Differences In Clinical Trials Research Articles

Sample size calculations based on day-to-day variability of stress biomarkers in persons with dementia and their family caregivers

Introduction: Accurate estimates of intra-individual variability are necessary for proper design of clinical trials and epidemiological studies where the stress biomarkers cortisol and dehydroepiandrosterone sulfate (DHEA-S) are measured for dyads of persons with dementia (PWDs) and their family caregivers (FCGs). The aim is to determine the number of consecutive sampling days required to detect effect differences in clinical trials, and to accurately estimate regression coefficients in epidemiological studies where stress biomarkers are exposure variables in regression models with future disease as outcome. Methods: Clinical trial data from dyads of PWDs and their FCGs were used. Salivary cortisol and DHEA-S samples were collected five days a week, for eight consecutive weeks. From this data, we created formulas and graphical tools for the number of required sampling days needed to detect effect differences, and we calculated number of days needed for regression coefficients to be estimated with<10% bias. Results: A total of 5791 salivary samples from 34 dyads were used. For morning cortisol, five consecutive sampling days at baseline and an equal number of days at study termination is sufficient to detect a treatment difference>5% of baseline level with>20 dyads per group. When stress biomarkers are used in epidemiological studies at least six consecutive sampling days are required. Conclusion: Based on a large number of consecutive measurements of stress biomarkers we calculated the sufficient numbers of sampling days for clinical trials and for epidemiological studies to produce credible results. Our findings will aid researchers in the study design phase.

Effect of a correlated competing risk on marginal survival estimation in an accelerated failure time model

In problems with a time to event outcome, subjects may experience competing events, which censor the outcome of interest. Cox’s partial likelihood estimator treating competing events as independent censoring is commonly used to examine group differences in clinical trials but fails to adjust for omitted covariates and can bias the assessment of marginal benefit. A bivariate normal linear model generating latent data with dependent censoring is used to assess this bias. Our R-package bnc provides maximum penalized likelihood (MPL) parameter estimation using a novel EM algorithm. Using bnc, we study the properties of such MPL estimation. Simulation results for two-sample survival comparisons of time to an event of interest, with independent censoring accompanied by censoring from a correlated competing risk, are presented. Key parameters—means, hazard ratios, and correlation—are estimated. These results demonstrated that, despite ill-conditioning in models generating correlated competing risks, estimates of marginal effects are reliable. Bivariate normal models were fitted in a trial of head and neck cancer. Model fits help with clinical interpretation while also supplementing other standard methods for follow-up that are terminated by intervening risks.

Female Recruitment Into Cardiovascular Disease Trials

Female Recruitment Into Cardiovascular Disease Trials

Sex differences in clinical trials of ALRV5XR treatment of androgenetic alopecia and telogen effluvium.

IntroductionALRV5XR treatment of androgenetic alopecia (AGA) and telogen effluvium (TE) has early evidence of regenerating a normal scalp hair phenotype in both sexes.DesignWe performed two 24-week double-blinded placebo-controlled comparison trials, one in each sex, on the ALRV5XR treatment effect on hair regeneration, in AGA and TE, in 92 AGA subjects (24 also had TE). Forty-six women (age 24–64 years) and 46 men (age 22–63 years) were randomized 1:1 to either ALRV5XR or placebo regimens (one b.i.d. oral capsule and daily administration of shampoo, conditioner, and follicle serum).EvaluationPrimary outcomes: Absolute and relative changes in terminal hair (TH) density. Secondary outcomes: Response rate, changes in vellus hair (VH) density, TH/VH ratio, hair diameter, growth, and shedding rate.ResultsForty-one women (20 ALRV5XR, 21 placebo) and 36 men (17 ALRV5XR, 19 placebo) completed the trials. TH outcome was evaluable for 18 and 21 women and 11 and 11 men (ALRV5XR, placebo, respectively). Efficacy in women: 30.1 THs/cm2 (p = 0.0002) and 19.7% (p = 0.0016). Efficacy in men: 21.0 THs/cm2 (p = 0.0014) and 16.4% (p = 0.0012). 66.7% of women and 100% of men responded to ALRV5XR. TH/VH ratio for men increased 33.0% (p = 0.0033). Growth rate in women increased by 30.7 μm/24 h (p < 0.0001) and 10.0% (p < 0.0001). There were no adverse events reported.Conclusion and relevanceALRV5XR induced significant regrowth of TH. Accelerating regrowth by reactivation of dormant telogen follicles were the dominant effects in women. Thickening of miniaturized hair and regrowth of dormant telogen follicles contributed equally to the increased TH seen in men (see Graphical ).

