions (OR=3.554, 95%CI 1.569-8.052, P=0.002), congenital corneal opacity (OR=2.606, 95%CI 1.216-5.589, P=0.014), total number of corneal transplants (OR=3.206, 95%CI 1.753-5.864, P<0.001), corneal deep neovascularization crossing the graft (OR=8.347, 95%CI 3.967-17.559, P<0.001), and severe opacity (OR=3.063, 95%CI 1.221-7.682, P=0.017) were independent risk factors for CMV infection after corneal transplant. Conclusions: CMV infection was present in more than 1/5 of corneal transplant recipients who experienced transplant failure. CMV infection after corneal transplant may be related to immune rejection reactions and ocular inflammatory responses. Inflammatory corneal lesions associated with systemic or local immune abnormalities, congenital corneal opacity, and multiple corneal transplants may exacerbate the levels of inflammatory factors during the perioperative period of corneal transplant, increasing the risk of post-transplant CMV infection, leading to the infiltration of deep neovascularization and severe opacity in the cornea.

[Analysis of the awareness rate and correlates of core information on tuberculosis prevention and control in elderly in Chinese]

Objective: To understand the awareness and influencing factors of core information on tuberculosis prevention and control in the elderly population in China. Methods: The study included all participants aged ≥60 from the "13th Five-Year" National Tuberculosis Control Plan end-term assessment in 2020, with 13 706 valid questionnaires obtained. Multivariate logistic regression was used to analyze the influencing factors of the awareness rate of core information on tuberculosis prevention and control in the elderly. Results: The total awareness rate of core information on tuberculosis prevention and control in the elderly aged ≥60 was 78.4%, with the highest for "suspicious symptoms of pulmonary tuberculosis" (85.4%) and the lowest for "whether pulmonary tuberculosis can be cured" (65.3%). The complete awareness rate of core information on tuberculosis prevention and control in the elderly was 41.3%, and the proportion of those who received tuberculosis health education is 67.6%. Multivariate logistic regression analysis results showed that factors associated with low awareness of core information included females (OR=0.93, 95%CI: 0.86-1.00), ages 70- (OR=0.91, 95%CI: 0.84-0.98) and ≥80 (OR=0.77, 95%CI: 0.68-0.87) and minority ethnicity (OR=0.85, 95%CI: 0.74-0.99). Factors associated with high awareness of core information included educational levels of junior high school (OR=1.46, 95%CI: 1.34-1.58), high school (OR=1.62, 95%CI: 1.45-1.81), junior college (OR=1.37, 95%CI: 1.11-1.68), and an undergraduate degree or higher (OR=1.52, 95%CI: 1.09-2.11), and receiving tuberculosis health education (OR=2.13, 95%CI: 1.97-2.27). Conclusions: In 2020, the awareness rate of core information on tuberculosis prevention and control in Chinese older adults aged ≥60 was lower than the national planning target. Therefore, there should be an increased focus on health education about tuberculosis for elderly females, those aged ≥70, ethnic minorities, and those with lower education levels.

CITIES: Clinical trials with intercurrent events simulator

Although clinical trials are often designed with randomization and well-controlled protocols, complications will inevitably arise in the presence of intercurrent events (ICEs) such as treatment discontinuation. These can lead to missing outcome data and possibly confounding causal inference when the missingness is a function of a latent stratification of patients defined by intermediate outcomes. The pharmaceutical industry has been focused on developing new methods that can yield pertinent causal inferences in trials with ICEs. However, it is difficult to compare the properties of different methods developed in this endeavor as real-life clinical trial data cannot be easily shared to provide benchmark data sets. Furthermore, different methods consider distinct assumptions for the underlying data-generating mechanisms, and simulation studies often are customized to specific situations or methods. We develop a novel, general simulation model and corresponding Shiny application in R for clinical trials with ICEs, aptly named the Clinical Trials with Intercurrent Events Simulator (CITIES). It is formulated under the Rubin Causal Model where the considered treatment effects account for ICEs in clinical trials with repeated measures. CITIES facilitates the effective generation of data that resemble real-life clinical trials with respect to their reported summary statistics, without requiring the use of the original trial data. We illustrate the utility of CITIES via two case studies involving real-life clinical trials that demonstrate how CITIES provides a comprehensive tool for practitioners in the pharmaceutical industry to compare methods for the analysis of clinical trials with ICEs on identical, benchmark settings that resemble real-life trials.

Non-monotone Exponential Time (NEXT) Model for the Longitudinal Trend of a Continuous Outcome in Clinical Trials

The dose-response curve has been studied extensively for decades. However, most of these methods ignore intermediate measurements of the response variable and only use the measurement at the endpoint. In early phase trials, it is crucial to utilize all available data due to the smaller sample size. Simulation studies have shown that the longitudinal dose-response surface model provides a more precise parameter estimation compared to the traditional dose response using only data from the primary time point. However, the current longitudinal models with parametric assumptions assume the treatment effect increases monotonically over time, which may be controversial to reality. We propose a parametric non-monotone exponential time (NEXT) model, an enhanced longitudinal dose-response model with greater flexibility, capable of accommodating non-monotonic treatment effects and making predictions for longer-term efficacy. In addition, the estimator for the time to maximum treatment effect and its asymptotic distribution have been derived from NEXT. Extensive simulation studies using known data-generating models and using real clinical data showed the NEXT model outperformed the existing monotone longitudinal models.

Predicting coronary artery disease by carotid color doppler ultrasonography

OBJECTIVE

In this study, the color ultrasound indicators of carotid atherosclerosis (CAS) intima-media thickness (IMT) and atherosclerotic plaque (AP) were retrospectively analyzed for the prediction of CHD with the help of compressed speckle denoising.

PATIENTS AND METHODS

A total of 248 patients with suspected coronary atherosclerosis admitted to the Department of Cardiovascular Medicine of The First Affiliated Hospital of Harbin Medical University from August 2020 to January 2022 were retrospectively recruited as research subjects.

