Randomized Controlled Trials Data Research Articles

Proxy endpoints - bridging clinical trials and real world data

Objective:Disease severity scores, or endpoints, are routinely measured during Randomized Controlled Trials (RCTs) to closely monitor the effect of treatment. In real-world clinical practice, although a larger set of patients is observed, the specific RCT endpoints are often not captured, which makes it hard to utilize real-world data (RWD) to evaluate drug efficacy in larger populations. Methods:To overcome this challenge, we developed an ensemble technique which learns proxy models of disease endpoints in RWD. Using a multi-stage learning framework applied to RCT data, we first identify features considered significant drivers of disease available within RWD. To create endpoint proxy models, we use Explainable Boosting Machines (EBMs) which allow for both end-user interpretability and modeling of non-linear relationships. Results:We demonstrate our approach on two diseases, rheumatoid arthritis (RA) and atopic dermatitis (AD). As we show, our combined feature selection and prediction method achieves good results for both disease areas, improving upon prior methods proposed for predictive disease severity scoring. Conclusion:Having disease severity over time for a patient is important to further disease understanding and management. Our results open the door to more use cases in the space of RA and AD such as treatment effect estimates or prognostic scoring on RWD. Our framework may be extended beyond RA and AD to other diseases where the severity score is not well measured in electronic health records.

Assessing heterogeneity in treatment initiation guidelines in longitudinal randomized controlled trials

Treatment initiation guidelines are essential in healthcare, dictating when patients begin therapy. These guidelines are typically assessed through randomized controlled trials (RCTs) to measure their average effect on a population. However, this method may not fully account for patient heterogeneity. We introduce a refined analysis methodology that accounts for diverse times to treatment initiation (TTI) arising from these guidelines. We offer a more detailed perspective on the guidelines’ impact by analyzing homogeneous subpopulations based on their TTI. We develop a longitudinal regression model with smooth time functions to capture dynamic changes in average guideline effects on subpopulations (AGES). A unique weighting mechanism creates pseudo-subpopulations from RCT data, enabling consistent and precise estimation of smooth functions. The efficacy of our approach is validated through theoretical and numerical studies, underscoring its capacity to provide insightful statistical inferences. We exemplify the utility of our methodology by applying it to an RCT of the World Health Organization (WHO) guideline for adults with HIV. This analysis promises to enhance the evaluation of treatment initiation guidelines, leading to more personalized and efficient patient care.

Association Between Single-Dose and Longer Term Clinical Response to Stimulants in Attention-Deficit/Hyperactivity Disorder: A Systematic Review of Randomized Controlled Trials.

Objectives: Stimulants, such as methylphenidate (MPH) and amphetamines, represent the first-line pharmacological option for attention-deficit/hyperactivity disorder (ADHD). Randomized controlled trials (RCTs) have demonstrated beneficial effects at a group level but could not identify characteristics consistently associated with varying individual response. Thus, more individualized approaches are needed. Experimental studies have suggested that the neurobiological response to a single dose is indicative of longer term response. It is unclear whether this also applies to clinical measures. Methods: We carried out a systematic review of RCTs testing the association between the clinical response to a single dose of stimulants and longer term improvement. Potentially suitable single-dose RCTs were identified from the MED-ADHD data set, the European ADHD Guidelines Group RCT Data set (https://med-adhd.org/), as updated on February 1, 2024. Quality assessment was carried out using the Cochrane Risk of Bias (RoB) 2.0 tool. Results: A total of 63 single-dose RCTs (94% testing MPH, 85% in children) were identified. Among these, only a secondary analysis of an RCT tested the association between acute and longer term clinical response. This showed that the clinical improvement after a single dose of MPH was significantly associated with symptom improvement after a 4-week MPH treatment in 46 children (89% males) with ADHD. The risk of bias was rated as moderate. A further RCT used near-infrared spectroscopy, thus did not meet the inclusion criteria, and reported an association between brain changes under a single-dose and longer term clinical response in 22 children (82% males) with ADHD. The remaining RCTs only reported single-dose effects on neuropsychological, neuroimaging, or neurophysiological measures. Conclusion: This systematic review highlighted an important gap in the current knowledge. Investigating how acute and long-term response may be related can foster our understanding of stimulant mechanism of action and help develop stratification approaches for more tailored treatment strategies. Future studies need to investigate potential age- and sex-related differences.