Clinical trials cannot provide sufficient accuracy for studying weak factors necessary for curing chronic diseases

Chronic diseases are still known as incurable diseases, and we suspect that the medical research model is unfit for characterizing chronic diseases. In this study, we examined accuracy and reliability required for characterizing chronic diseases, reviewed implied presumptions in clinical trials and assumptions used in statistical analysis, examined sources of variances normally encountered in clinical trials, and conducted numeric simulations by using hypothetical data for several theoretical and hypothetical models. We found that the sources of variances attributable to personal differences in clinical trials can distort hypothesis test outcomes, that clinical trials introduce too many errors and too many inaccuracies that tend to hide weak and slow-delivering effects of treatments, and that the means of treatments used in statistical analysis have little or no relevance to specific patients. We further found that a large number of uncontrolled co-causal or interfering factors normally seen in human beings can greatly enlarge the means and the variances or experimental errors, and the use of high rejection criteria (e.g., small p values) further raises the chances of failing to find treatment effects. As a whole, we concluded that the research model using clinical trials is wrong on multiple grounds under any of our realistic theoretical and hypothetical models, and that misuse of statistical analysis is most probably responsible for failure to identify treatment effects for chronic diseases and failure to detect harmful effects of toxic substances in the environment. We proposed alternative experimental models involving the use of single-person or mini optimization trials for studying low-risk weak treatments.

A novel statistical test for treatment differences in clinical trials using a response-adaptive forward-looking Gittins Index Rule.

The most common objective for response-adaptive clinical trials is to seek to ensure that patients within a trial have a high chance of receiving the best treatment available by altering the chance of allocation on the basis of accumulating data. Approaches that yield good patient benefit properties suffer from low power from a frequentist perspective when testing for a treatment difference at the end of the study due to the high imbalance in treatment allocations. In this work we develop an alternative pairwise test for treatment difference on the basis of allocation probabilities of the covariate-adjusted response-adaptive randomization with forward-looking Gittins Index (CARA-FLGI) Rule for binary responses. The performance of the novel test is evaluated in simulations for two-armed studies and then its applications to multiarmed studies are illustrated. The proposed test has markedly improved power over the traditional Fisher exact test when this class of nonmyopic response adaptation is used. We also find that the test's power is close to the power of a Fisher exact test under equalrandomization.

Reliability, validityand important difference estimates for the NCCN-FACT Ovarian Symptom Index-18 (NFOSI-18).

Objective: To evaluate psychometric performance of the NCCN-FACT Ovarian Cancer Symptom Index-18 (NFOSI-18) in advanced ovarian cancer. Methods: Cross-sectional, observational data from patients receiving treatment for ovarian cancer. Other measures included European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire core (EORTC QLQ-C30) and associated ovarian cancer module (EORTC QLQ-OV28) and Work Productivity and Activity Impairment. Internal consistency reliability, construct validity and anchor-based clinically important differences were assessed. Results: 897 patients were analyzed. Reliability was acceptable for all NFOSI-18 scores; construct validity was supported. Twelve anchors sufficiently correlated with NFOSI-18 scores and suggested clinically important differences: NFOSI-18 total score (5-7), disease-related symptoms - physical (3-4), disease-related symptoms - emotional (1), treatment side effects (2)and functional well-being (1-2). Conclusions: Results provide evidence of reliability and validity of NFOSI-18 scores. Generated CIDs will help improve interpretation of between-group treatment differences in clinical trials.