RESULTS

The plaque detection rate (71.83%), IMT (1.26 ± 0.75) mm, and plaque index (PI) (2.31 ± 0.95) in the Obs group were greatly higher. The IMT and PI values in the patients with two CALs were superior to those in patients with a single CAL, and the IMT and PI values in the patients with three CALs were higher than those in patients with two CALs, illustrating considerable differences between the two groups (p < 0.05). The predictive sensitivity of IMT combined with AP was higher than that of IMT and AP (p < 0.05), and the predictive specificity of AP results was markedly inferior to that of IMT and IMT combined with AP (p < 0.05).

CONCLUSIONS

The ultrasound examination of CAS had obvious predictive value for the occurrence and disease severity of CHD. The higher the IMT and AP, the higher the incidence and severity of CAD.

CT-based radiomics for prediction of pulmonary haemorrhage after percutaneous CT-guided transthoracic lung biopsy of pulmonary nodules

AIM

To evaluate the feasibility of intranodular and perinodular computed tomography (CT) radiomics features for predicting the occurrence of pulmonary haemorrhage after percutaneous CT-guided transthoracic lung biopsy (PCTLB) in pulmonary nodules.

MATERIALS AND METHODS

The data for 332 patients with pulmonary nodules who underwent PCTLB were reviewed retrospectively. Pulmonary haemorrhage after PCTLB was evaluated using CT (144 cases occurred). Radiomics features based on gross nodular (GNV) and perinodular volumes (PNV) were extracted from pre-biopsy CT images and features selection using least absolute shrinkage and selection operator (LASSO) regression, and three radiomics scores (rad-scores) were built. Rad-scores, clinical, and clinical-radiomic models were developed and evaluated to predict the occurrence of pulmonary haemorrhage.

RESULTS

Five, five, and six significant features were selected for prediction of pulmonary haemorrhage based on GNV, PNV, and GNV + PNV, respectively. Lesion depth was the only clinical characteristics related to pulmonary haemorrhage. Lesion depth and rad-score based on GNV, PNV, and GNV + PNV for predicting the pulmonary haemorrhage achieved areas under the curves (AUCs) of 0.656, 0.645, 0.651, and 0.635 in the validation group, respectively. Three clinical-radiomic models improved the AUCs to 0.743, 0.723, and 0.748. The performance of rad-score_GNV + PNV combined with lesion depth outperformed the clinical model (p=0.024) and the radiomics signature (p=0.038). In addition, the radiomics signatures were significantly associated with higher-grade pulmonary haemorrhage (p<0.05).

CONCLUSIONS

Radiomics features from intranodular and perinodular regions of pulmonary nodules have good predictive ability for pulmonary haemorrhage after PCTLB, which may provide additional predictive value for clinical practice.

Prevalence and influencing factors of depressive and anxiety symptoms among hospital-based healthcare workers during the surge period of the COVID-19 pandemic in the Chinese mainland: a multicenter cross-sectional study

BACKGROUND

From November 2022 to February 2023, the Chinese mainland experienced a surge in COVID-19 infection and hospitalization, and the hospital-based healthcare workers (HCWs) might suffer serious psychological crisis during this period. This study aims to assess the depressive and anxiety symptoms among HCWs during the surge of COVID-19 pandemic and to provide possible reference on protecting mental health of HCWs in future infectious disease outbreaks.

METHODS

A multicenter cross-sectional study was carried out among hospital-based HCWs in the Chinese mainland from 5 January to 9 February 2023. The PHQ-9 (nine-item Patient Health Questionnaire) and GAD-7 (seven-item Generalized Anxiety Disorder Questionnaire) were used to measure depressive and anxiety symptoms. Ordinal logistic regression analysis was performed to identify influencing factors.

RESULTS

A total of 6522 hospital-based HCWs in the Chinse mainland were included in this survey. The prevalence of depressive symptoms among the HCWs was 70.75%, and anxiety symptoms was 47.87%. The HCWs who perceived higher risk of COVID-19 infection and those who had higher work intensity were more likely to experience depressive and anxiety symptoms. Additionally, higher levels of mindfulness, resilience and perceived social support were negatively associated with depressive and anxiety symptoms.

CONCLUSION

This study revealed that a high proportion of HCWs in the Chinese mainland suffered from mental health disturbances during the surge of the COVID-19 pandemic. Resilience, mindfulness and perceived social support are important protective factors of HCWs' mental health. Tailored interventions, such as mindfulness practice, should be implemented to alleviate psychological symptoms of HCWs during the COVID-19 pandemic or other similar events in the future.

Longitudinal Microbiome Changes in Supragingival Biofilm Transcriptomes Induced by Orthodontics

INTRODUCTION

Common oral diseases are known to be associated with dysbiotic shifts in the supragingival microbiome, yet most oral microbiome associations with clinical end points emanate from cross-sectional studies. Orthodontic treatment is an elective procedure that can be exploited to prospectively examine clinically relevant longitudinal changes in the composition and function of the supragingival microbiome.

METHODS

A longitudinal cohort study was conducted among 24 adolescent orthodontic patients who underwent saliva and plaque sampling and clinical examinations at time points: before fixed appliance bonding and at 1, 6, and 12 wk thereafter. Clinical indices included bleeding on probing (BOP), mean gingival index (GI), probing depths (PDs), and plaque index (PI). To study the biologically (i.e., transcriptionally) active microbial communities, RNA was extracted from plaque and saliva for RNA sequencing and microbiome bioinformatics analysis. Longitudinal changes in microbiome beta diversity were examined using PERMANOVA tests, and the relative abundance of microbial taxa was measured using Kruskal-Wallis tests, Wilcoxon rank-sum tests, and negative binomial and zero-inflated mixed models.

