Direct and indirect treatment effects in the presence of semicompeting risks.

Semicompeting risks refer to the phenomenon that the terminal event (such as death) can censor the nonterminal event (such as disease progression) but not vice versa. The treatment effect on the terminal event can be delivered either directly following the treatment or indirectly through the nonterminal event. We consider 2 strategies to decompose the total effect into a direct effect and an indirect effect under the framework of mediation analysis in completely randomized experiments by adjusting the prevalence and hazard of nonterminal events, respectively. They require slightly different assumptions on cross-world quantities to achieve identifiability. We establish asymptotic properties for the estimated counterfactual cumulative incidences and decomposed treatment effects. We illustrate the subtle difference between these 2 decompositions through simulation studies and two real-data applications in the Supplementary Materials.

Assessing treatment effect heterogeneity in the presence of missing effect modifier data in cluster-randomized trials.

Understanding whether and how treatment effects vary across subgroups is crucial to inform clinical practice and recommendations. Accordingly, the assessment of heterogeneous treatment effects based on pre-specified potential effect modifiers has become a common goal in modern randomized trials. However, when one or more potential effect modifiers are missing, complete-case analysis may lead to bias and under-coverage. While statistical methods for handling missing data have been proposed and compared for individually randomized trials with missing effect modifier data, few guidelines exist for the cluster-randomized setting, where intracluster correlations in the effect modifiers, outcomes, or even missingness mechanisms may introduce further threats to accurate assessment of heterogeneous treatment effect. In this article, the performance of several missing data methods are compared through a simulation study of cluster-randomized trials with continuous outcome and missing binary effect modifier data, and further illustrated using real data from the Work, Family, and Health Study. Our results suggest that multilevel multiple imputation and Bayesian multilevel multiple imputation have better performance than other available methods, and that Bayesian multilevel multiple imputation has lower bias and closer to nominal coverage than standard multilevel multiple imputation when there are model specification or compatibility issues.

Problematic meta-analyses: Bayesian and frequentist perspectives on combining randomized controlled trials and non-randomized studies.

PURPOSE: In the literature, the propriety of the meta-analytic treatment-effect produced by combining randomized controlled trials (RCT) and non-randomized studies (NRS) is questioned, given the inherent confounding in NRS that may bias the meta-analysis. The current study compared an implicitly principled pooled Bayesian meta-analytic treatment-effect with that of frequentist pooling of RCT and NRS to determine how well each approach handled the NRS bias. MATERIALS & METHODS: Binary outcome Critical-Care meta-analyses, reflecting the importance of such outcomes in Critical-Care practice, combining RCT and NRS were identified electronically. Bayesian pooled treatment-effect and 95% credible-intervals (BCrI), posterior model probabilities indicating model plausibility and Bayes-factors (BF) were estimated using an informative heavy-tailed heterogeneity prior (half-Cauchy). Preference for pooling of RCT and NRS was indicated for Bayes-factors > 3 or < 0.333 for the converse. All pooled frequentist treatment-effects and 95% confidence intervals (FCI) were re-estimated using the popular DerSimonian-Laird (DSL) random effects model. RESULTS: Fifty meta-analyses were identified (2009-2021), reporting pooled estimates in 44; 29 were pharmaceutical-therapeutic and 21 were non-pharmaceutical therapeutic. Re-computed pooled DSL FCI excluded the null (OR or RR = 1) in 86% (43/50). In 18 meta-analyses there was an agreement between FCI and BCrI in excluding the null. In 23 meta-analyses where FCI excluded the null, BCrI embraced the null. BF supported a pooled model in 27 meta-analyses and separate models in 4. The highest density of the posterior model probabilities for 0.333 < Bayes factor < 1 was 0.8. CONCLUSIONS: In the current meta-analytic cohort, an integrated and multifaceted Bayesian approach gave support to including NRS in a pooled-estimate model. Conversely, caution should attend the reporting of naïve frequentist pooled, RCT and NRS, meta-analytic treatment effects.

Accuracy of Event Rate and Effect Size Estimation in Major Cardiovascular Trials: A Systematic Review.

