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Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

ObjectiveThe objective of this review is to provide an overview of the justification reported for using unequal allocation ratios in randomized clinical trials (RCTs) testing a medical intervention.MethodsUsing the PICOS framework, we conducted a systematic search to find meta-studies within PubMed (a Medline database interface) that addressed the objective.ResultsThe developed search strategy generated 525 results, of which, three studies met criteria for inclusion. These studies found that 22-43% of RCTs provided a justification for the use of unequal allocation based on publication alone, and between 38.7 and 66% after seeking input from trial authors. The most common reason given for this design was to gather increased safety data according to two reviews and to gain experience with an intervention according to the third review.ConclusionReporting of justification for RCTs designed with unequal allocation appears to occur less than half the time in the included studies. The reasons given for designing clinical trials with unequal participants encompass many domains, including ethical considerations. As such, this design feature should be implemented with intentionality to maximize the ethical features of clinical trials for participants. Coupling lack of justification with lack of adjusting for sample size estimations depicts an overall landscape in which there is significant room for improvement in methodological transparency within this area of RCTs.

Pharmacokinetic (PK) studies in children are usually small and have ethical constraints due to the medical complexities of drawing blood in this special population. Often, population PK models for the drug(s) of interest are available in adults, and these models can be extended to incorporate the expected deviations seen in children. As a consequence, there is increasing interest in the use of optimal design methodology to design PK sampling schemes in children that maximize information using a small sample size and limited number of sampling times per dosing period. As a case study, we use the novel tuberculosis drug delamanid, and show how applications of optimal design methodology can result in highly efficient and model-robust designs in children for estimating PK parameters using a limited number of sampling measurements. Using developed population PK models based on available data from adults living with and without HIV, and limited data on children without HIV, competing designs for children living with HIV were derived and assessed based on robustness to model uncertainty.

Interest in incorporating historical data in the clinical trial has increased with the rising cost of conducting clinical trials. The intervention arm for the current trial often requires prospective data to assess a novel treatment, and thus borrowing historical control data commensurate in distribution to current control data is motivated in order to increase the allocation ratio to the current intervention arm. Existing historical control borrowing adaptive designs adjust allocation ratios based on the commensurability assessed through study-level summary statistics of the response agnostic of the distributions of the trial subject characteristics in the current and historical trials. This can lead to distributional imbalance of the current trial subject characteristics across the treatment arms as well as between current control data and borrowed historical control data. Such covariate imbalance may threaten the internal validity of the current trial by introducing confounding factors that affect study endpoints. In this article, we propose a Bayesian design which borrows and updates the treatment allocation ratios both covariate-adaptively and commensurate to covariate dependently assessed similarity between the current and historical control data. We employ covariate-dependent discrepancy parameters which are allowed to grow with the sample size and propose a regularized local regression procedure for the estimation of the parameters. The proposed design also permits the current and the historical controls to be similar to varying degree, depending on the subject level characteristics. We evaluate the proposed design extensively under the settings derived from two placebo-controlled randomized trials on vertebral fracture risk in post-menopausal women.

Large-scale data obtained from aggregation of already collected multi-site neuroimaging datasets has brought benefits such as higher statistical power, reliability, and robustness to the studies. Despite these promises from growth in sample size, substantial technical variability stemming from differences in scanner specifications exists in the aggregated data and could inadvertently bias any downstream analyses on it. Such a challenge calls for data normalization and/or harmonization frameworks, in addition to comprehensive criteria to estimate the scanner-related variability and evaluate the harmonization frameworks. In this study, we propose MISPEL (Multi-scanner Image harmonization via Structure Preserving Embedding Learning), a supervised multi-scanner harmonization method that is naturally extendable to more than two scanners. We also designed a set of criteria to investigate the scanner-related technical variability and evaluate the harmonization techniques. As an essential requirement of our criteria, we introduced a multi-scanner matched dataset of 3T T1 images across four scanners, which, to the best of our knowledge is one of the few datasets of this kind. We also investigated our evaluations using two popular segmentation frameworks: FSL and segmentation in statistical parametric mapping (SPM). Lastly, we compared MISPEL to popular methods of normalization and harmonization, namely White Stripe, RAVEL, and CALAMITI. MISPEL outperformed these methods and is promising for many other neuroimaging modalities.

We conducted a meta-analysis using individual participant data from three, two-dose psilocybin trials for depression (N = 102) with the aim of assessing the risk of symptom worsening. Clinically significant symptom worsening occurred for a minority of participants in the psilocybin and escitalopram conditions (∼10%) and for a majority of participants in the waitlist condition (63.6%). Using data from the two trials with control arms, the psilocybin arm showed a lower likelihood of symptom worsening versus waitlist, and no difference in the likelihood of symptom worsening versus escitalopram. The limitation of a relatively small sample size should be addressed in future studies.

Across research disciplines, cluster randomized trials (CRTs) are commonly implemented to evaluate interventions delivered to groups of participants, such as communities and clinics. Despite advances in the design and analysis of CRTs, several challenges remain. First, there are many possible ways to specify the causal effect of interest (eg, at the individual-level or at the cluster-level). Second, the theoretical and practical performance of common methods for CRT analysis remain poorly understood. Here, we present a general framework to formally define an array of causal effects in terms of summary measures of counterfactual outcomes. Next, we provide a comprehensive overview of CRT estimators, including the t-test, generalized estimating equations (GEE), augmented-GEE, and targeted maximum likelihood estimation (TMLE). Using finite sample simulations, we illustrate the practical performance of these estimators for different causal effects and when, as commonly occurs, there are limited numbers of clusters of different sizes. Finally, our application to data from the Preterm Birth Initiative (PTBi) study demonstrates the real-world impact of varying cluster sizes and targeting effects at the cluster-level or at the individual-level. Specifically, the relative effect of the PTBi intervention was 0.81 at the cluster-level, corresponding to a 19% reduction in outcome incidence, and was 0.66 at the individual-level, corresponding to a 34% reduction in outcome risk. Given its flexibility to estimate a variety of user-specified effects and ability to adaptively adjust for covariates for precision gains while maintaining Type-I error control, we conclude TMLE is a promising tool for CRT analysis.