RESULTS

Clinical measures of oral health deteriorated over time-the proportion of sites with GI and PI ≥1 increased by over 70% between prebonding and 12 wk postbonding while the proportion of sites with PD ≥4 mm increased 2.5-fold. Streptococcus sanguinis, a health-associated species that antagonizes cariogenic pathogens, showed a lasting decrease in relative abundance during orthodontic treatment. Contrarily, caries- and periodontal disease-associated taxa, including Selenomonas sputigena, Leptotrichia wadei, and Lachnoanaerobaculum saburreum, increased in abundance after bonding. Relative abundances of Stomatobaculum longum and Mogibacterium diversum in prebonding saliva predicted elevated BOP 12 wk postbonding, whereas Neisseria subflava was associated with lower BOP.

CONCLUSIONS

This study offers insights into longitudinal community and species-specific changes in the supragingival microbiome transcriptome during fixed orthodontic treatment, advancing our understanding of microbial dysbioses and identifying targets of future health-promoting clinical investigations.

KNOWLEDGE TRANSFER STATEMENT

Bonding braces was associated with subsequent changes in the oral microbiome characterized by increases in disease-associated species, decreases in health-associated species, and worsened clinical measures of oral health.

High Dose Hyperfractionated Thoracic Radiotherapy vs. Standard Dose for Limited Stage Small-Cell Lung Cancer: A Multicenter, Open-Label Randomized, Phase 3 Trial

PURPOSE/OBJECTIVE(S)

Limited stage small-cell lung cancer (LS-SCLC) is associated with poor prognosis. We aimed to assess the efficacy and safety of high-dose, hyperfractionated thoracic radiotherapy of 54 Gy in 30 fractions compared with standard dose (45 Gy in 30 fractions) as a first-line treatment for LS-SCLC.

MATERIALS/METHODS

The study was an open-label, randomized, phase 3 trial, done at 16 public hospitals in China. Key inclusion criteria were patients aged 18-70 years, with previously histologically or cytologically confirmed LS-SCLC, previously untreated or received 1-2 courses of intravenous cisplatin (75 mg/m²of body-surface area, on day 1 or divided into two days of each cycle) or carboplatin (area under the curve of 5 mg/mL per min, day 1 of each cycle)and intravenous etoposide (100 mg/m²of body-surface area, on days 1-3 of each cycle), and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-1.Eligible patients were randomly assigned (1:1) to receive volumetric-modulated arc radiotherapy (VMAT) of 45 Gy in 30 fractions or the simultaneous integrated boost VMAT (SIB-VMAT) of 54 Gy in 30 fractions to the primary lung tumor and lymph node metastases starting 0-42 days after the first chemotherapy course. Both groups of patients received thoracic radiotherapy twice per day and 10 fractions per week. Prophylactic cranial radiation (PCI, 25 Gy in 10 fractions) was implemented to patients with responsive disease. The primary endpoint was overall survival. Safety was analyzed in the as-treated population.

RESULTS

Between June 30, 2017, and April 6, 2021, 224 eligible patients were enrolled and randomly assigned to 54 Gy (n = 108) or 45 Gy (n = 116). Median follow-up for the primary analysis was 45 months (IQR 41-48). Median overall survival was significantly improved in the 54 Gy group (62.4 months) compared with the 45 Gy group (43.1 months; p = 0.001). Median progression-free survival was significantly improved in the 54 Gy group (30.5 months) compared with the 45 Gy group (16.7 months; p = 0.044). The most common grade 3-4 adverse events were neutropenia (30 [28%] of 108 patients in the 54 Gy group vs 27 [23%] of 116 patients in the 45 Gy group), neutropenic infections (6 [6%] vs 2 [2%]), thrombocytopenia (13 [12%] vs 12 [10%]), anemia (6 [6%] vs 4 [3%]), and esophagitis (1 [1%] vs 3 [3%]). Treatment-related serious adverse events occurred in 9 [8%] patients in the 54 Gy group and 16 [14%] patients in the 45 Gy group. There were one treatment-related deaths in 54 Gy group (myocardial infarction).

CONCLUSION

Compared with standard thoracic radiotherapy dose of 45 Gy, the high dose of 54 Gy improved overall survival and progression-free survival without increasing toxicities in patients with LS-SCLC, supporting twice-daily hyperfractionated thoracic radiotherapy of 54 Gy with concurrent chemotherapy is an alternative treatment option for LS-SCLC. This study is complete and registered with ClinicalTrials.gov, NCT03214003.

Feasibility of Omitting Contralateral Neck Irradiation in Patients with Node-Negative Sinonasal Squamous Cell Carcinoma Crossing the Midline

PURPOSE/OBJECTIVE(S)

This study aims to analyze the nodal target volume in patients with node-negative SNSCC crossing the midline.

MATERIALS/METHODS

One hundred and four patients with node-negative advanced sinonasal squamous cell carcinoma (SNSCC) crossing the midline were included. Survival rates were estimated and compared between treatment groups.

RESULTS

Sixty-four patients received contralateral ENI (contralateral ENI group), while forty patients did not (non-contralateral ENI group). The median follow-up time was 89.99 and 95.01 months in the contralateral and non-contralateral ENI groups, respectively. At 5 years, the regional relapse-free survival and contralateral regional relapse-free survival were 57.68% vs. 55.83% (p = 0.372), and 57.68% vs. 61.62% (p = 0.541), in contralateral ENI group vs. non-contralateral ENI group, respectively. Five-year overall survival, local relapse-free survival, and distant metastasis-free survival were similar in the two groups (all p > 0.05).

CONCLUSION

In patients with node-negative SNSCC crossing the midline, omission of contralateral ENI did not affect regional control and survival outcomes on the premise of receiving ipsilateral ENI covering at least levels Ib and II.

[Prediction of 1p/19q codeletion status in diffuse lower-grade glioma using multimodal MRI radiomics]

OBJECTIVE

To develop a noninvasive method for prediction of 1p/19q codeletion in diffuse lower-grade glioma (DLGG) based on multimodal magnetic resonance imaging (MRI) radiomics.

