Trial Sample Size Research Articles

An Assessment of Randomized Controlled Trial Quality in The Journal of Bone & Joint Surgery: Update from 2001 to 2013.

The quality of reporting of randomized controlled trials (RCTs) published in The Journal of Bone & Joint Surgery (JBJS) from 1988 to 2000 was previously analyzed. The purpose of this current study was to analyze the quality of reporting of RCTs published in JBJS from 2001 to 2013 to identify trends over time and potential areas of improvement for future clinical trials. A manual search of the JBJS database identified RCTs published between January 2001 and December 2013. Quality assessments, using the Detsky quality-of-reporting index (Detsky score), a modified Cochrane risk-of-bias tool, and abstraction of relevant data identifying predictors of quality, were conducted. A total of 5,780 publications were identified in JBJS from 2001 to 2013, with 285 RCTs (4.9%), representing an increase from the prior 13-year period. The overall mean transformed Detsky score (and standard error) increased significantly (p < 0.001) from 68.1% ± 1.67% to 76.24% ± 0.72%. The percentage of multicenter RCTs decreased from 67% to 31%. The percentage of positive trials also decreased from 80% to 50.5%, as did the mean sample size (212 to 166). Regression analysis indicated that trials with an epidemiologist as the first author and nonsurgical trials were significantly associated (p = 0.001) with a higher overall trial quality score. The categories of the lowest mean methodology scores were randomization and concealment, eligibility criteria, and reasons for patient exclusion, as identified with the Detsky score, and patient and assessor blinding, as identified with the risk-of-bias assessment. The quantity and quality of published RCTs in JBJS have increased in the 2001 to 2013 time period compared with the previous time period. Although these improvements are encouraging, trends to smaller, single-center trials were also observed. To efficiently determine the efficacy of orthopaedic treatments and limit bias, high-quality randomized trials of appropriate sample size and rigorous design are needed.

Estimation of between-Cow Variability in Nutrient Digestion of Lactating Dairy Cows Fed Corn-Based Diets.

Simple SummaryCow variability present in nutrient digestibility studies differs for different diets and nutrients. It is a major factor determining adequate sample size so that studies are not under-powered or over-powered. The objective of the current study was to develop cow variability estimates that can be used to determine the optimal sample size for digestibility trials having randomized block designs using mid-lactation dairy cows when fed corn-based diets having different neutral detergent fiber:starch ratio (0.7, 1.0, and 1.3). Cow variability is greater for digestibility of fiber and dry matter and less for starch. Estimated cow variability as standard deviations for digestibility of dry matter, neutral detergent fiber and starch were 3.8 g/kg, 5.1 g/kg and 3.3 g/kg, respectively. A major implication of this study is that cow variability is greatest for fiber digestibility and the use of a minimum of 12 cows per dietary treatment is adequate to reliably detect treatment effects on the digestibility of fiber, starch and dry matter using lactating dairy cows fed in groups with randomized block design under current experimental conditions. The objective of this study was to estimate cow variability that can be used to determine the optimal sample size for digestibility trials using lactating dairy cows. Experimental design was randomized complete block design having three blocks and three dietary treatments. Three similarly managed nearby intensive farms were considered as blocks, and three diets were formulated to have 0.7, 1.0, and 1.3 neutral detergent fiber (NDF): starch ratio. In each farm, 18 cows were assigned for each dietary treatment and five sample sizes per each treatment group were simulated by simple random sampling of data from 18, 15, 12, 9 and 6 cows respectively. Intake was not affected by diet or sample size (p > 0.05). Estimated cow variability (as standard deviation) for digestibility of dry matter, NDF and starch were 3.8 g/kg, 5.1 g/kg and 3.3 g/kg, respectively. A major implication of this study is that cow variability is greatest for NDF digestibility and the use of a minimum of 12 cows per dietary treatment is adequate to reliably detect treatment effects on the digestibility of NDF, starch and dry matter using cows fed in groups with randomized block design under these experimental conditions.