Importance: For the design of a randomized clinical trial (RCT), estimation of the expected event rate and effect size of an intervention is needed to calculate the sample size. Overestimation may lead to an underpowered trial. Objective: To evaluate the accuracy of published estimates of event rate and effect size in contemporary cardiovascular RCTs. Evidence Review: A systematic search was conducted in MEDLINE for multicenter cardiovascular RCTs associated with MeSH (Medical Subject Headings) terms for cardiovascular diseases published in the New England Journal of Medicine, JAMA, or the Lancet between January 1, 2010, and December 31, 2019. Identified trials underwent abstract review; eligible trials then underwent full review, and those with insufficiently reported data were excluded. Data were extracted from the original publication or the study protocol, and a random-effects model was used for data pooling. This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guideline. The primary outcome was the accuracy of event rate and effect size estimation. Accuracy was determined by comparing the observed event rate in the control group and the effect size with their hypothesized values. Linear regression was used to determine the association between estimation accuracy and trial characteristics. Findings: Of the 873 RCTs identified, 374 underwent full review and 30 were subsequently excluded, resulting in 344 trials for analysis. The median observed event rate was 9.0% (IQR, 4.3% to 21.4%), which was significantly lower than the estimated event rate of 11.0% (IQR, 6.0% to 25.0%) with a median deviation of -12.3% (95% CI, -16.4% to -5.6%; P < .001). More than half of the trials (196 [61.1%]) overestimated the expected event rate. Accuracy of event rate estimation was associated with a higher likelihood of refuting the null hypothesis (0.13 [95% CI, 0.01 to 0.25]; P = .03). The median observed effect size in superiority trials was 0.91 (IQR, 0.74 to 0.99), which was significantly lower than the estimated effect size of 0.72 (IQR, 0.60 to 0.80), indicating a median overestimation of 23.1% (95% CI, 17.9% to 28.3%). A total of 216 trials (82.1%) overestimated the effect size. Conclusions and Relevance: In this systematic review of contemporary cardiovascular RCTs, event rates of the primary end point and effect sizes of an intervention were frequently overestimated. This overestimation may have contributed to the inability to adequately test the trial hypothesis.

Elucidating vaccine efficacy using a correlate of protection, demographics, and logistic regression.

BACKGROUND: Vaccine efficacy (VE) assessed in a randomized controlled clinical trial can be affected by demographic, clinical, and other subject-specific characteristics evaluated as baseline covariates. Understanding the effect of covariates on efficacy is key to decisions by vaccine developers and public health authorities. METHODS: This work evaluates the impact of including correlate of protection (CoP) data in logistic regression on its performance in identifying statistically and clinically significant covariates in settings typical for a vaccine phase 3 trial. The proposed approach uses CoP data and covariate data as predictors of clinical outcome (diseased versus non-diseased) and is compared to logistic regression (without CoP data) to relate vaccination status and covariate data to clinical outcome. RESULTS: Clinical trial simulations, in which the true relationship between CoP data and clinical outcome probability is a sigmoid function, show that use of CoP data increases the positive predictive value for detection of a covariate effect. If the true relationship is characterized by a decreasing convex function, use of CoP data does not substantially change positive or negative predictive value. In either scenario, vaccine efficacy is estimated more precisely (i.e., confidence intervals are narrower) in covariate-defined subgroups if CoP data are used, implying that using CoP data increases the ability to determine clinical significance of baseline covariate effects on efficacy. CONCLUSIONS: This study proposes and evaluates a novel approach for assessing baseline demographic covariates potentially affecting VE. Results show that the proposed approach can sensitively and specifically identify potentially important covariates and provides a method for evaluating their likely clinical significance in terms of predicted impact on vaccine efficacy. It shows further that inclusion of CoP data can enable more precise VE estimation, thus enhancing study power and/or efficiency and providing even better information to support health policy and development decisions.

Optimal allocation strategies in platform trials with continuous endpoints.