METHODS

We collected MRI data from 104 patients with pathologically confirmed DLGG between October, 2015 and September, 2022. A total of 535 radiomics features were extracted from T₂WI, T₁WI, FLAIR, CE-T₁WI and DWI, including 70 morphological features, 90 first order features, and 375 texture features. We constructed logistic regression (LR), logistic regression least absolute shrinkage and selection operator (LRlasso), support vector machine (SVM) and Linear Discriminant Analysis (LDA) radiomics models and compared their predictive performance after 10-fold cross validation. The MRI images were reviewed by two radiologists independently for predicting the 1p/19q status. Receiver operating characteristic curves were used to evaluate classification performance of the radiomics models and the radiologists.

RESULTS

The 4 radiomics models (LR, LRlasso, SVM and LDA) achieved similar area under the curve (AUC) in the validation dataset (0.833, 0.819, 0.824 and 0.819, respectively; P>0.1), and their predictive performance was all superior to that of resident physicians of radiology (AUC=0.645, P=0.011, 0.022, 0.016, 0.030, respectively) and similar to that of attending physicians of radiology (AUC=0.838, P>0.05).

CONCLUSION

Multiparametric MRI radiomics models show good performance for noninvasive prediction of 1p/19q codeletion status in patients with in diffuse lower-grade glioma.

Analysis of a Binary Outcome Dichotomized from an Underlying Continuous Variable in Clinical Trials

Binary-valued outcome is often seen in many clinical trials across therapeutic areas. It is not uncommon that such binary endpoints are derived from a continuous variable. For example, in diabetes clinical trials, the proportion of patients with HbA1c< 7% is often investigated as one of the key objectives, where HbA1c is a continuous-valued variable reflecting the averaged blood glucose value from the previous three months. Most of the time, if not all, the mean of those binary endpoints were estimated directly through the binary variable defined by the corresponding cutoff. Alternatively, by the nature of the derivation, that quantity could also be estimated by leveraging the density of the underlying continuous variable and computing the area under the density curve up to a threshold. This paper provides a few methods in relation to density estimation. Extensive simulation studies were conducted based on real clinical trial data to compare these estimation approaches against the direct estimation of the proportions. Simulation results showed that the density estimation approaches in general benefited from a smaller mean squared error in early phase studies where the sample size is limited. The density estimation approach is certainly expected to introduce bias, however, a favorable bias-variance trade-off may make these approaches attractive in early phase studies.

[Research advances on the role and mechanism of chitosan-based wound dressing in wound healing]

The skin is the first barrier to maintain the stability of internal environment of the body and resist harmful factors of external environment, and is easily damaged because of various external factors. When full-thickness skin defects reach a certain level, it is difficult for the skin to repair itself, so wound dressings are needed to promote wound healing. Seeking an ideal dressing that can promote wound healing has long been a hot research topic. Chitosan is a unique biopolysaccharide polymer with good biocompatibility, biodegradability, antibacterial activity, and thermal stability, which has great potential in the development and application of wound dressings. Based on the introduction of properties of chitosan, this article reviews the role and mechanism of chitosan-based wound dressings in wound healing, and summarizes the hemostatic effect, antibacterial effect, delivery effect, and tissue regeneration promotion effect of chitosan, aiming to provide a certain reference for the research and development of new chitosan-based wound dressings in the future.

[Advances of pathological diagnosis of lung cancer based on clinical needs]

Pathological diagnosis of lung cancer keep updating and developing, in order to meet the clinical needs in the era of precision medicine. It mainly involves the advances of histological subtype classification, molecular testing for targeted therapy, biomarkers detection for immunotherapy and the pathological evaluation for neoadjuvant therapy. Nowadays, pathological diagnosis of lung cancer present a multidisciplinary model including clinical medicine, radiology and pathology. It is gradually moving towards standardization with expection to provide better guidance for clinical treatment and prognosis.

Accurate Collection of Reasons for Treatment Discontinuation to Better Define Estimands in Clinical Trials

BACKGROUND

Reasons for treatment discontinuation are important not only to understand the benefit and risk profile of experimental treatments, but also to help choose appropriate strategies to handle intercurrent events in defining estimands. The current case report form (CRF) commonly in use mixes the underlying reasons for treatment discontinuation and who makes the decision for treatment discontinuation, often resulting in an inaccurate collection of reasons for treatment discontinuation.

METHODS AND RESULTS

We systematically reviewed and analyzed treatment discontinuation data from nine phase 2 and phase 3 studies for insulin peglispro. A total of 857 participants with treatment discontinuation were included in the analysis. Our review suggested that, due to the vague multiple-choice options for treatment discontinuation present in the CRF, different reasons were sometimes recorded for the same underlying reason for treatment discontinuation. Based on our review and analysis, we suggest an intermediate solution and a more systematic way to improve the current CRF for treatment discontinuations.

CONCLUSION

This research provides insight and directions on how to optimize the CRF for recording treatment discontinuation. Further work needs to be done to build the learning into Clinical Data Interchange Standards Consortium standards.

CLINICAL TRIALS

Clinicaltrials.gov numbers: NCT01027871 (Phase 2 for type 2 diabetes), NCT01049412 (Phase 2 for type 1 diabetes), NCT01481779 (IMAGINE 1 Study), NCT01435616 (IMAGINE 2 Study), NCT01454284 (IMAGINE 3 Study), NCT01468987 (IMAGINE 4 Study), NCT01582451 (IMAGINE 5 Study), NCT01790438 (IMAGINE 6 Study), NCT01792284 (IMAGINE 7 Study).

[Longitudinal correlation between cell phone use and sleep quality in college students]

Objective: To investigate the current situation of cell phone use and sleep quality among college students, establish a sleep quality trajectory model and explore the influence of cell phone use on the sleep quality trajectory. Methods: Based on data from the College Student Behavior and Health Cohort Study 2019-2020, a latent class growth modeling was used to establish a sleep quality trajectory model among college students. The baseline influencing factors of sleep quality trajectories among college students were analyzed by χ² test, and the effects of cell phone use on sleep quality trajectories were analyzed by binary logistic regression. Results: A total of 1 092 college students were included in the analysis. The detection rates of cell phone use and poor sleep quality were 24.5% and 13.3%. Latent class growth model identified two groups of sleep quality trend trajactories: an improved sleep quality group (86.0%) and a decreased sleep quality group (14.0%). The result of binary logistic regression showed that the cell phone use was a risk factor of sleep quality trajectories. Conclusion: The cell phone use during college period could increase the risk of poor sleep quality. Targeted intervention measures about cell phone use should be adopted to improve the sleep quality among college students.