Designing historical control studies with survival endpoints using exact statistical inference

Historical control trials compare an experimental treatment with a previously conducted control treatment. By assigning all recruited samples to the experimental arm, historical control trials can better identify promising treatments in early phase trials compared with randomized control trials. Existing designs of historical control trials with survival endpoints are based on asymptotic normal distribution. However, it remains unclear whether the asymptotic distribution of the test statistic is close enough to the true distribution given relatively small sample sizes in early phase trials. In this article, we address this question by introducing an exact design approach for exponentially distributed survival endpoints, and compare it with an asymptotic design in both real examples and simulation examples. Simulation results show that the asymptotic test could lead to bias in the sample size estimation. We conclude the proposed exact design should be used in the design of historical control trials.

Implementation of Mobile Health Technologies in Clinical Trials of Movement Disorders: Underutilized Potential.

Mobile health technologies (mHealth) are patient-worn or portable devices aimed at increasing the granularity and relevance of clinical measurements. The implementation of mHealth has the potential to decrease sample size, duration, and cost of clinical trials. We performed a review of the ClinicalTrials.gov database using a standardized approach to identify adoption in and usefulness of mHealth in movement disorders interventional clinical trials. Trial phase, geographical area, availability of data captured, constructs of interest, and outcome priority were collected. Eligible trials underwent quality appraisal using an ad hoc 5-point checklist to assess mHealth feasibility, acceptability, correlation with patient-centered outcome measures, and clinical meaningfulness. A total of 29% (n = 54/184) registered trials were using mHealth, mainly in Parkinson's disease and essential tremor (59.3% and 27.8%). In most cases, mHealth were used in phase 2 trials (83.3%) as secondary outcome measures (59.3%). Only five phase 3 trials, representing 9.3% of the total, used mHealth (1 as primary outcome measure, 3 as secondary, and 1 as tertiary). Only 3.7% (n = 2/54) of all trials used mHealth for measuring both motor and non-motor symptoms, and 23.1% (n = 12/52) used mHealth for unsupervised, ecologic outcomes. Our findings suggest that mHealth remain underutilized and largely relegated to phase 2 trials for secondary or tertiary outcome measures. Efforts toward greater alignment of mHealth with patient-centered outcomes and development of a universal, common-language platform to synchronize data from one or more devices will assist future efforts toward the integration of mHealth into clinical trials.

Long-Term Outcomes of Epidurals with Lidocaine With or Without Steroids for Lumbar Disc Herniation and Spinal Stenosis: A Meta-Analysis

Previous meta-analyses examined only the short-term differences between lidocaine and steroids vs lidocaine alone in treating lumbar degenerative diseases. Long-term outcomes (1-2 years) in patients with lumbar disc herniation (LDH) and lumbar central spinal stenosis (LCSS) have not yet been systematically evaluated. The objective of our study was to assess quantitatively the difference in efficacy at 1 to 2 years between lidocaine alone vs lidocaine and steroids for the management of LDH or LCSS. We conducted a meta-analysis. PubMed, EMBASE, and the Cochrane library were electronically searched up to July 22, 2016, for randomized controlled trials comparing lidocaine alone vs in combination with steroids for the treatment of LDH and LCSS. Effective pain relief (EPR), Numeric Rating Scale (NRS-11), Oswestry Disability Index (ODI), opioid intake (OI), and total employed increased rate (TEIR) were the endpoints. Risk ratios (RRs) or weighted mean difference (WMD) with 95% confidence intervals (CIs) were calculated, and the pooled analysis was conducted using RevMan 5.2. Seven trials were included. EPR was not significantly different at 1 and 2 years, with RR = 1.08 (95% CI, 0.90-1.30; P = .39) and RR = 1.04 (95% CI, 0.92-1.18; P = .51), respectively, in patients treated with lidocaine alone vs in combination with steroids. The NRS-11 was also similar at 1 and 2 years. ODI and OI were not significantly different at 1 and 2 years. A similar TEIR effect was also observed for the 2 treatments. This meta-analysis relied on a small sample size of trials. Significant heterogeneity among studies was observed. Several significant differences in terms of age of the patients were reported in one included trial. This meta-analysis confirmed the similar effects associated with lidocaine alone vs in combination with steroids for the management of LDH and LCSS. Studies with longer follow-up periods are still recommended. Effective pain relief, lidocaine, long-term, lumbar central spinal stenosis, lumbar disc herniation, Numeric Rating Scale, opioid intake, Oswestry Disability Index, steroids, total employed increased rate.