Incidence and predictors of major gastrointestinal bleeding in patients on aspirin, low-dose rivaroxaban, or the combination: Secondary analysis of the COMPASS randomised controlled trial.

The incidence of major gastrointestinal bleeding (GIB) in patients on low-dose direct-acting oral anticoagulants (DOACs) is relatively unknown. Estimates from randomised controlled trials (RCTs) are lacking. To assess GIB incidence and predictors from RCT data of patients on aspirin, low-dose rivaroxaban, or both. This was a secondary analysis of RCT data wherein patients received aspirin 100 mg daily and rivaroxaban 2.5 mg b.d., aspirin alone, or rivaroxaban 5 mg b.d. Patients were followed from 2013 to 2016 at 602 centres. Outcomes included overall, upper, and lower GIB. We employed multivariable logistic regression to yield odds ratios (ORs) and 95% confidence intervals for potential exposures. Among 27,395 patients, the annual incidence of GIB on rivaroxaban 2.5 mg b.d. with aspirin was 801.7 per 100,000 compared with 372.3 in 100,000 for aspirin. Age (OR 4.16, 2.53-6.82 for ≥75 vs. 55-64), peptic ulcer disease (PUD, OR 1.57, 1.01-2.44), liver disease (OR 2.09, 1.01-4.33), hypertension (OR 1.42, 1.04-1.94), and smoking (OR 1.85, 1.26-2.73) were associated with overall GIB. Kidney disease (OR 1.68, 1.12-2.51) was significantly associated with upper GIB, whereas diverticular disease (OR 3.75, 1.88-7.49) was associated with lower GIB. Addition of rivaroxaban to aspirin was associated more with lower GIB (OR 2.82, 1.64-4.84) than upper GIB (OR 1.86, 1.18-2.92). We established incidences and identified risk factors for GIB in users of low-dose DOACs. Novel risk factors included current or former smoking and diverticulosis. Future studies should aim to validate these risk factors.

High-flow nasal oxygen therapy compared with conventional oxygen therapy in hospitalised patients with respiratory illness: a systematic review and meta-analysis

BackgroundHigh-flow nasal oxygen therapy (HFNO) is used in diverse hospital settings to treat patients with acute respiratory failure (ARF). This systematic review aims to summarise the evidence regarding any benefits...

Evaluating CR as a surrogate endpoint for PFS in R/R chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL): A meta-analysis of randomized controlled trials (RCT).

7046 Background: CLL/SLL is the most common leukemia in adults. Achieving a CR by International Workshop on CLL 2018 criteria indicates complete eradication of CLL/SLL in all disease compartments. Patients with R/R CLL/SLL who achieved CR tend to have delayed disease progression/death compared with patients who did not achieve CR. This is the first report to evaluate CR as a surrogate endpoint for PFS in R/R CLL/SLL using aggregate RCT data. Methods: A systematic literature review (SLR) identified published RCTs in R/R CLL/SLL from inception to 10/2023, reporting nonzero CR rates (CRR) and PFS. Association between treatment effects on CR and PFS across RCTs was estimated using a weighted linear model (WLM) in the primary analysis, and Daniels and Hughes (D&H) and Riley bivariate random-effects meta-analysis (BRMA) in sensitivity analyses. Strength of association was assessed based on surrogacy criteria described by D&H. Predictive performance of models was evaluated using leave-one-out cross-validation. Results: The SLR identified 13 RCTs with a total of 4388 patients with R/R CLL/SLL treated with a variety of therapies, including but not limited to BTKi, BCL2i, PI3Ki, CAR T cell therapy, anti-CD20 mAb, and chemotherapy. Across the evidence base, CRR ranged from 0.48% to 38.10% and median PFS was between 1 and 35.9 months (excluding unreached medians). Across RCTs, contrasting treatment and control arms, higher odds of CR resulted in lower hazards of disease progression/death (CRR improvement translated to PFS benefit). D&H surrogacy criteria were met for WLM: 1) a near-zero, statistically nonsignificant intercept, indicating that no treatment effect on CRR implies no effect on PFS; 2) a negative, statistically significant slope, suggesting that improved CRR correlates with longer PFS; and 3) a near-zero conditional variance, meaning that PFS HR variation was primarily explained by CR odds ratio. During cross-validation, treatment effects on CR were predictive of PFS benefits, as the 95% predictive interval of PFS HR contained the observed HR in all RCTs for WLM. Results were largely consistent across all 3 models(Table). Conclusions: Improved CRR corresponds to prolonged PFS across RCTs and treatment comparisons. The results support CRR as an important treatment goal for R/R CLL/SLL and a valid surrogate endpoint. Consistent results and predictive performance across different models indicate the robustness of the results. [Table: see text]