[Long-term outcomes and failure patterns of definitive radiotherapy for cervical esophageal carcinoma]

Objective: To evaluate the long-term outcomes, failure patterns and prognostic factors of definitive radiotherapy in patients with cervical esophageal carcinoma (CEC). Methods: We retrospectively reviewed the clinical data of 148 CEC patients who treated with definitive radiotherapy in Cancer Hospital of Chinese Academy of Medical Sciences from January 2001 to December 2017. The median radiation dose was 66 Gy (59.4-70 Gy) and 33.1% of patients received concurrent chemotherapy. The Kaplan-Meier method was used to calculate survival rates. The log rank test was used for survival comparison and univariate prognostic analysis. The Cox model was used for multivariate prognostic analysis. Results: The median follow-up time was 102.6 months. The median survival time, 2- and 5-year overall survival (OS) were 22.7 months, 49.9% and 28.3%. The median, 2- and 5-year progression-free survival were 12.6 months, 35.8% and 25.8%. The 2- and 5-year locoregional recurrence-free survival were 59.1% and 50.8%. The 2- and 5-year distant metastases-free survival were 74.6% and 65.9%. Multivariate analysis showed that EQD(2)>66 Gy was the only independent prognostic indicator for OS (P=0.040). The median survival time and 5-year OS rate significantly improved in patients who received EQD(2)>66 Gy than those who received≤66 Gy (31.2 months vs. 19.2 months, 40.1% vs. 19.1%, P=0.027). A total of 87 patients (58.8%) developed tumor progression. There were 50 (33.8%), 23 (15.5%) and 39 (26.4%) patients developed local, regional recurrence and distant metastases, respectively. Eleven patients (7.4%) underwent salvage surgery, and the laryngeal preservation rate for entire group was 93.9%. Conclusions: Definitive radiotherapy is an effective treatment for cervical esophageal carcinoma with the advantage of larynx preservation. Local recurrence is the major failure pattern. EQD(2)>66 Gy is associated with the improved overall survival.

Using principal stratification in analysis of clinical trials

The ICH E9(R1) addendum (2019) proposed principal stratification (PS) as one of five strategies for dealing with intercurrent events. Therefore, understanding the strengths, limitations, and assumptions of PS is important for the broad community of clinical trialists. Many approaches have been developed under the general framework of PS in different areas of research, including experimental and observational studies. These diverse applications have utilized a diverse set of tools and assumptions. Thus, need exists to present these approaches in a unifying manner. The goal of this tutorial is threefold. First, we provide a coherent and unifying description of PS. Second, we emphasize that estimation of effects within PS relies on strong assumptions and we thoroughly examine the consequences of these assumptions to understand in which situations certain assumptions are reasonable. Finally, we provide an overview of a variety of key methods for PS analysis and use a real clinical trial example to illustrate them. Examples of code for implementation of some of these approaches are given in Supplemental Materials.

Physical activity patterns, genetic susceptibility, and risk of hip/knee osteoarthritis: a prospective cohort study based on the UK Biobank

OBJECTIVES

The effect of physical activity on hip/knee osteoarthritis (OA) and how it varies by genetic susceptibility to OA remains inconclusive.

METHODS

In a cohort study of UK Biobank, 436,166 OA-free participants were recruited in 2006-2010 and followed for knee/hip OA until the end of 2020. 28 physical activity-related items were collected at baseline. Cox regression was used to estimate associations between physical activity behaviors, as well as major activity patterns (i.e., significant principal components[PCs] identified by principal component analysis), and risk of OA, adjusting for multiple confounders. We further stratified the analyses by polygenic risk score (PRS) for OA to examine the impact of genetic susceptibility to OA on the studied association.

RESULTS

During a mean follow-up of 11.15 years, 13,227 hip and 21,119 knee OA cases were identified. 19, out of 28, studied items showed associations with increased OA risk. Compared with low adherence group(<1^st tertile of PC score for each pattern), individuals with high adherence to five identified patterns were associated with increased risk of OA. The moderate adherence to "strenuous sports"(HR = 0.93, 95%CI: 0.89-0.97) and "walking for pleasure"(HR = 0.93, 95%CI: 0.89-0.98) patterns was associated with reduced OA. Similar risk patterns were obtained in the stratified analysis by PRS levels for OA.

CONCLUSION

High intensity of most activity patterns were associated with increased OA. However, a protective effect was suggested for moderate adherence to patterns of "strenuous sports" and "walking for pleasure" that consistent across different genetic susceptibilities, underscoring the potential benefits of moderate-intensity physical activity on OA.

AB0390 COST-EFFECTIVENESS OF IGURATIMOD IN PATIENTS WITH RHEUMATOID ARTHRITIS (RA) BY USING A CLAIMS-BASED ALGORITHM: RETROSPECTIVE ANALYSIS OF REAL‑WORLD DATA

Background

Iguratimod (IGU), as one of the conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), has been approved by National Medical Products Administration (NMPA) to treat Rheumatoid arthritis (RA).

Objectives

This study aimed to compare the cost-effectiveness of well-established RA therapies using a claims-based algorithm in RA patients.

Methods

An electronic medical record (EMR) database from Zhujiang Hospital was utilized to estimate the cost-effectiveness of medication for RA patients, including IGU with MTX, biological DMARDs (bDMARDs) with MTX, and MTX alone for more than 6 months from 2014 to 2020. Patients who were deemed effective must meet all the following criteria according to the algorithm, high adherence; no bDMARDs or IGU switch or addition; no prescription of new csDMARDs; no increase in dose or frequency of index drug; no new use of chronic glucocorticoids or increase in glucocorticoid dose; and no more than one glucocorticoid injection. Average cost was calculated by summing total cost of effective treatment and dividing by number of patients achieving efficacy in each group.