Registered Interventional Clinical Trials for Old Populations With Infectious Diseases on ClinicalTrials.gov: A Cross-Sectional Study.

BackgroundInterventional clinical trials for infectious diseases in old population have arisen much attention in recent years, however, little is known about the characteristics of registered clinical trials regarding this field. This study aimed to investigate the characteristics of registered interventional trials for infectious diseases in old populations on ClinicalTrials.gov.MethodsA cross-sectional study was performed. We used viral OR bacterial OR fungal OR parasitic OR infectious disease to search the ClinicalTrials.gov database and to assess characteristics of included trials. The age of participants was restricted to more than 65 years old. All analyses were performed using the SPSS19.0 software.ResultsA total of 138 registered trials were included. Among them, 105(76.1%) trials were completed; however, the results were available in ClinicalTrials.gov for only 44(31.9%) trials. North America was the most frequently identified study location (52.9%), followed by Europe (30.4%) and Asia (11.6%). Seventy-one percent trials focused on viral pathogens, followed by bacterial pathogens (22.5%). A total of 84.1% trials were prevention oriented. A total of 84.1% trials used randomization, 73.2% trials used parallel assignment, and 64.5% used masking. Eighty-six trials were industry-funded and 52 were non-industry-funded. Industry-funded trials had higher percentages than non-industry-funded trials in available results, prevention trial, and phase 2 and phase 3 trial, and lager sample size trial. One hundred eleven trials were vaccine trials and 27 trials were non-vaccine trials. Vaccine trials had higher percentages than non-vaccine trials in available results, leading industry sponsor and viral etiology.ConclusionsThe current study is the first study of the landscape of interventional clinical trials for infectious diseases in old populations registered in ClinicalTrials.gov, providing the basis for treatment and prevention of infectious diseases in old populations. Trials in this field are still relatively lacking, and additional and better trials are needed.

Probiotic treatment for women with gestational diabetes to improve maternal and infant health and well-being.