Platform trials are randomized clinical trials that allow simultaneous comparison of multiple interventions, usually against a common control. Arms to test experimental interventions may enter and leave the platform over time. This implies that the number of experimental intervention arms in the trial may change as the trial progresses. Determining optimal allocation rates to allocate patients to the treatment and control arms in platform trials is challenging because the optimal allocation depends on the number of arms in the platform and the latter typically varies over time. In addition, the optimal allocation depends on the analysis strategy used and the optimality criteria considered. In this article, we derive optimal treatment allocation rates for platform trials with shared controls, assuming that a stratified estimation and a testing procedure based on a regression model are used to adjust for time trends. We consider both, analysis using concurrent controls only as well as analysis methods using concurrent and non-concurrent controls and assume that the total sample size is fixed. The objective function to be minimized is the maximum of the variances of the effect estimators. We show that the optimal solution depends on the entry time of the arms in the trial and, in general, does not correspond to the square root of k allocation rule used in classical multi-arm trials. We illustrate the optimal allocation and evaluate the power and type 1 error rate compared to trials using one-to-one and square root of k allocations by means of a case study.

Sample size estimation for stratified cluster randomization trial with survival endpoint.

Cluster randomization trials with survival endpoint are predominantly used in drug development and clinical care research when drug treatments or interventions are delivered at a group level. Unlike conventional cluster randomization design, stratified cluster randomization design is generally considered more effective in reducing the impacts of imbalanced baseline prognostic factors and varying cluster sizes between groups when these stratification factors are adopted in the design. Failure to account for stratification and cluster size variability may lead to underpowered analysis and inaccurate sample size estimation. Apart from the sample size estimation in unstratified cluster randomization trials, there are no development of an explicit sample size formula for survival endpoint when a stratified cluster randomization design is employed. In this article, we present a closed-form sample size formula based on the stratified cluster log-rank statistics for stratified cluster randomization trials with survival endpoint. It provides an integrated solution for sample size estimation that account for cluster size variation, baseline hazard heterogeneity, and the estimated intracluster correlation coefficient based on the preliminary data. Simulation studies show that the proposed formula provides the appropriate sample size for achieving the desired statistical power under various parameter configurations. A real example of a stratified cluster randomization trial in the population with stable coronary heart disease is presented to illustrate our method.

Representation of Racial and Ethnic Minorities in Nephrology Clinical Trials: A Systematic Review and Meta-Analysis.

SIGNIFICANCE STATEMENT: Racial and ethnic disparities in clinical trial enrollment are well described. However, whether these disparities are present in nephrology randomized clinical trials has not been previously reported. We performed a systematic review and meta-analysis of 380 randomized clinical trials involving different aspects of kidney disease published between 2000 and 2021. Our results indicate that worldwide reporting of race and ethnicity is poor and that White individuals account for most of the randomized participants with decreased enrollment of Black participants in more recent trials. However, trials conducted in the United States have representation of Black and Hispanic participants consistent with the population prevalence of disease and under-representation of Asian participants. BACKGROUND: Under-representation of racial and ethnic minorities in clinical trials could worsen disparities, but reporting and enrollment practices in nephrology randomized clinical trials have not been described. METHODS: PubMed was searched to capture randomized clinical trials for five kidney disease-related conditions published between 2000 and 2021 in ten high-impact journals. We excluded trials with <50 participants and pilot trials. Outcomes of interest were the proportion of trials reporting race and ethnicity and the proportions of enrolled participants in each race and ethnicity category. RESULTS: Among 380 trials worldwide, race was reported in just over half and ethnicity in 12%. Most enrolled participants were White, and Black individuals accounted for ≤10% of participants except in dialysis trials where they accounted for 26% of participants. However, Black participants were enrolled at high proportions relative to disease and population prevalence in US CKD, dialysis, and transplant trials representing 19% of participants in AKI, 26% in CKD, 44% in GN, 40% in dialysis, and 26% in transplant trials. Enrollment of Asian participants was low worldwide except in GN trials with marked under-representation in US CKD, dialysis, and transplant trials. Hispanic individuals represented only 13% of participants in US dialysis trials compared with 29% of US dialysis population. CONCLUSION: More complete reporting of race and ethnicity in nephrology trials is needed. Black and Hispanic patients are well-represented in kidney disease trials in the United States. Asian patients are poorly represented in kidney trials both globally and in the United States.

Assessing intervention effects in a randomized trial within a social network.