Patent Foramen Ovale Closure in Older Patients With Stroke: Patient Selection for Trial Feasibility.

Whether patent foramen ovale (PFO) closure benefits older patients with PFO and cryptogenic stroke is unknown because randomized controlled trials (RCTs) have predominantly enrolled patients younger than 60 years of age. Our objective was to estimate anticipated effects of PFO closure in older patients to predict the numbers needed to plan an RCT. Effectiveness estimates are derived from major observational studies (Risk of Paradoxical Embolism [RoPE] Study and Oxford Vascular Study, together referred to as the "RoPE-Ox" database) and all 6 major RCTs (Systematic, Collaborative, PFO Closure Evaluation [SCOPE] Consortium). To estimate stroke recurrence risk, observed outcomes were calculated for patients older than 60 years in the age-inclusive observational databases (n = 549). To estimate the reduction in the rate of recurrent stroke associated with PFO closure vs medical therapy based on the RoPE score and the presence of high-risk PFO features, a Cox proportional hazards regression model was developed on the RCT data in the SCOPE database (n = 3,740). These estimates were used to calculate sample sizes required for a future RCT. Five-year risk of stroke recurrence using Kaplan-Meier estimates was 13.7 (95% CI 10.5-17.9) overall, 14.9% (95% CI 10.2-21.6) in those with high-risk PFO features. Predicted relative reduction in the event rate with PFO closure was 12.9% overall, 48.8% in those with a high-risk PFO feature. Using these estimates, enrolling all older patients with cryptogenic stroke and PFO would require much larger samples than those used for prior PFO closure trials, but selectively enrolling patients with high-risk PFO features would require totals of 630 patients for 90% power and 471 patients for 80% power, with an average of 5 years of follow-up. Based on our projections, anticipated effect sizes in older patients with high-risk features make a trial in these subjects feasible. With lengthening life expectancy in almost all regions of the world, the utility of PFO closure in older adults is increasingly important to explore.

#2609 Comparison of baseline patient characteristics of the CONVINCE randomized controlled trial with existing trial and registry populations