Analysis of Female Enrollment and Participant Sex by Burden of Disease in US Clinical Trials Between 2000 and 2020

Although female representation has increased in clinical trials, little is known about how clinical trial representation compares with burden of disease or is associated with clinical trial features, including disease category. To describe the rate of sex reporting (ie, the presence of clinical trial data according to sex), compare the female burden of disease with the female proportion of clinical trial enrollees, and investigate the associations of disease category and clinical trial features with the female proportion of clinical trial enrollees. This cross-sectional study included descriptive analyses and logistic and generalized linear regression analyses with a logit link. Data were downloaded from the Aggregate Analysis of ClinicalTrials.gov database for all studies registered between March 1, 2000, and March 9, 2020. Enrollment was compared with data from the 2016 Global Burden of Disease database. Of 328 452 clinical trials, 70 095 were excluded because they had noninterventional designs, 167 936 because they had recruitment sites outside the US, 69 084 because they had no reported results, 1003 because they received primary funding from the US military, and 314 because they had unclear sex categories. A total of 20 020 interventional studies enrolling approximately 5.11 million participants met inclusion criteria and were divided into those with and without data on participant sex. The primary exposure variable was clinical trial disease category. Secondary exposure variables included funding, study design, and study phase. Sex reporting and female proportion of participants in clinical trials. Among 20 020 clinical trials from 2000 to 2020, 19 866 studies (99.2%) reported sex, and 154 studies (0.8%) did not. Clinical trials in the fields of oncology (46% of disability-adjusted life-years [DALYs]; 43% of participants), neurology (56% of DALYs; 53% of participants), immunology (49% of DALYs; 46% of participants), and nephrology (45% of DALYs; 42% of participants) had the lowest female representation relative to corresponding DALYs. Male participants were underrepresented in 8 disease categories, with the greatest disparity in clinical trials of musculoskeletal disease and trauma (11.3% difference between representation and proportion of DALYs). Clinical trials of preventive interventions were associated with greater female enrollment (adjusted relative difference, 8.48%; 95% CI, 3.77%-13.00%). Clinical trials in cardiology (adjusted relative difference, -18.68%; 95% CI, -22.87% to -14.47%) and pediatrics (adjusted relative difference, -20.47%; 95% CI, -25.77% to -15.16%) had the greatest negative association with female enrollment. In this study, sex differences in clinical trials varied by clinical trial disease category, with male and female participants underrepresented in different medical fields. Although sex equity has progressed, these findings suggest that sex bias in clinical trials persists within medical fields, with negative consequences for the health of all individuals.

Characteristics of Industry-Sponsored Drug Clinical Trials Registered in Japan Pharmaceutical Information Center Clinical Trials Information 2010-2018.

To examine the trends and characteristics of industry-sponsored drug clinical trials registered in the JapicCTI (Japan Pharmaceutical Information Center Clinical Trials Information) in 2010-2018. A data set of 3116 clinical trials registered from Jan. 2010 to Dec. 2018 were analyzed. Fundamental characteristics of the clinical trials were analyzed by 3-year time periods. The analysis was also focused on 3 therapeutic areas: cardiovascular, mental health, and oncology. Of all the trials (2010-2018), 74.7% were conducted in Japan only; the rate decreased from 82.8 to 65.3% over the 3 time periods. Most trials were phase 3 trials, which comprised 44.1% of the trials. Small trials (anticipated number of 1000 or fewer participants) made up 94.0% of the trials. Oncology trials (29.5%) were the most common type and involved more phase 1 trials than mental health and cardiovascular trials (33.6% vs 14.5% and 11.5%, respectively). Oncology trials composed the smallest proportion of trials conducted in "Japan only" at 57.3% vs 81.0% and 83.1% for mental health and cardiovascular trials, respectively (p < 0.001). The median of the anticipated number of participants in mental health trials were larger than those in cardiovascular and oncology trials (p = 0.001). Mental health trials were more likely to permit children under age 15 (10.9% vs 4.9% for cardiovascular and 1.2% for oncology). Oncology trials were more likely not to set an upper age limit (89.8% vs 51.4% for cardiovascular and 41.7% for mental health). Cardiovascular and mental health trials were more likely to be conducted as "double blind" (42.4% and 47.1%, respectively vs 16.7% for oncology). During this time, the majority of industry-sponsored trials in Japan were phase 3 trials, Japan only and small trials. There were differences in clinical trials among the 3 therapeutic areas: size of the trial, globalization, phase, age of participants, blinding.