Studies of social networks provide unique opportunities to assess the causal effects of interventions that may impact more of the population than just those intervened on directly. Such effects are sometimes called peer or spillover effects, and may exist in the presence of interference, that is, when one individual's treatment affects another individual's outcome. Randomization-based inference (RI) methods provide a theoretical basis for causal inference in randomized studies, even in the presence of interference. In this article, we consider RI of the intervention effect in the eX-FLU trial, a randomized study designed to assess the effect of a social distancing intervention on influenza-like-illness transmission in a connected network of college students. The approach considered enables inference about the effect of the social distancing intervention on the per-contact probability of influenza-like-illness transmission in the observed network. The methods allow for interference between connected individuals and for heterogeneous treatment effects. The proposed methods are evaluated empirically via simulation studies, and then applied to data from the eX-FLU trial.

The comprehensive analysis of clinical trials registration for IgA nephropathy therapy on ClinicalTrials.gov.

OBJECTIVES: IgA Nephropathy (IgAN) is common chronic kidney disease with a high incidence. This study aims to analyze comprehensively therapeutic clinical trials for IgAN registered on ClinicalTrials.gov. METHODS: Therapeutic trials for IgAN registered on ClinicalTrials.gov. up to 15 August 2021 were obtained. The general characteristics, features of experimental design, treatment strategies, and some main inclusion criteria and outcome measures were accessed. RESULTS: A total of 104 therapeutic clinical trials for IgAN were extracted on ClinicalTrials.gov up to 15 August 2021. Most of these trials explored the treatment for primary IgAN confirmed by renal biopsy in adults. Only 9% of all selected trials had results. Forty-five percent of trials recruited 50 or fewer participants, and 73% were adults or older adults. 99% of trials were interventional studies, and of all the interventional trials, 70% of trials were randomized, and 68% exercised a parallel assignment of intervention model. Immunosuppression was the most studied for the treatment of IgAN. Moreover, many novel agents had been increasingly studied in recent years. Furthermore, the inclusion criteria and primary outcome measures in these trials were diverse, and the level of proteinuria and change of proteinuria levels were the most used as inclusion criteria and primary outcome, respectively. CONCLUSIONS: The majority of therapeutic trials for IgAN were randomized, none masking and parallel-assignment interventional studies, primarily recruiting adult patients as research subjects. These trials had relatively small sample sizes and short observation. Thus, more large-scale, multicenter, and randomized controlled trials are still needed to improve the management for IgAN.

Predictors, Moderators, and Mediators Associated With Treatment Outcome in Randomized Clinical Trials Among Adolescents With Depression: A Scoping Review.

Importance: The application of precision medicine principles for the treatment of depressive disorders in adolescents requires an examination of the variables associated with depression outcomes in randomized clinical trials (RCTs). Objective: To describe predictors, moderators, and mediators associated with outcomes in RCTs for the treatment of depressive disorders in adolescents. Evidence Review: A scoping review of RCTs for the treatment of depression in adolescents was conducted. Databases searched included MEDLINE, Embase, APA PsycInfo, and CINAHL. Included publications tested predictors, moderators, and/or mediators associated with depression symptom outcomes (eg, symptom reduction, response, remission) in RCTs pertaining to the treatment of adolescents, ages 13 to 17 years. Predictors were defined as variables that were associated with depression outcomes, independent of treatment group. Moderators were defined as baseline variables that were associated with differential outcomes between treatment groups. Mediators were defined by a formal mediation analysis. In duplicate, variables were extracted and coded with respect to analysis type (univariable or multivariable), statistical significance, direction of effect size, reporting of a priori hypotheses, and adjustment for multiple comparisons. Aggregated results were summarized by variable domain and RCT sample. Findings: Eighty-one articles reporting on variables associated with outcomes across 33 RCTs were identified, including studies of biological (10 RCTs), psychosocial (18 RCTs), and combined (4 RCTs) treatments as well as a service delivery model (1 RCT). Fifty-three variable domains were tested as baseline predictors of depression outcome, 41 as moderators, 19 as postbaseline predictors, and 5 as mediators. Variable domains that were reported as significant in at least 3 RCTs included age, sex/gender, baseline depression severity, early response to treatment, sleep changes, parent-child conflict, overall psychopathology, suicidal ideation, hopelessness, functional impairment, attendance at therapy sessions, and history of trauma. Two publications reported a priori hypotheses and adjustment for multiple comparisons, both finding that baseline depression severity and family conflict were associated with poorer outcomes. Conclusions and Relevance: This review identified commonly researched variables requiring more scrutiny as well as underresearched variables to inform future study designs. Further efforts to discover predictors, moderators, and mediators associated with treatment response have great potential to optimize care for adolescents with depression.