Abstract Background and Aims The generalizability of randomized controlled trials (RCTs) results is based on representativeness of the population involved. Trial populations may have different baseline characteristics compared to the general population that could benefit from the intervention. We compare the baseline characteristics of patients involved in the CONVINCE trial with those involved in all previous RCTs and representative registries of patients receiving hemodialysis as renal replacement therapy. Method Based on world class methods for systematic reviews, we identified all RCTs comparing hemodiafiltration (HDF) with hemodialysis (HD) published up to January 2024 and extracted data on baseline patient characteristics. Where data were missing, authors have been contacted and data so far obtained were included in this analysis (Fig. 1). Additional contact attempts are being performed. In addition, a comprehensive search was conducted to identify renal registries from all geographic regions. Those without information in English, without information on HDF and registries focusing on special patient groups (e.g. transplantation only) were excluded. This registry data will not be analyzed in this abstract as we are in progress of extracting the patient data from the latest registry annual reports available up to January 2024 for further analysis. Results We have selected 11 RCTs for further analysis, with the selection criteria and outcomes presented in Fig. 1. Key patient characteristics from RCTs were compared with those of patients in the CONVINCE trial using descriptive statistics and forest plots (Fig. 1). Comparison of differences was analyzed with the Kruskal-Wallis-Test. Interpretation of the results are as follows: • Age: Mean age of 76.5 years noted in Morena et al. (2017) because study inclusion criterion was ≥65 years. Other RCTs ranged from 54.1 to 68 years, which is consistent with 62.4 years in the CONVINCE trial (χ2 = 10, df = 10, p = 0.44). • Sex: 16.7% and 50% female noted in Selby et al. (2006) and Meert et al. (2009) respectively probably due to limited sample size (12 patients and 14 patients respectively). Other RCTs ranges from 30.4% to 42.5%, which is consistent with 36.0% in the CONVINCE trial (χ2 = 11, df = 11, p = 0.44). • Diabetes comorbidities: Ranges from 17.8% to 45%. CONVINCE trial is 35.0% (χ2 = 6, df = 6, p = 0.42). • Cardiovascular diseases comorbidities: Range from 26.4% to 45%. CONVINCE trial is 45% (χ2 = 3, df = 3, p = 0.39). • AVF as vascular access: value of 100% in Pedrini et al. (2011) because it was an inclusion criterion. Other RCTs ranged from 79.4% to 90%, which is consistent with 82% in the CONVINCE trial (χ2 = 7, df = 7, p = 0.43). There were no significant differences between CONVINCE and other RCTs data regarding all 5 patient baseline characteristics. Conclusion Our analysis showed the CONVINCE trial has no significant differences in patient baseline characteristics compared to previous RCTs. For a more comprehensive evaluation of representativeness of the trial's population, we are currently retrieving missing data from the trial authors and analyzing data from hemodialysis registries.

Progress in methodological research on bridging the efficacy-effectiveness gap of clinical interventions(2): to improve the extrapolation of efficacy

Objective: Randomized controlled trials (RCT) usually have strict implementation criteria. The included subjects' characteristics of the conditions for the intervention implementation are quite different from the actual clinical environment, resulting in discrepancies between the risk-benefit of interventions in actual clinical use and the risk-benefit shown in RCT. Therefore, some methods are needed to enhance the extrapolation of RCT results to evaluate the real effects of drugs in real people and clinical practice settings. Methods: Six databases (PubMed, Embase, Web of Science, CNKI, Wanfang Data, and VIP) were searched up to 31st December 2022 with detailed search strategies. A scoping review method was used to integrate and qualitatively describe the included literature inductively. Results: A total of 12 articles were included. Three methods in the included literature focused on: ①improving the design of traditional RCT to increase population representation; ②combining RCT Data with real-world data (RWD) for analysis;③calibrating RCT results according to real-world patient characteristics. Conclusions: Improving the design of RCT to enhance the population representation can improve the extrapolation of the results of RCT. Combining RCT data with RWD can give full play to the advantages of data from different sources; the results of the RCT were calibrated against real-world population characteristics so that the effects of interventions in real-world patient populations can be predicted.

The use of real-world data for clinical investigation of effectiveness in drug development