Greater Dynamic and Lower Static Functional Brain Connectivity Prospectively Predict Placebo Response in Pediatric Generalized Anxiety Disorder.

Objectives: Placebo response is one of the most significant barriers to detecting treatment effects in pediatric (and adult) clinical trials focusing on affective and anxiety disorders. We sought to identify neurofunctional predictors of placebo response in adolescents with generalized anxiety disorder (GAD) by examining dynamic and static functional brain connectivity. Methods: Before randomization to blinded placebo, adolescents, aged 12-17 years, with GAD (N = 25) underwent resting state functional magnetic resonance imaging. Whole brain voxelwise correlation analyses were used to determine the relationship between change in anxiety symptoms from baseline to week 8 and seed-based dynamic and static functional connectivity maps of regions in the salience and ventral attention networks (amygdala, dorsal anterior cingulate cortex [dACC], and ventrolateral prefrontal cortex [VLPFC]). Results: Greater dynamic functional connectivity variability in amygdala, dACC, VLPFC, and regions within salience, default mode, and frontoparietal networks was associated with greater placebo response. Lower static functional connectivity between amygdala and dorsolateral prefrontal cortex, amygdala and medial prefrontal cortex, dACC and posterior cingulate cortex and greater static functional connectivity between VLPFC and inferior parietal lobule were associated with greater placebo response. Conclusion: Placebo response is associated with a distinct dynamic and static connectivity fingerprint characterized by "variable" dynamic but "weak" static connectivity in the salience, default mode, frontoparietal, and ventral attention networks. These data provide granular evidence of how circuit-based biotypes mechanistically relate to placebo response. Finding biosignatures that predict placebo response is critically important in clinical psychopharmacology and to improve our ability to detect medication-placebo differences in clinical trials.

Testing for baseline differences in clinical trials

&lt;p class="abstract"&gt;Reporting statistical tests for baseline measures of clinical trials does not make sense since the statistical significance is dependent on sample size, as a large trial can find significance in the same difference that a small trial did not find to be statistically significant. We use 3 published trials using the same baseline measures to provide the relationship between trial sample size and p value. For trial 1 sequential organ failure assessment (SOFA) score, p=0.01, 10.4±3.4 vs. 9.6±3.2, difference=0.8; p=0.007 for vasopressors, 83.0% vs. 72.6%. Trial 2 has SOFA score 11±3 vs. 12±3, difference=1, p=0.42. Trial 3 has vasopressors 73% vs. 83%, p=0.21. Based on trial 2, supine group has a mean of 12 and an SD of 3 for SOFA score, while prone group has a mean of 11 and an SD of 3 for SOFA score. The p values are 0.29850, 0.09877, 0.01940, 0.00094, 0.00005, and &amp;lt;0.00001 when n (per arm) is 20, 50, 100, 200, 300 and 400, respectively. Based on trial 3 information, the vasopressors percentages are 73.0% in the supine group vs. 83.0% in the prone group. The p values are 0.4452, 0.2274, 0.0878, 0.0158, 0.0031, and 0.0006 when n (per arm) is 20, 50, 100, 200, 300 and 400, respectively. Small trials provide larger p values than big trials for the same baseline differences. We cannot define the imbalance in baseline measures only based on these p values. There is no statistical basis for advocating the baseline difference tests&lt;/p&gt;

Sex and Gender Differences in Rilpivirine based ART - Data from the HIVCENTER Frankfurt