Randomized controlled trial to test the efficacy of a brief, communication-based, substance use preventive intervention for parents of adolescents: Protocol for the SUPPER Project (Substance Use Prevention Promoted by Eating family meals Regularly).

BACKGROUND: Substance use among adolescents in the U.S. is associated with adverse physical and mental health outcomes in the long-term. Universal youth-focused substance use prevention programs have demonstrated effectiveness but are often not sustainable due to the significant amount of time, effort, and resources required. We describe a trial protocol for a brief, low-participant-burden intervention to improve substance use-specific parent-child communication through the promotion of family meals and increased parental engagement. METHODS: This study is a parallel-group randomized controlled trial designed to assess the efficacy of a 13-week intervention. A total of 500 dyads of parents and their 5th-7th grade children are recruited from across Massachusetts. Dyads are randomized to the intervention or attention-control condition using block urn randomization, based on child grade, gender, and school. Parents/guardians in the substance use preventive intervention arm receive a short handbook, attend two meetings with an interventionist, and receive two SMS messages per week. Parents/guardians in the control arm receive the same dose but with content focused on nutrition, physical activity, and weight stigma. Participant dyads submit videos of family meals, audio recordings of prompted conversations, and quantitative surveys over an 18-month period (baseline, 3, 6, 12, 18 months post-intervention). The primary outcomes measure the quantity and quality of parent-child substance use conversations and proximal child indicators (i.e., substance use attitudes and expectancies, affiliation with substance-using peers, and intentions and willingness to use substances). The secondary outcome is child substance use initiation. DISCUSSION: This is a novel, brief, communication-focused intervention for parents/guardians that was designed to reduce participant burden. The intervention has the potential to improve parent-child engagement and communication and conversations about substance use specifically and decrease child substance use risk factors and substance use initiation. TRIAL REGISTRATION: ClinicalTrials.gov NCT03925220. Registered on 24 April 2019.

Analysis of 567,758 randomized controlled trials published over 30 years reveals trends in phrases used to discuss results that do not reach statistical significance.

The power of language to modify the reader's perception of interpreting biomedical results cannot be underestimated. Misreporting and misinterpretation are pressing problems in randomized controlled trials (RCT) output. This may be partially related to the statistical significance paradigm used in clinical trials centered around a P value below 0.05 cutoff. Strict use of this P value may lead to strategies of clinical researchers to describe their clinical results with P values approaching but not reaching the threshold to be "almost significant." The question is how phrases expressing nonsignificant results have been reported in RCTs over the past 30 years. To this end, we conducted a quantitative analysis of English full texts containing 567,758 RCTs recorded in PubMed between 1990 and 2020 (81.5% of all published RCTs in PubMed). We determined the exact presence of 505 predefined phrases denoting results that approach but do not cross the line of formal statistical significance (P < 0.05). We modeled temporal trends in phrase data with Bayesian linear regression. Evidence for temporal change was obtained through Bayes factor (BF) analysis. In a randomly sampled subset, the associated P values were manually extracted. We identified 61,741 phrases in 49,134 RCTs indicating almost significant results (8.65%; 95% confidence interval (CI): 8.58% to 8.73%). The overall prevalence of these phrases remained stable over time, with the most prevalent phrases being "marginally significant" (in 7,735 RCTs), "all but significant" (7,015), "a nonsignificant trend" (3,442), "failed to reach statistical significance" (2,578), and "a strong trend" (1,700). The strongest evidence for an increased temporal prevalence was found for "a numerical trend," "a positive trend," "an increasing trend," and "nominally significant." In contrast, the phrases "all but significant," "approaches statistical significance," "did not quite reach statistical significance," "difference was apparent," "failed to reach statistical significance," and "not quite significant" decreased over time. In a random sampled subset of 29,000 phrases, the manually identified and corresponding 11,926 P values, 68,1% ranged between 0.05 and 0.15 (CI: 67. to 69.0; median 0.06). Our results show that RCT reports regularly contain specific phrases describing marginally nonsignificant results to report P values close to but above the dominant 0.05 cutoff. The fact that the prevalence of the phrases remained stable over time indicates that this practice of broadly interpreting P values close to a predefined threshold remains prevalent. To enhance responsible and transparent interpretation of RCT results, researchers, clinicians, reviewers, and editors may reduce the focus on formal statistical significance thresholds and stimulate reporting of P values with corresponding effect sizes and CIs and focus on the clinical relevance of the statistical difference found in RCTs.