Results

A total of 263 patients were included in the analysis. Based on a claims-based algorithm, the effective rate was 27.1 % (26/96) for IGU with MTX group, 11.2% (7/62) for bDMARDs with MTX group, and 13.3% (14/105) for MTX alone group, respectively. Average cost of effective treatment was $833.46 for IGU with MTX therapy, $2554.57 for bDMARDs with MTX therapy, and $171.48 for MTX alone (Table 1).

Table 1.

Effectiveness and Cost per Effectively Treated Patient with RA

CriteriaAll patients (n=263)IGU with MTX group(n=96)bDMARDs with MTX group (n=62)MTX (n=105)Effectiveness:no. of patients (%)a47(17.87%)26 (27.1%)7 (11.2/%)14 (13.3%)Cost of all RA-related medication per effectively treated patient(SD)$892.75(911.57)$833.46 (252.67)$2554.5 (1273.13)$171.4 (110.33)Average cost of all RA medications postindex (excluding biologic DMARDs) per patient (SD)b$146.38(114.60)$148.81 (123.12)$86.90 (74.53)$171.4 (110.33)Average cost of only biologicDMARDs postindex per patient (SD)b$746.38(926.35)$684.27(188.67)$2468.67(1285.91)/

a χ2showed significant difference in percentage effectiveness for the original algorithm (p<0.05).

bMedication cost was 2020 U.S. dollars.

Conclusion

IGU with MTX therapy was revealed to be both effective and modestly priced, which seemed to be a cost-effective strategy for RA therapy and warranted further cost-effectiveness investigation.

References

[1](2018) [2018 Chinese guideline for the diagnosis and treatment of rheumatoid arthritis]. Zhonghua Nei Ke Za Zhi 57 (4), 242-251. https://doi.org/10.3760/cma.j.issn.0578-1426.2018.04.004

[2]Hitchon, C. A., & El-Gabalawy, H. S. (2011). The synovium in rheumatoid arthritis. The open rheumatology journal, 5, 107–114. https://doi.org/10.2174/1874312901105010107

[3]Smolen, J. S., Landewé, R., Bijlsma, J., Burmester, G. R., Dougados, M., Kerschbaumer, A., McInnes, I. B., Sepriano, A., van Vollenhoven, R. F., de Wit, M., Aletaha, D., Aringer, M., Askling, J., Balsa, A., Boers, M., den Broeder, A. A., Buch, M. H., Buttgereit, F., Caporali, R., Cardiel, M. H., … van der Heijde, D. (2020). EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Annals of the rheumatic diseases, 79(6), 685–699. https://doi.org/10.1136/annrheumdis-2019-216655

[4]Fraenkel, L., Bathon, J. M., England, B. R., St Clair, E. W., Arayssi, T., Carandang, K., Deane, K. D., Genovese, M., Huston, K. K., Kerr, G., Kremer, J., Nakamura, M. C., Russell, L. A., Singh, J. A., Smith, B. J., Sparks, J. A., Venkatachalam, S., Weinblatt, M. E., Al-Gibbawi, M., Baker, J. F., … Akl, E. A. (2021). 2021 American College of Rheumatology Guideline for the Treatment of Rheumatoid Arthritis. Arthritis care & research, 73(7), 924–939. https://doi.org/10.1002/acr.24596

Disclosure of Interests

None declared

Impact of Using A Mixed Data Collection Modality on Statistical Inferences in Decentralized Clinical Trials

Background

Decentralized clinical trials offer the promise of reduced patient burden, faster and more diverse recruitment, and have received regulatory support during the COVID-19 pandemic. However, lack of data accuracy or data validation poses a challenge for fully decentralized trials. A mixed data collection modality where onsite measurements are collected at key time points and decentralized measurements are taken at intermediate time points is attractive operationally. To date, the impact of decentralized measurements (which could presumably be less accurate) taken at intermediate time points on statistical inference on the primary or other key time points has not been evaluated.

Methods

In this article we evaluate the estimation and statistical inference for three scenarios: (1) all onsite measurements, (2) a mixture of onsite and decentralized measurements, and (3) all decentralized measurements, in the setting of a chronic weight management trial. We consider scenarios where decentralized measurements have additional within- and between-subject variabilities and/or bias.

Results

In the mixed modality setting, simulation studies showed that the estimation and inference for the key time points with onsite measurements have good properties and are not impacted by the additional variability and bias from intermediate decentralized measurements. However, estimates for intermediate decentralized time points for the mixed modality and estimates for the all decentralized modality measurements have increased variability and bias.

Conclusion

Mixed modality trials can help achieve the benefits of decentralized clinical trials by reducing the number of onsite visits with little impact on statistical inferences for various estimands, compared to traditional (all onsite) clinical trials.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43441-022-00416-x.

Efficacy and safety of combination therapy with vildagliptin and metformin vs. metformin monotherapy for Type 2 Diabetes Mellitus therapy: a meta-analysis

OBJECTIVE

The aim is to assess the comparative efficacy and safety of combination therapy with vildagliptin and metformin vs. metformin monotherapy in the treatment of type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

We searched on PubMed, Cochrane Library, Web of Science, and Embase databases for randomized controlled trials (RCTs) of combination therapy with vildagliptin and metformin vs. metformin monotherapy in patients with T2DM published up to 30 February 2021. The Cochrane tool and Revman 5.3 software was used to assess the risk of bias and conducted the meta-analysis in the included RCTs. Evidence level was assessed by the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach.