ABSTRACT With the growing interest in leveraging real-world data (RWD) to support effectiveness evaluations for new indications, new target populations, and post-market performance, the United States Food and Drug Administration has published several guidance documents on RWD sources and real-world studies (RWS) to assist sponsors in generating credible real-world evidence (RWE). Meanwhile, the randomized controlled trial (RCT) remains the gold standard in drug evaluation. Along this line, we propose a hybrid two-stage adaptive design to evaluate effectiveness based on evidence from both RCT and RWS. At the first stage, a typical non-inferiority test is conducted using RCT data to test for not-ineffectiveness. Once not-ineffectiveness is established, the study proceeds to the second stage to conduct an RWS and test for effectiveness using integrated information from RCT and RWD. The composite likelihood approach is implemented as a down-weighing strategy to account for the impact of high variability in RWS population. An optimal sample size determination procedure for RCT and RWS is introduced, aiming to achieve the minimal expected sample size. Through extensive numerical study, the proposed design demonstrates the ability to control type I error inflation in most cases and consistently maintain statistical power above the desired level. In general, this RCT/RWS hybrid two-stage adaptive design is beneficial for effectiveness evaluations in drug development, especially for oncology and rare diseases.

Screening Implications for Distribution of Colorectal Cancer Subsite by Age and Role of Flexible Sigmoidoscopy.

Objectives: The effectiveness of colonoscopy to reduce colorectal cancer (CRC) mortality is extrapolated from cohort studies in the absence of randomized controlled trial (RCT) data, whereas flexible sigmoidoscopy is supported by RCT data and may be easier to implement in practice. We characterized the anatomic distribution of CRC to determine the proportion that is visible with sigmoidoscopy. Methods: Patients with a primary diagnosis of colorectal adenocarcinoma were identified in the Surveillance, Epidemiology, and End Results program (2000-2020). Tumors from the rectum to the descending colon were categorized as visible by sigmoidoscopy, whereas more proximal tumors required colonoscopy. Differential prognosis between tumor locations, stratified by age groups and stage, was assessed using the overall restricted mean survival time (RMST) at 2, 5, and 10 years. Results: Among 309,466 patients, 58% had tumors visible by sigmoidoscopy, including 73% of those under age 50 (OR 2.10, 95% CI 2.03-2.16 age < 45, OR 2.20, 95% CI 2.13-2.27 age 45-49 versus age ≥ 50). Male sex (OR 1.54, 95% CI 1.51-1.56) and Asian or Pacific Islander race (OR 1.60, 95% CI 1.56-1.64) were also positively associated with tumors visualizable by sigmoidoscopy. Across age groups, for local disease, RMST was comparable for tumors visible versus not visible on sigmoidoscopy. For regional and metastatic cancer, patients with tumors visible by sigmoidoscopy had improved RMST versus those with more proximal tumors. Conclusions: 58% of CRC arises in locations visible by flexible sigmoidoscopy. Flexible sigmoidoscopy should be considered as a viable option for CRC screening, particularly in younger patients unwilling or unable to undergo colonoscopy.

Comparative efficacy and safety of stiripentol, cannabidiol and fenfluramine as first-line add-on therapies for seizures in Dravet syndrome: A network meta-analysis.

Stiripentol, fenfluramine, and cannabidiol are licensed add-on therapies to treat seizures in Dravet Syndrome (DS). There are no direct or indirect comparisons assessing their full licensed dose regimens, across different jurisdictions, as first-line add-on therapies in DS. We conducted a systematic review and frequentist network meta-analysis (NMA) of randomized controlled trial (RCT) data for licensed add-on DS therapies. We compared the proportions of patients experiencing: reductions from baseline in monthly convulsive seizure frequency (MCSF) of ≥50% (clinically meaningful), ≥75% (profound), and 100% (seizure-free); serious adverse events (SAEs); discontinuations due to AEs. We identified relevant data from two placebo-controlled RCTs for each drug. Stiripentol 50 mg/kg/day and fenfluramine 0.7 mg/kg/day had similar efficacy in achieving ≥50% (clinically meaningful) and ≥75% (profound) reductions from baseline in MCSF (absolute risk difference [RD] for stiripentol versus fenfluramine 1% [95% confidence interval: -20% to 22%; p = 0.93] and 6% [-15% to 27%; p = 0.59], respectively), and both were statistically superior (p < 0.05) to licensed dose regimens of cannabidiol (10 or 20 mg/kg/day, with/irrespective of clobazam) for these outcomes. Stiripentol was statistically superior in achieving seizure-free intervals compared to fenfluramine (RD = 26% [CI: 8% to 44%; p < 0.01]) and licensed dose regimens of cannabidiol. There were no significant differences in the proportions of patients experiencing SAEs. The risk of discontinuations due to AEs was lower for stiripentol, although the stiripentol trials were shorter. This NMA of RCT data indicates stiripentol, as a first-line add-on therapy in DS, is at least as effective as fenfluramine and both are more effective than cannabidiol in reducing convulsive seizures. No significant difference in the incidence of SAEs between the three add-on agents was observed, but stiripentol may have a lower risk of discontinuations due to AEs. These results may inform clinical decision-making and the continued development of guidelines for the treatment of people with DS. This study compared three drugs (stiripentol, fenfluramine, and cannabidiol) used alongside other medications for managing seizures in a severe type of epilepsy called DS. The study found that stiripentol and fenfluramine were similarly effective in reducing seizures and both were more effective than cannabidiol. Stiripentol was the best drug for stopping seizures completely based on the available clinical trial data. All three drugs had similar rates of serious side effects, but stiripentol had a lower chance of being stopped due to side effects. This information can help guide treatment choices for people with DS.