Assessing the efficacy of an integrated intervention to create demand for fishermen's schistosomiasis and HIV services (FISH) in Mangochi, Malawi: Study protocol for a cluster randomized control trial.

BACKGROUND: Both HIV and schistosomiasis are major public health problems worldwide with 1.8 million new HIV infections, and up to 110 million untreated schistosomiasis cases globally. Although a causal link has not been established, there are strong suggestions that having schistosomiasis increases onward transmission of HIV from co-infected men to women. With both HIV and schistosomiasis treatment readily available in Malawi, there is a need to investigate the feasibility, acceptability and health impacts of joint management of these two hazards, with special focus on health education and demand-creation for fishermen. The aim of this project is to identify optimal models of delivering integrated HIV and schistosomiasis services for fishermen, particularly investigating the effect of using social networks, HIV self-test kits and beach clinic services in Mangochi, Malawi. METHODS: We have mapped 45 boat teams or landing sites for a 3-arm cluster randomized trial using "boat team" as the unit of randomization. The three arms are: 1) Standard of care (SOC) with leaflets explaining the importance of receiving presumptive treatment for schistosomiasis (praziquantel) and HIV services for fishermen, and two intervention arms of 2) SOC + a peer explaining the leaflet to his fellow fishermen in a boat team; and 3) arm 2 with HIV self-test kits delivered to the boat team fishermen by the peer. The primary outcomes measured at 9 months of trial delivery will compare differences between arms in the proportions of boat-team fishermen: 1) who self-report starting antiretroviral therapy or undergoing voluntary medical male circumcision; and 2) who have ≥1 S. haematobium egg seen on light microscopy of the filtrate from 10mls urine ("egg-positive"). DISCUSSION: This is the first evaluation of an integrated HIV and schistosomiasis services intervention for fishermen, particularly investigating the effect of using social networks, HIVST kits and beach clinic services. The findings will support future efforts to integrate HIVST with other health services for fishermen in similar settings if found to be efficacious. TRIAL REGISTRATION: This trial is registered in the ISRCTN registry: ISRCTN14354324; date of registration: 05 October 2020. https://www.isrctn.com/ISRCTN14354324?q=ISRCTN14354324&filters=&sort=&offset=1&totalResults=1&page=1&pageSize=10&searchType=basic-search. Linked to protocol version number 1.4 of 11 January 2021.

Metastatic gastroesophageal cancer in older patients - is this patient cohort represented in clinical trials?

BACKGROUND: Older patients are underrepresented in the clinical trials that determine the standards of care for oncological treatment. We conducted a review to identify whether there have been age-restrictive inclusion criteria in clinical trials over the last twenty five years, focusing on patients with metastatic gastroesophageal cancer. METHODS: A search strategy was developed encompassing Embase, PubMed and The Cochrane Library databases. Completed phase III randomised controlled trials evaluating systemic anti-cancer therapies in metastatic gastroesophageal malignancies from 1st January 1995 to 18th November 2020 were identified. These were screened for eligibility using reference management software (Covidence; Veritas Health Innovation Ltd). Data including age inclusion/exclusion criteria and median age of participants were recorded. The percentage of patients ≥ 65 enrolled was collected where available. The change over time in the proportion of studies using an upper age exclusion was estimated using a linear probability model. RESULTS: Three hundred sixty-three phase III studies were identified and screened, with 66 trials remaining for final analysis. The majority of trials were Asian (48%; n = 32) and predominantly evaluated gastric malignancies, (86%; n = 56). The median age of participants was 62 (range 18-94). Thirty-two percent (n = 21) of studies specified an upper age limit for inclusion and over half of these were Asian studies. The median age of exclusion was 75 (range 65-80). All studies prior to 2003 used an upper age exclusion (n = 12); whereas only 9 that started in 2003 or later did (17%). Among later studies, there was a very modest downward yearly-trend in the proportion of studies using an upper age exclusion (-0.02 per year; 95%CI -0.05 to 0.01; p = 0.31). Fifty-two percent (n = 34) of studies specified the proportion of their study population who were ≥ 65 years. Older patients represented only 36% of the trial populations in these studies (range 7-60%). CONCLUSIONS: Recent years have seen improvements in clinical trial protocols, with many no longer specifying restrictive age criteria. Reasons for poor representation of older patients are complex and ongoing efforts are needed to broaden eligibility criteria and prioritise the inclusion of older adults in clinical trials.