Gestational diabetes mellitus (GDM) is carbohydrate intolerance first recognised during pregnancy and associated with complications for mothers and babies. Probiotics are naturally occurring micro-organisms, which when ingested in adequate amounts, may confer health benefits. Evidence of the role of probiotics as treatment for GDM is limited. To evaluate the safety and effectiveness of probiotics in treating women with GDM on maternal and infant outcomes. We searched the Cochrane Pregnancy and Childbirth's Trials Register ClinicalTrials.gov, WHO International Clinical Trials Registry Platform (ICTRP) (24 July 2019), and reference lists of retrieved studies. Randomised controlled trials (RCTs) comparing the use of probiotics versus placebo/standard care for the treatment of GDM. Two review authors independently assessed study eligibility, extracted data, checked data accuracy, and assessed risk of bias of included trials. The certainty of evidence for selected maternal and infant/child outcomes was assessed using GRADE. Nine RCTs (695 pregnant women with GDM) comparing probiotics versus placebo were identified. The overall risk of bias in the nine RCTs was low to unclear and the evidence was downgraded for imprecision due to the small numbers of women participating in the trials. The trials were carried out in hospitals and universities in Iran (seven trials), Thailand (one trial) and Ireland (one trial). All trials compared probiotics with placebo. Maternal outcomes We are uncertain if probiotics have any effect compared with placebo on hypertensive disorders of pregnancy, (risk ratio (RR) 1.50, 95% confidence interval (CI) 0.64 to 3.53; participants = 256; studies = 3; low-certainty evidence) and mode of birth as caesareans (average RR 0.64, 95% CI 0.30 to 1.35; participants = 267; studies = 3; low-certainty evidence) because the certainty of evidence is low and the 95% CIs span possible benefit and possible harm. No trials reported primary outcomes of: mode of birth as vaginal/assisted and subsequent development of type 2 diabetes. We are uncertain if probiotics have any effect compared with placebo on induction of labour (RR 1.33, 95% CI 0.74 to 2.37; participants = 127; studies = 1; very low-certainty evidence). For other secondary maternal outcomes, we are uncertain if there are differences between probiotics and placebo for: postpartum haemorrhage; weight gain during pregnancy intervention and total gestational weight gain; fasting plasma glucose and need for extra pharmacotherapy (insulin). Probiotics may be associated with a slight reduction in triglycerides and total cholesterol. In probiotics compared with placebo, there was evidence of reduction in markers for insulin resistance (HOMA-IR) and HOMA-B; and insulin secretion. There was also an increase in quantitative insulin sensitivity check index (QUICKI). Probiotics were associated with minor benefits in relevant bio-markers with evidence of a reduction in inflammatory markers high-sensitivity C-reactive protein (hs-CRP), interleukin 6 (IL-6), and marker of oxidative stress malondialdehyde; and an increase in antioxidant total glutathione, but we are uncertain if there is any difference in total antioxidant capacity. No trials reported secondary outcomes: perineal trauma, postnatal weight retention or return to pre-pregnancy weight and postnatal depression. Infant/child/adult outcomes We are uncertain if probiotics have any effect, compared with placebo, on the risk of large-for-gestational-age babies (RR 0.73, 95% CI 0.35 to 1.52; participants = 174; studies = 2; low-certainty evidence) or infant hypoglycaemia (RR 0.85, 95% CI 0.39 to 1.84; participants = 177; studies = 3; low-certainty evidence) because the certainty of evidence is low and the 95% CIs span possible benefit and possible harm. No trials reported primary outcomes of: perinatal (fetal/neonatal) mortality; or neurosensory disability. For other secondary outcomes, we are uncertain if there is any difference between probiotics and placebo in gestational age at birth, preterm birth, macrosomia, birthweight, head circumference, length, infant hypoglycaemia, and neonatal intensive care unit (NICU) admissions. There was evidence of a reduction in infant hyperbilirubinaemia with probiotics compared with placebo. No trials reported secondary outcomes: infant adiposity, and later childhood adiposity. There were no adverse events reported by any of the trials. Low-certainty evidence means we are not certain if there is any difference between probiotic and placebo groups in maternal hypertensive disorders of pregnancy, caesareans; and large-for-gestational-age babies. There were no adverse events reported by the trials. Due to the variability of probiotics used and small sample sizes of trials, evidence from this review has limited ability to inform practice. Well-designed adequately-powered trials are needed to identify whether probiotics may improve maternal blood glucose levels and/or infant/child/adult outcomes; and whether they can be used to treat GDM.

A randomised feasibility study of serial magnetic resonance imaging to reduce treatment times in Charcot neuroarthropathy in people with diabetes (CADOM): a protocol

BackgroundCharcot neuroarthropathy is a complication of peripheral neuropathy associated with diabetes which most frequently affects the lower limb. It can cause fractures and dislocations within the foot, which may progress to deformity and ulceration. Recommended treatment is immobilisation and offloading, with a below knee non-removable cast or boot. Duration of treatment varies from six months to more than 1 year. Small observational studies suggest that repeated assessment with magnetic resonance imaging improves decision-making about when to stop treatment, but this has not been tested in clinical trials. This study aims to explore the feasibility of using serial magnetic resonance imaging without contrast in the monitoring of Charcot neuroarthropathy to reduce duration of immobilisation of the foot. A nested qualitative study aims to explore participants’ lived experience of Charcot neuroarthropathy and of taking part in the feasibility study.MethodsWe will undertake a two-arm, open study and randomise 60 people with a suspected or confirmed diagnosis of Charcot neuroarthropathy from five NHS, secondary care multidisciplinary Diabetic Foot Clinics across England. Participants will be randomised 1:1 to receive magnetic resonance imaging at baseline and remission up to 12 months, with repeated foot temperature measurements and X-rays (standard care plus), or standard care plus with additional three-monthly magnetic resonance imaging until remission up to 12 months (intervention). Time to confirmed remission of Charcot neuroarthropathy with off-loading treatment (days) and its variance will be used to inform sample size in a full-scale trial. We will look for opportunities to improve the protocols for monitoring techniques and the clinical, patient-centred and health economic measures used in a future study. For the nested qualitative study, we will invite a purposive sample of 10–14 people able to offer maximally varying experiences from the feasibility study to take part in semi-structured interviews to be analysed using thematic analysis.DiscussionThe study will inform the decision whether to proceed to a full-scale trial. It will also allow deeper understanding of the lived experience of Charcot neuroarthropathy, and factors that contribute to engagement in management and contribute to the development of more effective patient-centred strategies.Trial registrationISRCTN, ISRCTN74101606. Registered on 6 November 2017.