While Rilpivirine has shown high overall response rates in treatment-naïve patients without sex and gender specific differences in clinical trials, Sex and gender specific data in treatment experienced patients receiving rilpivirine are still limited. We conducted a 48 week efficacy and safety analysis in naïve and treatment experienced men and women using retrospective data from the HIVCENTER Frankfurt. In this retrospective observational study data of all patients who received a rilpivirine based regimen at the HIVCENTER between March 2011 and December 2015 were analyzed. Primary endpoint was the proportion of patients with any discontinuation until week 48. Virologic response rates (FDA snapshot analysis; HIV-1 RNA <50 copies/mL) were assessed at week 48. 194 patients (34% female) were included in the analysis. 74% were treatment-experienced and 26% naïve, respectively. Discontinuations were observed in 31 (15.9%) patients. Regarding sex differences, the proportion of discontinuations was significantly higher in women than in men (24.2% vs. 11.7%; p=0.024; ODDS-Ratio = 2.41; CI 1.12 - 5.18). Virologic failure occurred in 8 PLWHIV (4.1%). While virologic overall response rates to rilpivirine based ART were high for both treatment-experienced and -naïve patients the proportion of discontinuations was significantly higher in women (24.2% vs. 11.7%; p = 0.024; ODDS-Ratio = 2.41; CI 1.12 - 5.18). Although the total number of patients with virologic failure was low (4.1%), the higher rate of ART discontinuations in female patients receiving RPV require close monitoring in the first months of treatment addressing special needs of women living with HIV.

Exact confidence limits for proportion difference in clinical trials with bilateral outcome

Bilateral data are frequently occur in medical research. Asymptotic approaches are traditionally used to construct confidence intervals for proportion difference. However, they are often have unsatisfactory performance with regards to coverage, with the actual coverage below the nominal level or being too conservative. For these reasons, we propose developing exact one-sided limits for proportion difference in a parallel study with bilateral data to guarantee the coverage probability when sample size is small to medium. A statistical quantity has to be used for sample space ordering in the exact limit calculation. Four asymptotic limits are utilized as statistical quantities: the Wald limits under the independence or dependence assumptions for variance estimates, the Wald limits with the difference estimate under the dependence assumption, and the bootstrap percentile limits. We compare the performance of these exact limits with regards to average length and the limits of all possible samples. A real example from a randomized clinical trial in otolaryngology is used to illustrate the application of the proposed exact limits.

PMU46 TRIAL SEPARATION - IS THERE A TRUE GENDER DISPARITY IN CLINICAL TRIALS?

The gender imbalance in clinical studies has been widely discussed with women underrepresented in trial populations and becoming a growing concern. However, there may be several mitigating factors such as ability to recruit, gender-specific diseases, incidence variations and genetic predispositions. To drive a change in gender bias in this aspect of clinical research, more incisive analyses are required to define the true difference and understand the root causal relationship. This research aims to assess the current state of the gender disparity in pivotal clinical trials supporting recent FDA (Food and Drug Administration) CDER (Center for Drug Evaluation and Research) novel drug approvals. Publicly-available FDA CDER Drug Trial Snapshots were used to identify the gender split in participants of key trials supporting novel drug approvals between 01/01/2014-31/12/2018. For the 172 novel drugs approved by the FDA between 2014 to 2018, there were 106,894 (49.4%) male subjects, and 109,600 (50.6%) female subjects in total. In terms of specific therapy areas, for the 50 novel oncology drugs, there were 9,201 (45.4%) male subjects and 11,066 (54.6%) female subjects. For the 9 novel cardiovascular drugs, there were 33,721 (55.8%) male subjects, and 26,683 (44.2%) female subjects. However, there are a number of women-specific diseases which had zero male subjects in the trials such as ovarian cancer and bacterial vaginosis. There are also rare hereditary genetic diseases which had zero female trial subjects such as Duchenne muscular dystrophy and hemophilia A. Despite the inherent mitigating factors, the gender disparity remains unclear with women well-represented, underrepresented, or overrepresented in trials of novel drugs depending on the therapy area. Recruitment and retention of women in clinical studies is a key challenge requiring further research to defining the true gender differences in clinical trials and also to develop strategies to overcome these differences.