Prophylactic dialysis improves short-term clinical outcome in patients with non-dialysis-dependent chronic kidney disease undergoing cardiac surgery: a meta-analysis of randomized controlled trials.

BACKGROUND: Several studies have reported that prophylactic dialysis can reduce the mortality of non-dialysis-dependent chronic kidney disease (CKD) patients after cardiac surgery. However, the results of complications in these randomized controlled trials (RCTs) were not consistent. We aimed to perform a meta-analysis to systematically evaluate the effect of prophylactic dialysis in these non-dialysis-dependent CKD patients. METHODS: We systematically searched Medline, Embase, Cochrane's Library and other online sources for related RCTs. Effects of prophylactic dialysis on the incidence of 30 days' mortality and postoperative complications were analyzed. RESULTS: Four RCTs comprising 395 patients were included, all of them treated by coronary artery bypass grafting. Treatment of preoperative and intraoperative prophylactic dialysis significantly reduced the rate of 30-day all-cause mortality (risk ratio [RR]: 0.27, 95% confidence interval [CI], 0.13-0.58, P < 0.001, I2 = 0%) and the incidence of pulmonary complications (RR: 0.39, 95% CI, 0.20-0.77, P = 0.007, I2 = 0%), low cardiac output (RR: 0.29, 95% CI, 0.09-0.99, P = 0.05, I2 = 0%), and acute kidney injury (RR: 0.19, 95% CI: 0.07-0.52, P = 0.001, I2 = 0%). However, there were no statistically significant differences between the dialysis group and the control group in gastrointestinal bleeding, sepsis or multiple organ failure, wound infection, arrhythmia, transient neurologic deficit, stroke and re-exploration for bleeding. CONCLUSION: Prophylactic dialysis can improve the 30-day clinical outcomes of non-dialysis-dependent CKD patients undergoing cardiac surgery, it was associated with the 30-day mortality benefit and led to a decrease in the incidence of pulmonary complications, as well as low cardiac output, and acute kidney injury.

Efficacy and safety of antiseizure medication for Lennox-Gastaut syndrome: a systematic review and network meta-analysis.

AIM: To compare and rank the efficacy and safety of antiseizure medication (ASM) in patients with Lennox-Gastaut syndrome (LGS). METHOD: We included randomized controlled trials (RCTs) assessing the efficacy of ASM for LGS compared with placebo or with each other. The efficacy and safety were reported in terms of an at least 50% monthly seizure frequency reduction in drop seizures, dropout, and serious adverse events. Outcomes were ranked according to the surface under the cumulative ranking curve (SUCRA). RESULTS: A total of eight RCTs with 1171 patients were included, involving six ASMs: lamotrigine, rufinamide, cannabidiol, topiramate, clobazam, and felbamate. The calculated SUCRA showed that rufinamide, cannabidiol, and topiramate had the highest probability of achieving a response; however, no significant differences were found among these treatments. Cannabidiol, topiramate, and rufinamide were more likely to result in dropouts; moreover, a significantly greater percentage of patients receiving cannabidiol experienced premature discontinuation as compared to placebo, clobazam, and lamotrigine. INTERPRETATION: All ASMs showed a significantly higher response rate than placebo. SUCRA ranking demonstrated that rufinamide and cannabidiol are more efficacious than other treatments in reducing drop seizures. However, there was no significant difference between these treatments.