Sample Size Calculation for “Gold-Standard” Noninferiority Trials With Fixed Margins and Negative Binomial Endpoints

For clinical trials in patients with asthma, chronic obstructive pulmonary disease, and relapsing-remitting multiple sclerosis, regulatory guidelines state that a noninferiority clinical trial is an option. Aiming at establishing assay sensitivity, a three-arm noninferiority trial, including an experimental treatment, a reference treatment, and a placebo, the so-called gold-standard noninferiority trial, is recommended. In addition, in the clinical trials for the above diseases, the number of events per unit time is often used as a primary or key secondary endpoint. There are two issues to be addressed in determining the sample size for gold-standard noninferiority trials: the hypotheses to be tested for assay sensitivity, and overdispersion of the number of events. To address these two issues, we propose a sample size calculation method for gold-standard noninferiority trials with two fixed margins and negative binomial endpoints. In a simulation, we show that the proposed hypothesis-testing method achieves the target power, while controlling the Type I error rate at a nominal level, and that the sample size calculation method has adequate power accuracy. Moreover, we illustrate an application of our proposed method for a clinical trial of mild asthma.

Meta-analysis on the efficacy and safety of immunoadsorption for systemic lupus erythematosus among Chinese population.

To systematically evaluate the efficacy and safety of immunoadsorption (IAS) versus non-IAS for systemic lupus erythematosus (SLE) among Chinese population. A meta-analysis was performed by all the literatures germane to estimate the SLE patients treated with IAS and non-IAS from published randomized controlled trials (RCTs) from 1990 to February 2020. Mean differences (MDs), relative ratios (RRs), and 95% confidence intervals (CIs) were calculated, and the meta-analysis was conducted with Stata 12.0 software. A total of 18 RCTs involving 457 patients were included. The results of meta-analysis demonstrated that the IgG, Scr, Bun, ANA, 24-h urine protein, leptin, and TNF-α of IAS combined with a drug therapy group were lower than that of non-IAS, and the levels of C3 and C4 were higher than that of non-IAS after treatment in terms of laboratory parameters. In terms of adverse reactions, the incidence of fever or chills, low blood pressure, or bleeding risk was higher in the treatment group. However, there was no difference in the incidence of puncture point bleeding, thrombocytopenia, mild rash, death due to severe infection, tightness, palpitation, or chest tightness between the two groups. However, most of the adverse effects could be considered as tolerable after timely treatment. Our results indicate that IAS may be superior to non-IAS in treating SLE patients. However, due to the lower quality of included studies, high quality of multicenter, large sample size, randomized, and double-blind controlled trials are needed to validate the results.

Fragility index of trials supporting approval of anti-cancer drugs in common solid tumors.

2055 Background: The Fragility Index (FI) quantifies the reliability of positive trials by estimating the number of events which would change statistically significant results to non-significant results. Here, we calculate the FI of trials supporting approval of drugs for common solid tumors. Methods: We searched Drugs@FDA to identify randomized trials (RCT) supporting drug approvals by the US Food and Drug Administration between January 2009 and December 2019 in lung, breast, prostate, gastric and colon cancers. We adapted the FI framework (Walsh et al. J Clin Epidemiol 2014) to allow use of time to event data. First, we reconstructed survival tables from reported data using the Parmar Toolkit (Parmar et al. Stat Med 1998) and then calculated the number of events which would result in a non-significant effect for the primary endpoint of each trial. The FI was then compared quantitatively to the number of patients in each trial who withdrew consent or were lost to follow-up. Multivariable linear regression was used to explore association between RCT characteristics and the FI. Results: We identified 69 RCT with a median of 669 patients (range 123-4804) and 358 primary outcome events (range 56-884). The median FI was 26 (range 1-322). The FI was ≤10 in 21 trials (30%) and ≤20 in 31 trials (45%). Among the 69 RCT, the median number of patients who withdrew consent or were lost to follow up was 27 (range, 6-317). The number of patients who withdrew consent or were lost to follow-up was equal or greater than the FI in 42 trials (61%). There was statistically significant inverse association between FI and trial hazard ratio (p0,001) and a positive association with number of patients who were lost to follow-up or withdrew consent (p0,001). There was no association between trial sample size, year of approval or reported p-value and the FI. Conclusions: Statistical significance of trials supporting drug approval in common solid tumors relies often on a small number of events. In most trials the FI was lower than the number of patients lost to follow up or withdrawing consent. Post-approval randomized trials or real-world data analyses should be performed to ensure that effects observed in registration trials are robust.