Pulmonary Surfactant Preparations and Surfactant Therapy for ARDS in Surgical Intensive Care (a Literature Review)

Introduction.Despite the fact that clinical studies of pulmonary surfactants conducted over many years have demonstrated their efficacy for the treatment of acute respiratory distress syndrome (ARDS) which led to their approval for use inRussia andBelarus, only a few similar positive results have been achieved in other countries. This calls for an extensive literature review for intensive care professionals.Materials and methods.Using the data from 87 papers this review covers the composition, properties, methods of administration and delivery strategies of surfactant in the treatment and prevention of ARDS in patients with sepsis, severe complex injuries, inhalation injuries and a range of complications associated with thoracic and cardiovascular surgical procedures, massive blood transfusions, severe obstetric pathologies and the A/H1N1 pneumonia.Results.The early administration of natural pulmonary surfactants within 24 hours following the onset of ARDS as a part of the ARDS combination treatment or prevention drives down the time on mechanical ventilation to six days or shorter, prevents ventilator-associated and hospital-acquired pneumonias, bringing the respiratory failure mortality rate down to 15–20%.Discussion.Offering the first attempt to discuss the causes of failure of Phase III multicenter clinical trials outsideRussia andBelarus, this review outlines recent developments in synthetic and powdered pulmonary surfactant preparations.Conclusion. Pulmonary surfactants are highly effective as a part of complex therapy in ARDS treatment and prevention, resulting in two to four fold drop in ARDS mortality rate. The timing of administration is seen as the key factor of the efficacy of surfactant therapy, explaining the differences in clinical trials results from different countries.

Effect of probiotic interventions on depressive symptoms: A narrative review evaluating systematic reviews.

Depression is one of the most prevalent mental illnesses and is often associated with various other medical disorders. Since the 1980s, the primary pharmacological treatment has been antidepressants, but due to the recent discovery of the association between the gut microbiome and mental health, probiotics have been proposed as an adjunctive or alternate treatment. In this narrative review, we aim to provide a holistic perspective by synthesizing and evaluating existing evidence, discussing key biological mechanisms, exploring the history of probiotic use, and appreciating the influence of modern diet on mental health. Five online databases were searched for relevant studies up to December 2017. Systematic reviews that included randomized controlled trials assessing the efficacy of probiotics in the treatment of depressive symptoms were included. Seven systematic reviews met the inclusion criteria. Three of these reviews conducted meta-analyses, out of which, two concluded that probiotics improved depressive symptoms in the sample population. Out of the four reviews that conducted qualitative analysis, three reviews concluded that probiotics have the potential to be used as a treatment. Due to the differences in clinical trials, a definitive effect of probiotics on depressive symptoms cannot be concluded. Nonetheless, probiotics seem to potentially produce a significant therapeutic effect for subjects with pre-existing depressive symptoms. Further studies are warranted for definitive conclusions.

Randomized Clinical Trial Is Biased and Invalid In Studying Chronic Diseases, Compared with Multiple Factors Optimization Trial

Chronic diseases are still known as incurable diseases, and we suspect that the medical research model is unfit for characterizing chronic diseases. In this study, we examined accuracy and reliability required for characterizing chronic diseases, reviewed implied presumptions in clinical trials and assumptions used in statistical analysis, examined sources of variances normally encountered in clinical trials, and conducted numeric simulations by using hypothetical data for several theoretical and hypothetical models. We found that the sources of variances attributable to personal differences in clinical trials can distort hypothesis test outcomes, that clinical trials introduce too many errors and too much inaccuracies that tend to hide weak and slow effects of treatments, and that the means of treatments used in statistical analysis have little or no relevance to specific patients. We further found that a large number of uncontrolled co-causal or interfering factors normally seen in human subjects can greatly enlarge the means and the variances of the experimental errors, and the use of high rejection criteria (e.g., low p values) further raises the chances of failing to find treatment effects. As a whole, we concluded that the research model using clinical trials is wrong on multiple grounds, under any of our realistic theoretical and hypothetical models, and that misuse of statistical analysis is most probably responsible for failure to identify treatment effects for chronic diseases and to detect harmful effects of toxic substances in the environment. We proposed alternative experimental models involving the use of single-person or mini optimization trials for studying low-risk weak treatments. Conclusions: The total gain in treatment effects existing in an optimization trial over a clinical trial is (1/g)*k while all test statistics such as T statistic, Z statistic, and F statistic used in hypothesis tests are increased by (1/g)*k*√k, where 1/g is attributed to avoiding negating effects, k is attributed to the additive effect of multiple treatment factors, and √k is attributed to reduction in the error variances. Their collective impacts could be huge. This conclusively shows why medicine could not find “scientific evidence” for any treatment based on a single lifestyle factor.