Whole-family programmes for families living with parental mental illness: a systematic review and meta-analysis.

Several interventions have been developed to support families living with parental mental illness (PMI). Recent evidence suggests that programmes with whole-family components may have greater positive effects for families, thereby also reducing costs to health and social care systems. This review aimed to identify whole-family interventions, their common characteristics, effectiveness and acceptability. A systematic review was conducted according to PRISMA 2020 guidelines. A literature search was conducted in ASSIA, CINAHL, Embase, Medline, and PsycINFO in January 2021 and updated in August 2022. We double screened 3914 abstracts and 212 papers according to pre-set inclusion and exclusion criteria. The Mixed Methods Appraisal Tool was used for quality assessment. Quantitative and qualitative data were extracted and synthesised. Randomised-control trial data on child and parent mental health outcomes were analysed separately in random-effects meta-analyses. The protocol, extracted data, and meta-data are accessible via the Open Science Framework ( https://osf.io/9uxgp/ ). Data from 66 reports-based on 41 independent studies and referring to 30 different interventions-were included. Findings indicated small intervention effects for all outcomes including children's and parents' mental health (dc = -0.017, -027; dp = -0.14, -0.16) and family outcomes. Qualitative evidence suggested that most families experienced whole-family interventions as positive, highlighting specific components as helpful, including whole-family components, speaking about mental illness, and the benefits of group settings. Our findings highlight the lack of high-quality studies. The present review fills an important gap in the literature by summarising the evidence for whole-family interventions. There is a lack of robust evidence coupled with a great need in families affected by PMI which could be addressed by whole-family interventions. We recommend the involvement of families in the further development of these interventions and their evaluation.

Treatment effect estimation using the propensity score in clinical trials with historical control

BackgroundClinical trials assessing new treatment effects require a control group to compare the pure treatment effects. However, in clinical trials on regenerative medicine, rare diseases, and intractable diseases, it may be ethically difficult to assign participants to the control group. In recent years, the use of historical control data has attracted attention as a method for supplementing the number of participants in the control group. When combining historical control data with new randomized controlled trial (RCT) data, the assessment of heterogeneity using outcome data is not sufficient. Therefore, several statistical methods that consider participant outcomes and baseline characteristics, including the propensity score (PS) method have been proposed.MethodsWe propose a new method considering “information on whether the data are RCT data or not” in the PS model when combining the RCT and historical control data. The performance of the proposed method in estimating the treatment effect is evaluated using simulation data.ResultsWhen the distribution of covariates is similar between the RCT and historical control data, not much difference in performance is found between the proposed and conventional methods to estimate the treatment effect. On the other hand, when the distribution of covariates is not similar between the two kinds of data, the proposed method shows higher performance.ConclusionsEven when it is not known whether RCT and historical control data are similar, the proposed PS model is useful to estimate the treatment effect appropriately in RCTs using historical control data.