Implications of a prognostic 40-gene expression profile (40-GEP) test for high-risk cutaneous squamous cell carcinoma (cSCC) on staging-based risk assessment and adjuvant therapy trial design.

e22091 Background: Deaths due to cSCC are expected to exceed melanoma-specific deaths. With the demonstration of effective therapies for advanced cSCC, and as treatment of patients in the adjuvant setting is considered, accurate prognosis is critical. For improved identification of ‘high-risk’ patients, with biologically aggressive disease capable of metastasis, a prognostic 40-gene expression profile (40-GEP) test was validated using an independent cohort of patients with high-risk cSCC and known clinical outcomes. The test identified three groups with increasing metastasis risk profiles: Class 1 (low risk), Class 2A (high risk), and Class 2B (highest risk) having metastasis rates of 8.9%, 20.4%, and 60%, respectively. Multivariable analysis demonstrated prognostic efficacy of the 40-GEP test alone and in combination with clinicopathological staging systems. This study evaluated risk stratification with concurrent consideration of the 40-GEP result and the Brigham and Women’s Hospital (BWH) stage. The primary objective was evaluation of the potential impact of the 40-GEP on adjuvant clinical trial design. Methods: To determine if a 40-GEP Class 2B result could optimize clinical trial accrual, metastasis rates of BWH high-risk T stage patients (T2b-T3) alone and in combination with 40-GEP results from the validation cohort were used for two-arm trial sample size calculations. Results: Metastasis rates for cases with T2b-T3 tumors increased from 35.1% to 71.4% when selecting for T2b-T3 cases with a 40-GEP Class 2B result. To provide 80% power to detect hazard ratio of 0.6 with 3 years of follow-up (alpha = 0.05), in line with improvement rates by addition of radiation to surgery, 434 T2b-T3 patients are required for randomization. However, sample size could be reduced by 51% to 214 patients by focusing enrollment on T2b-T3 patients with a 40-GEP Class 2B result. Conclusions: These results support the incorporation of the 40-GEP test into selection processes for patients with T2b-T3 tumors who are at the highest risk for metastasis and appropriate for adjuvant clinical trials.

Assessing the relationship in relapsed-refractory multiple myeloma between response, progression, and survival between pooled clinical trial subjects and a real-world electronic medical record data source.

e20525 Background: Despite new treatments, Relapsed-Refractory Multiple Myeloma (RRMM) remains an incurable disease1. In a recent study by Moreau et al, there was a demonstrated survival benefit to treatment with pomalidomide in RRMM patients2. To better understand how the relationships between initial depth of response and long-term prognosis can inform clinical decision making and guide new compound development, we performed an analysis of standardized clinical trial patient pool data compared with Real-World Data (RWD), across multiple studies. Methods: Pooled clinical trial data was obtained from a Study Data Tabulation Model (SDTM) dataset (n=1,815) from the Medidata Enterprise Data Store. De-identified Oncology EMR data was sourced from the Guardian Research Network™ (GRN)5 of integrated delivery systems from 2010-2018, with robust clinical endpoint extraction and curation to enable outcomes comparisons (n=962). Subject selection was refined based on the inclusion/exclusion criteria from the NIMBUS trial2. Response, Progression-free survival (PFS), and Overall Survival (OS) were extracted. Patients were stratified by age, gender, and prior regimens. Log-rank tests were conducted to compare PFS and OS in patient sub-populations at 90, 180, and 240 days from most recent treatment start. Cox proportional hazard models assessed predictors of survival. Rates were estimated for common adverse events, including leukopenia, neutropenia, and thrombocytopenia. Factors associated with neutropenia were assessed using logistic regression. Results: Within pooled trial and RWD patients, the majority were on regimens with proteasome inhibitors, followed by immunomodulators, and approximately one third on monoclonal antibodies. Within the pooled trial analysis, survival rates were consistent with published literature rates, at ~4 months and ~12 months, respectively. EMR data analysis showed overall longer times to progression with an increased depth of response, with similar associations. Frequency-Factored Time-to-Progression also decreased. Conclusions: The use of SDTM for pooled clinical trial analyses, together with real-world data, can overcome individual trial sample size limitations and biases. Together this approach can expand the range of populations, relative treatment comparisons, and clinical events that can be studied to more comprehensively understand the complexity of the oncology treatment landscape.