RESULTS

A total of 11 RCTs and 8533 patients were included. For the efficacy, we found that combination therapy with vildagliptin and metformin (dose of metformin ≥1500mg/d) had a significantly higher reduction in hemoglobin A1c (HbA1c) [mean differences (MD)= -0.59, 95% CI (-0.28, -0.16), p<0.00001] and fasting plasma glucose (FPG) level [MD= -0.82, 95% CI (-1.09, -0.56), p<0.00001] than combination therapy with vildagliptin and metformin (dose of metformin <1500 mg/d). Vildagliptin plus metformin as combination therapy reduced body weight loss ratio [MD=0.22, 95% CI (0.17, 0.27), p<0.00001] when compared with metformin monotherapy. In terms of safety, the vildagliptin plus metformin as combination therapy did not increase risk of total adverse events (AEs) [RR=0.98, 95% CI (0.94,1.02), p=0.29], however there were significant statistical difference and did not increase the risk of diarrhea [RR=0.55, 95% CI (0.40, 0.76), p=0.0003] and Gastrointestinal (GI) disorders [RR=0.72, 95% CI (0.58, 0.91), p=0.006], but significantly increased risk of dizziness [RR=1.41, 95% CI (1.06, 1.88), p=0.02] when compared with metformin monotherapy.

CONCLUSIONS

Compared with metformin, vildagliptin combined with metformin could significantly reduce FPG, HbA1c and body weight. When the dose of metformin in the combination group of vildagliptin and metformin is ≥1500mg/d, the results showed significant reduction in HbA1c and FPG. In addition, it had no risk of increase in total AEs, diarrhea, and GI disorders, but had significant risk of increase in dizziness. GRADE showed that the quality of evidence had high certainty in FPG and moderate certainty in HbA1c, body weight and all AEs.

Analysis of an incomplete binary outcome dichotomized from an underlying continuous variable in clinical trials

In many clinical trials, outcomes of interest are binary-valued. It is not uncommon that a binary-valued outcome is dichotomized from a continuous outcome at a threshold of clinical interest. To analyze such data, common approaches include (a) fitting a generalized linear mixed model (GLMM) to the dichotomized longitudinal binary outcome; and (b) the multiple imputation (MI) based method: imputing missing values in the continuous outcome, dichotomizing it into a binary outcome, and then fitting a generalized linear model to the "complete" data. We conducted comprehensive simulation studies to compare the performance of the GLMM versus the MI-based method for estimating the risk difference and the logarithm of odds ratio between two treatment arms at the end of study. In those simulation studies, we considered a range of multivariate distribution options for the continuous outcome (including a multivariate normal distribution, a multivariate t-distribution, a multivariate log-normal distribution, and the empirical distribution from a real clinical trial data) to evaluate the robustness of the estimators to various data-generating models. Simulation results demonstrate that both methods work well under those considered distribution options, but the MI-based method is more efficient with smaller mean squared errors compared to the GLMM. We further applied both the GLMM and the MI-based method to 29 phase 3 diabetes clinical trials, and found that the MI-based method generally led to smaller variance estimates compared to the GLMM.

[Treatment and prognosis analysis of perineural invasion on sinonasal adenoid cystic carcinoma]

Objective: To analyze the efficacy of sinonasal adenoid cystic carcinoma (ACC) with perineural invasion (PNI), and explore the prognostic value of PNI on sinonasal adenoid cystic carcinoma. Methods: The clinical data of 105 patients with sinonasal ACC admitted to Cancer Hospital, Chinese Academy of Medical Sciences from January 2000 to December 2016 were retrospectively reviewed. All patients were restaged according to American Joint Committee on Cancer 8th edition. Follow-up visits were conducted to obtain information of treatment failure and survival outcome. The Log rank test was used for univariate analysis of prognostic factors, and Cox regression model was used for multivariate prognostic analysis. Results: The maxillary sinus (n=59) was the most common primary site, followed by the nasal cavity (n=38). There were 93 patients with stage Ⅲ-Ⅳ. The treatment modalities included surgery alone (n=14), radiotherapy alone (n=13), preoperative radiotherapy plus surgery (n=10), and surgery plus postoperative radiotherapy (n=68). The median follow-up time was 91.8 months, the 5-year local control (LC), distant metastasis-free survival (DMFS), progression-free survival (PFS), and overall survival (OS) rates were 72.6%, 73.0%, 52.9% and 78.0%, respectively. There were 33 patients (31.4%) with PNI-positive. The 5-year DMFS, PFS, and OS rates of PNI-positive group were 53.7%, 29.4% and 56.5%, respectively, which were significantly inferior to those of PNI-negative group (80.8%, 63.0% and 86.8%, respectively, P<0.05), while there was no significant difference in the 5-year LC rate between both groups (64.5% vs 76.5%, P=0.273). The multivariate Cox regression analysis showed PNI was one of the poor prognostic factors of DMFS (HR=3.514, 95%CI: 1.557-7.932), PFS (HR=2.562, 95%CI: 1.349-4.866) and OS (HR=2.605, 95%CI: 1.169-5.806). Among patients with PNI-positive, the 5-year LC, PFS and OS rates of patients received surgery combined with radiotherapy were 84.9%, 41.3% and 72.7%, respectively, which were significantly higher than 23.3%, 10.0% and 26.7% of patients receiving surgery or radiotherapy alone (P<0.05). Conclusion: The presence of PNI increases the risk of distant metastasis in patients with sinonasal ACC. Compared with patients with PNI-negative, the prognosis of patients with PNI-positive is relatively poor, and surgery combined with radiotherapy for PNI-positive sinonasal ACC results in good clinical outcomes.

Return-to-baseline multiple imputation for missing values in clinical trials

Return-to-baseline is an important method to impute missing values or unobserved potential outcomes when certain hypothetical strategies are used to handle intercurrent events in clinical trials. Current return-to-baseline approaches seen in literature and in practice inflate the variability of the "complete" dataset after imputation and lead to biased mean estimators when the probability of missingness depends on the observed baseline and/or postbaseline intermediate outcomes. In this article, we first provide a set of criteria a return-to-baseline imputation method should satisfy. Under this framework, we propose a novel return-to-baseline imputation method. Simulations show the completed data after the new imputation approach have the proper distribution, and the estimators based on the new imputation method outperform the traditional method in terms of both bias and variance, when missingness depends on the observed values. The new method can be implemented easily with the existing multiple imputation procedures in commonly used statistical packages.