Comparison Between Drug-Coated Balloon and Stents in Large De Novo Coronary Artery Disease: A Systematic Review and Meta-Analysis of RCT Data.

Although a number of studies involving small-vessel de novo coronary disease showed clinical benefits of drug-coated balloons (DCB), the role of DCB in large vessel lesions is still unclear. We searched main electronic databases for randomized controlled trials (RCTs) comparing DCB with stents for large vessel de novo coronary artery disease. The primary endpoint was major cardiovascular adverse events (MACE), composite cardiovascular death (CD), myocardial infarction (MI), or target lesion revascularization (TLR). This study included 7 RCTs with 770 participants.DCB were associated with a marked risk reduction in MACE [Risk Ratio (RR): 0.48; 95% confidence interval [CI]: 0.24 to 0.97; P = 0.04], TLR (RR: 0.53; 95% CI: 0.25 to 1.14; P = 0.10), and late lumen loss [standard mean difference (SMD): -0.57; 95% CI: -1.09 to -0.05; P = 0.03] as compared with stents. There is no significant difference in MI (RR: 0.58; 95% CI: 0.21 to 1.54; P = 0.27), CD (RR: 0.33; 95% CI: 0.06 to 1.78; P = 0.19), and minimal lumen diameter (SMD: -0.34; 95% CI: -0.72 to 0.05; P = 0.08) between groups. In subgroup analyses, the risk reduction of MACE persisted in patients with chronic coronary syndrome (RR: 0.25; 95% CI: 0.07 to 0.89; P = 0.03), and patients receiving DCB vs. bare metal stent (RR: 0.19; 95% CI: 0.05 to 0.73; P = 0.01). In addition, there was no significant difference between the DCB group and the drug eluting stent group for MACE (RR: 0.69; 95% CI: 0.30 to 1.60; P = 0.38). DCB may be an effective therapeutic option in patients with large vessel de novo coronary artery disease.

The Continuous Fragility Index of Statistically Significant Findings in Randomized Controlled Trials That Compare Interventions for Anterior Shoulder Instability.

Evidence-based care relies on robust research. The fragility index (FI) is used to assess the robustness of statistically significant findings in randomized controlled trials (RCTs). While the traditional FI is limited to dichotomous outcomes, a novel tool, the continuous fragility index (CFI), allows for the assessment of the robustness of continuous outcomes. To calculate the CFI of statistically significant continuous outcomes in RCTs evaluating interventions for managing anterior shoulder instability (ASI). Meta-analysis; Level of evidence, 2. A search was conducted across the MEDLINE, Embase, and CENTRAL databases for RCTs assessing management strategies for ASI from inception to October 6, 2022. Studies that reported a statistically significant difference between study groups in ≥1 continuous outcome were included. The CFI was calculated and applied to all available RCTs reporting interventions for ASI. Multivariable linear regression was performed between the CFI and various study characteristics as predictors. There were 27 RCTs, with a total of 1846 shoulders, included. The median sample size was 61 shoulders (IQR, 43). The median CFI across 27 RCTs was 8.2 (IQR, 17.2; 95% CI, 3.6-15.4). The median CFI was 7.9 (IQR, 21; 95% CI, 1-22) for 11 studies comparing surgical methods, 22.6 (IQR, 16; 95% CI, 8.2-30.4) for 6 studies comparing nonsurgical reduction interventions, 2.8 for 3 studies comparing immobilization methods, and 2.4 for 3 studies comparing surgical versus nonsurgical interventions. Significantly, 22 of 57 included outcomes (38.6%) from studies with completed follow-up data had a loss to follow-up exceeding their CFI. Multivariable regression demonstrated that there was a statistically significant positive correlation between a trial's sample size and the CFI of its outcomes (r = 0.23 [95% CI, 0.13-0.33]; P < .001). More than a third of continuous outcomes in ASI trials had a CFI less than the reported loss to follow-up. This carries the significant risk of reversing trial findings and should be considered when evaluating available RCT data. We recommend including the FI, CFI, and loss to follow-up in the abstracts of future RCTs.