Bayesian Adaptive Clinical Trials for Anti-Infective Therapeutics During Epidemic Outbreaks

In the midst of epidemics such as COVID-19, therapeutic candidates are unlikely to be able to complete the usual multiyear clinical trial and regulatory approval process within the course of an outbreak. We apply a Bayesian adaptive patient-centered model—which minimizes the expected harm of false positives and false negatives—to optimize the clinical trial development path during such outbreaks. When the epidemic is more infectious and fatal, the Bayesian-optimal sample size in the clinical trial is lower and the optimal statistical significance level is higher. For COVID-19 (assuming a static R_{0} = 2 and initial infection percentage of 0.1%), the optimal significance level is 7.1% for a clinical trial of a nonvaccine anti-infective therapeutic and 13.6% for that of a vaccine. For a dynamic R_{0} decreasing from 3 to 1.5, the corresponding values are 14.4% and 26.4%, respectively. Our results illustrate the importance of adapting the clinical trial design and the regulatory approval process to the specific parameters and stage of the epidemic.

The Sensory Abnormalities and Neuropsychopathology of Autism and Anxiety.

Autism spectrum disorder (ASD) is a developmental disorder of interpersonal communications and restricted interest and deficits in sensory and social interactions. It co-occurs with anxiety and mostly in 30% of cases related to specific phobia. This review article summarises the sensory association between anxiety and ASD. The role of emotions and neurobiology discussed and sensory over-reactivity (SOR) was related to ASD and anxiety. PubMed database systematically searched for related articles on ASD and anxiety. The keywords used are autism spectrum disorder, autism spectrum disorder and emotion, anxiety disorder, sensory in autism and anxiety, and psychopathology. The results were most significant and related to the sensory association between ASD and anxiety. Out of 19 studies discussed, there were eight systematic reviews with meta-analysis, seven systematic reviews, three traditional reviews, and one included both systematic reviews with randomized controlled trials (RCTs). However, due to possible limitations and considerations, like small sample size and few clinical trials; hence, further recommendations to randomized clinical trials and cohort studies warranted. This review article helps scientists to plan and focus on necessary studies and possible screening for the disease to improve possible clinical outcomes. People gain awareness of the disease. Early recognition, as well as educational, behavioral, and family therapy, might decrease symptoms and support learning and development in children.

Minimal clinically important differences in average, best, worst and current intensity and unpleasantness of chronic breathlessness.

Chronic breathlessness has devastating consequences. The minimal clinically important difference (MCID) for current intensity has been estimated as 9 mm on a 100-mm visual analogue scale (VAS). We aimed to determine MCIDs for commonly used dimensions and recall periods: the current unpleasantness and current, average, best and worst intensity of the past 24 h for chronic breathlessness. This was a secondary analysis of a randomised controlled trial of morphine versus placebo over 7 days in people with chronic breathlessness from severe disease. The breathlessness scores were self-reported using a diary each evening on 100-mm VAS. The MCID for improvement in each score was estimated using anchor-based and distribution-based methods. 283 participants (mean age 74.2 years; 63% male; 58% COPD; 87.0% modified Medical Research Council (mMRC) score 3-4) were included. Anchor-based MCIDs for breathlessness scores ranged from -13.9 mm to -9.5 mm. The MCIDs were similar when using different anchors and across all participants, and participants with more severe breathlessness (mMRC 3-4). Distribution-based effect sizes were classed as small (-4.7-6.3 mm), moderate (-9.4-12.5 mm) and large (-15.0-20.0 mm) effect. Sample sizes for trials using the different scores were proposed. MCIDs of absolute change were more stable than using relative change from baseline. An improvement of ∼10 mm on a 100-mm VAS is likely to be clinically meaningful across commonly used measures of chronic breathlessness (current intensity, unpleasantness, and average, best and worst intensity over the past 24 h) to evaluate clinical benefit and effects in therapeutic 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;