Head-to-head trials of systemic psoriasis therapies: a systematic review of study design and maximum acceptable treatment differences.

There is increasing use of head-to-head clinical trials in dermatology when establishing the efficacy of a new treatment. Active comparator trials (ACTs) can be classified into three distinct study trial designs: non-inferiority, equivalence and superiority. A better understanding of the statistical parameters, such as acceptable treatment differences (also known as the margin or delta), is necessary to properly design and interpret findings of active comparator trials (ACTs) in the field of dermatology. Therefore, the objective of this study was to summarize the maximum acceptable treatment differences in clinical trials that examine the efficacy of an oral or biologic psoriasis therapy with an active comparator. We conducted a systematic search using MEDLINE, Scopus, EMBASE, Cochrane Central Register of Controlled Trials, LILACS, Web of Science and ClinicalTrials.gov from inception to 31 August 2017. All ACTs with adult participants that had a primary outcome of the Psoriasis Area and Severity Index score were included. Bibliographies of articles were further reviewed. Two investigators independently assessed for article inclusion and separately completed data extraction of predefined data points. When there was a disagreement, a third investigator was consulted. Of the 49 ACTs included, there were 13 superiority, eight non-inferiority and seven equivalence trials. Another 21 studies had inadequate information for classification. All of the non-inferiority trials reported the margin, one of the superiority and six of the equivalence trials stated the treatment difference explicitly. For superiority trials, acceptable treatment differences ranged from 14% to 20%. The non-inferiority studies reported lower bound margins ranging from -20% to -10%. The equivalence trials reported upper and lower bound margins ranging from ±12.5% to ±18%. The results demonstrate the need for harmonization in the conduct of dermatological clinical trials and in the approaches of reporting research parameters.

Gender differences in clinical trials of binge eating disorder: An analysis of aggregated data.

The aim of the study was to examine gender differences in baseline and outcome variables in clinical trials for binge eating disorder (BED). Data from 11 randomized controlled psychosocial treatment studies were aggregated (N = 1,325: 208 male, 1,117 female). Baseline and outcome symptoms were assessed via the interview and questionnaire versions of the Eating Disorder Examination (EDE). Multilevel analyses were conducted investigating gender differences at baseline and posttreatment, defined as EDE scores, objective binge episode (OBE) reduction, and OBE remission at termination. Few males from low socioeconomic status or minority groups participated in the outcome studies. Males reported significantly lower EDE global, shape, weight, and eating concerns at baseline. No main effects of gender were found in treatment outcome scores when controlling for baseline differences; however, baseline EDE global score (which showed gender differences at baseline) and OBEs directly predicted outcome for both males and females. A significant interaction between gender, treatment length, and shape/weight concerns indicated that males with lower shape/weight concerns achieved OBE remission in shorter treatments, whereas men with high shape/weight concerns and women with either high or low shape/weight concerns were more likely to achieve OBE remission in treatments of longer duration. These results suggest BED treatment studies must improve their recruitment of men and appeal to men with lower shape/weight concerns. Additionally, longer term treatments, although more efficacious for women and men with more severe shape/weight concerns, may not be necessary for men with low shape/weight concerns. (PsycINFO Database Record

The potential for a controlled human infection platform in Singapore.

For over 100 years, controlled human infection (CHI) studies have been performed to advance the understanding of the pathogenesis, treatment and prevention of infectious diseases. This methodology has seen a resurgence, as it offers an efficient model for selecting the most promising agents for further development from available candidates. CHI studies are utilised to bridge safety and immunogenicity testing and phase II/III efficacy studies. However, as this platform is not currently utilised in Asia, opportunities to study therapeutics and vaccines for infections that are important in Asia are missed. This review examines the regulatory differences for CHI studies between countries and summarises other regulatory differences in clinical trials as a whole. We found that the regulations that would apply to CHI studies in Singapore closely mirror those in the United Kingdom, and conclude that the regulatory and ethical guidelines in Singapore are compatible with the conduct of CHI studies.