Estimating the treatment effect for adherers using multiple imputation

Randomized controlled trials are considered the gold standard to evaluate the treatment effect (estimand) for efficacy and safety. According to the recent International Council on Harmonization (ICH)-E9 addendum (R1), intercurrent events (ICEs) need to be considered when defining an estimand, and principal stratum is one of the five strategies to handle ICEs. Qu et al. (2020, Statistics in Biopharmaceutical Research 12:1-18) proposed estimators for the adherer average causal effect (AdACE) for estimating the treatment difference for those who adhere to one or both treatments based on the causal-inference framework, and demonstrated the consistency of those estimators; however, this method requires complex custom programming related to high-dimensional numeric integrations. In this article, we implemented the AdACE estimators using multiple imputation (MI) and constructed confidence intervals (CIs) through bootstrapping. A simulation study showed that the MI-based estimators provided consistent estimators with the nominal coverage probabilities of CIs for the treatment difference for the adherent populations of interest. As an illustrative example, the new method was applied to data from a real clinical trial comparing two types of basal insulin for patients with type 1 diabetes.

Acute and chronic effects of high-intensity interval training (HIIT) on postexercise intramuscular lipid metabolism in rats

Recovery from exercise refers to the period between the end of a bout of exercise and the subsequent return to a resting or recovered state. It is a dynamic period in which many physiological changes occur. A large amount of research has evaluated the effect of training on intramuscular lipid metabolism. However, data are limited regarding intramuscular lipid metabolism during the recovery period. In this study, lipid metabolism-related proteins were examined after a single bout of exercise in a time-dependent way to explore the mechanism of how exercise induces intramuscular lipid metabolism adaptation. Firstly, all rats in the exercise group underwent a five-week training protocol (HIIT, five times/week), and then performed a more intense HIIT session after 72 h of the last-time five-week training. After that, rats were sampled in a time-dependent way, including 0 h, 6 h, 12 h, 24 h, 48 h, 72 h, and 96 h following the acute training session. Our results discovered that five weeks of HIIT increased the content of intramuscular triglyceride (IMTG) and enhanced the lipolytic and lipogenesis-related proteins in skeletal muscle. Furthermore, IMTG content decreased immediately post HIIT and gradually increased to baseline levels 48 h postexercise, continuing to over-recover up to 96 h postexercise. Following acute exercise, lipolytic-related proteins showed an initial increase (6-12 h) before decreasing during recovery. Conversely, lipogenesis-related proteins decreased following exercise (6-12 h), then increased in the recovery period. Based on the changes, we speculate that skeletal muscle is predominated by lipid oxidative at the first 12 h postexercise. After this period, lipid synthesis-related proteins increased, which may be the result of body recovery. Together, these results may provide insight into how the lipid metabolism-related signaling changes after chronic and acute HIIT and how protein levels lipid metabolism correlates to IMTG recovery.

Optical coherence tomography-defined vulnerable plaque characteristics in relation to functional severity of coronary stenoses stratified by quantitative flow ratio

Background

The functional severity and morphological features of epicardial lesions are both related to plaque vulnerability and adverse coronary events. However, their relationship remains controversial, especially in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS).

Purpose

This study aimed to examine whether quantitative flow ratio (QFR), an angiography-based computation of fractional flow reserve, was associated with optical coherence tomography (OCT)-defined vulnerable plaques such as thin-cap fibroatheromas (TCFAs) in a board spectrum of population, including patients presenting stable angina and NSTE-ACS.

Methods

We identified patients who underwent OCT examinations from 2 prospective cohorts and then assessed interrogated vessels with QFR. Lesions were divided into tertiles: QFR-T1 (QFR &lt;0.85)&lt;qfr),&gt;, QFR-T2 (0.85 to 0.93) and QFR-T3 (QFR &gt;0.93).

Results

This post-hoc analysis included 83 lesions from 79 patients (mean age: 61.5±9.8 years, males: 58%). Patients with NSTE-ACS accounted for the majority of the population (67%). The median % diameter stenosis and median QFR value were 42% (36 to 49%) and 0.88 (0.83 to 0.95), respectively. The prevalence of OCT-TCFA was significantly higher in QFR-T1 (50%) than in QFR-T2 (14%) and QFR-T3 (19%) (p=0.003 and 0.018, respectively). Overall significant differences were observed among tertiles in maximum lipid arc, thinnest fibrous cap thickness (FCT), and minimal lumen area (MLA) (p=0.017, 0.040, and &lt;0.001, respectively). The Spearman's correlation analysis showed that QFR was significantly related to MLA (ρ = 0.537, p&lt;0.001), % area stenosis (ρ = –0.512, p&lt;0.001), maximum lipid arc (ρ = –0.360, p=0.002), lipid length (ρ = –0.242, p=0.038), lipid index (ρ = –0.333, p=0.004), and thinnest FCT (ρ = 0.315, p=0.006). In the multivariable analysis, QFR ≤0.80 remained as a significant determinant of TCFAs regardless of the presence of NSTE-ACS and the level of low-density lipoprotein cholesterol (adjusted odds ratio = 4.387, 95% confidence interval: 1.297 to 14.839, p=0.017). In addition, QFR demonstrated moderate predictive ability for OCT-TCFA (area under the curve = 0.72, 95% confidence interval: 0.58 to 0.86, p=0.003) with the best cutoff of ≤0.86 (sensitivity: 65%; specificity: 73%; negative predictive value: 85%; accuracy: 71%).

Conclusions

Lower QFR was related to OCT-TCFA and other vulnerable plaque characteristics in angiographically mild-to-intermediate stable lesions and culprit lesions from NSTE-ACS. The QFR might be a useful tool for ruling out high-risk, rupture-prone plaques without using any pressure wires or vasodilators.

Funding Acknowledgement

Type of funding sources: Foundation. Main funding source(s): The Jiangsu Provincial Key Research and Development Program Flow diagram of patient selectionOCT findings according to QFR tertiles