Electronic cigarettes for smoking cessation.

Electronic cigarettes for smoking cessation.

Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data.

In recent years, numerous methods have been introduced to predict glucose levels using machine-learning techniques on patients' daily behavioral and continuous glucose data. Nevertheless, a definitive consensus remains elusive regarding modeling the combined effects of diet and exercise for optimal glucose prediction. A notable challenge is the propensity for observational patient datasets from uncontrolled environments to overfit due to skewed feature distributions of target behaviors; for instance, diabetic patients seldom engage in high-intensity exercise post-meal. In this study, we introduce a unique application of Bayesian transfer learning for postprandial glucose prediction using randomized controlled trial (RCT) data. The data comprises a time series of three key variables: continuous glucose levels, exercise expenditure, and carbohydrate intake. For building the optimal model to predict postprandial glucose levels we initially gathered balanced training data from RCTs on healthy participants by randomizing behavioral conditions. Subsequently, we pretrained the model's parameter distribution using RCT data from the healthy cohort. This pretrained distribution was then adjusted, transferred, and utilized to determine the model parameters for each patient. The efficacy of the proposed method was appraised using data from 68 gestational diabetes mellitus (GDM) patients in uncontrolled settings. The evaluation underscored the enhanced performance attained through our method. Furthermore, when modeling the joint impact of diet and exercise, the synergetic model proved more precise than its additive counterpart. An innovative application of the transfer-learning utilizing randomized controlled trial data can improve the challenging modeling task of postprandial glucose prediction for GDM patients, integrating both dietary and exercise behaviors. For more accurate prediction, future research should focus on incorporating the long-term effects of exercise and other glycemic-related factors such as stress, sleep.

Mixed-methods randomised study exploring the feasibility and acceptability of eye-movement desensitisation and reprocessing for improving the mental health of traumatised survivors of intensive care following hospital discharge: protocol

IntroductionPost-traumatic symptoms are common among patients discharged from intensive care units (ICUs), adversely affecting well-being, increasing healthcare utilisation and delaying return to work. Non-pharmacological approaches (eg, music, therapeutic touch and...

Automated information extraction model enhancing traditional Chinese medicine RCT evidence extraction (Evi-BERT): algorithm development and validation.

In the field of evidence-based medicine, randomized controlled trials (RCTs) are of critical importance for writing clinical guidelines and providing guidance to practicing physicians. Currently, RCTs rely heavily on manual extraction, but this method has data breadth limitations and is less efficient. To expand the breadth of data and improve the efficiency of obtaining clinical evidence, here, we introduce an automated information extraction model for traditional Chinese medicine (TCM) RCT evidence extraction. We adopt the Evidence-Bidirectional Encoder Representation from Transformers (Evi-BERT) for automated information extraction, which is combined with rule extraction. Eleven disease types and 48,523 research articles from the China National Knowledge Infrastructure (CNKI), WanFang Data, and VIP databases were selected as the data source for extraction. We then constructed a manually annotated dataset of TCM clinical literature to train the model, including ten evidence elements and 24,244 datapoints. We chose two models, BERT-CRF and BiLSTM-CRF, as the baseline, and compared the training effects with Evi-BERT and Evi-BERT combined with rule expression (RE). We found that Evi-BERT combined with RE achieved the best performance (precision score = 0.926, Recall = 0.952, F1 score = 0.938) and had the best robustness. We totally summarized 113 pieces of rule datasets in the regulation extraction procedure. Our model dramatically expands the amount of data that can be searched and greatly improves efficiency without losing accuracy. Our work provided an intelligent approach to extracting clinical evidence for TCM RCT data. Our model can help physicians reduce the time spent reading journals and rapidly speed up the screening of clinical trial evidence to help generate accurate clinical reference guidelines. Additionally, we hope the structured clinical evidence and structured knowledge extracted from this study will help other researchers build large language models in TCM.