Research Techniques Made Simple: Randomized Controlled Trials for Topical Drugs in Dermatology: When and How Should We Use a Within-Person Design?

Topical drugs are often used as first-line treatment for dermatological conditions. Depending on the disease and the drug, three main designs can be used for randomized controlled trials assessing topical drugs: the classical individual parallel design, the cluster randomized design, and designs allowing within-individual comparisons, including the cross-over design (in which patients are randomized to a sequence of interventions) and the within-person design (also called the split-body design). Within-person design can be used to compare different drugs concomitantly in the same patient. Randomization does not concern patients but rather lesions or body sites within patients, and the drugs to be compared are applied to the different lesions (or sites). This design considerably reduces interobservation variability, and thus, the number of patients to be included in the trial (sample size). However, this design has major methodological constraints, especially the need to resolve the problem of a possible carry-across effect. First, we describe the specificities of randomized controlled trials evaluating a topical drug. Second, we present the different designs available and discuss the methodological points that should be considered, especially for a within-person design. Finally, we compare the relevance of the within-person design with that of other trial designs by considering three different scenarios.

Effects of simulated sample sizes on the mortality effect estimates in three randomized intensive care unit trials.

Randomized clinical trials (RCTs) are occasionally stopped prematurely before reaching their planned sample sizes. It has been suggested that early stopped RCTs are associated with under- and overestimation of the effect estimates. We simulated the effect of hypothetical premature stopping of three large RCTs done in the intensive care unit (ICU) setting. In this post hoc study, we simulated the impact of stopping trials early by calculating mortality effect estimates continuously after the inclusion of each individual patient in three large RCTs, that is the 6S trial on hydroxyethyl starch vs Ringer's acetate in sepsis in ICU, the TRISS trial on lower vs higher haemoglobin threshold for transfusion in septic shock in ICU and the SUP-ICU trial on pantoprazole in patients at risk for gastrointestinal bleeding in the ICU. The three trials included a total of 5087 patients; 798 from the 6S trial, 998 from the TRISS trial and 3291 patients from the SUP-ICU trial. The premature mortality effect estimates showed considerable fluctuations until at least 20%-30% of the sample size was included. The premature estimates became stable after inclusion of 205 patients (26% of the final sample size) in the 6S trial, 133 patients(13%) in the TRISS trial and 1926 patients(59%) in the SUP-ICU trial. In this post hoc study of three international RCTs within intensive care, we found that the simulated interim mortality effect estimates showed considerable fluctuations until at least 20%-30% of the sample size was included, but remained instable until the final sample sizes had been included. Thus, this study illustrates the necessity for cautious interpretations of prematurely stopped trials.

Modelling the patient accrual with truncated Gaussian mixture distribution for the accurate estimation of sample size in survival trials.

In survival trials with fixed trial length, the patient accrual rate has a significant impact on the sample size estimation or equivalently, on the power of trials. A larger sample size is required for the staggered patient entry. During enrollment, the patient accrual rate changes with the recruitment publicity effect, disease incidence and many other factors and fluctuations of the accrual rate occur frequently. However, the existing accrual models are either over-simplified for the constant rate assumption or complicated in calculation for the subdivision of the accrual period. A more flexible accrual model is required to represent the fluctuant patient accrual rate for accurate sample size estimation. In this paper, inspired by the flexibility of the Gaussian mixture distribution in approximating continuous densities, we propose the truncated Gaussian mixture distribution accrual model to represent different variations of accrual rate by different parameter configurations. The sample size calculation formula and the parameter setting of the proposed accrual model are discussed further.