Micro-randomized trials (MRTs) are a novel experimental design for developing mobile health interventions. Participants are repeatedly randomized in an MRT, resulting in longitudinal data with time-varying treatments. Causal excursion effects are the main quantities of interest in MRT primary and secondary analyses. We consider MRTs where the proximal outcome is binary and the randomization probability is constant or time-varying but not data-dependent. We develop a sample size formula for detecting a nonzero marginal excursion effect. We prove that the formula guarantees power under a set of working assumptions. We demonstrate via simulation that violations of certain working assumptions do not affect the power, and for those that do, we point out the direction in which the power changes. We then propose practical guidelines for using the sample size formula. As an illustration, the formula is used to size an MRT on interventions for excessive drinking. The sample size calculator is implemented in R package MRTSampleSizeBinary and an interactive R Shiny app. This work can be used in trial planning for a wide range of MRTs with binary proximal outcomes.

Trial design Randomised, multicentre, double-blind crossover trial (with 2 × 16-week periods) of active neurostimulation versus sham stimulation with subsequent open-label follow-up to 58 weeks. Embedded mechanistic sub-study using magnetoencephalography to study bidirectional functional connectivity between brain and anorectum. Methods Participants: adults aged 18–80 years, with chronic symptoms of faecal incontinence refractory to first-line treatments (and meeting national criteria for sacral neuromodulation). Interventions: active: chronic, subsensory (low amplitude) stimulation of a mixed sacral nerve (usually S3) using a commercially available surgically implanted pulse generator; sham: identical implant but turned off (or to 0.05 V). Patient-chosen sub- or supra-sensory open-label stimulation from week 32 to week 58. Primary objectives: (1) to determine whether sub-sensory sacral neuromodulation led to a reduction in total faecal incontinence episodes per week compared to sham stimulation; (2) to identify whether clinical responses to sub-sensory sacral neuromodulation were biologically related to changes in evoked and induced activity between the brain and anorectum. Primary outcome: total faecal incontinence episodes per week based on paper bowel diary performed in the final 4 weeks of each crossover period (allowing 12-week washout). Randomised allocation (1 : 1) to arm 1 (sacral neuromodulation/sham) or arm 2 (sham/sacral neuromodulation) at time of surgery was stratified by sex and centre. Blinding: participants, surgeons and assessors; tamper-proof tape masked stimulation settings. Statistical methods: Poisson regression models failed to converge for the count outcomes, hence paired t-tests were used, and treatment effects summarised by mean differences [with 95% confidence intervals (CIs)]. Sample size: a total of 90 patients (45 per group) were required to detect a 30% reduction in episodes, allowing for 10% loss to follow-up (alpha = 0.05; power 90%). Results Recruitment: a total of 39 patients of 220 screened and 65 pre-enrolled (arm 1: N = 17; arm 2: N = 22) were recruited to the crossover trial at nine sites from the United Kingdom and one site from Ireland between February 2018 and July 2022, of whom only 16 (arm 1: N = 9; arm 2: N = 7) had complete primary outcome data. Nineteen completed follow-up to 58 weeks. Trial delivery was severely affected and terminated early due to COVID-19. Main barriers were the inability to continue face-to-face patient visits, redeployment of research staff to COVID-19 facing clinical roles and cancelling of sacral neuromodulation procedures due to lack of priority for non-urgent surgery. A total of 25 patients underwent magnetoencephalography studies compared to 20 healthy volunteers. Primary outcome (N = 16): sacral neuromodulation conferred a non-significant reduction in mean faecal incontinence episodes per week compared to sham (−0.7, 95% CI −1.5 to 0.0; p = 0.06). Secondary outcomes: in participants who also used the e-event recorder to record the number of faecal incontinence episodes in both periods (n = 7), estimate of effect size was greater but less precise (−1.5, −3.5 to +0.5; p = 0.12). Data suggested successful allocation concealment. Improvements were observed in faecal incontinence symptoms in the follow-up cohort (at 58 weeks) compared to baseline (approx. 3 fewer faecal incontinence episodes per week). A small number of expected adverse events all resolved. Magnetoencephalography studies demonstrated bidirectional afferent evoked cortical and efferent induced anal activity that did not vary greatly from control subjects (n = 20) and appeared unchanged by sacral neuromodulation. Conclusions Due to under-recruitment it is important to interpret the findings on the experimental efficacy of sacral neuromodulation as exploratory. Effects on symptoms observed during double-blinded crossover point to some efficacy over sham, though not large in comparison with placebo responses. The magnitude of effect was highly dependent on method and interpretation of event recording. Study registration Current Controlled Trials ISRCTN98760715. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Efficacy and Mechanism Evaluation (EME) programme (NIHR award ref: 14/144/08) and is published in full in Efficacy and Mechanism Evaluation; Vol. 11, No. 19. See the NIHR Funding and Awards website for further award information. Plain language summary A treatment called sacral neuromodulation is commonly offered to adults experiencing bowel (faecal) incontinence. A battery powered unit is implanted into the lower back in the region of the sacrum (tailbone). This is connected to a specially developed lead with electrodes that rest on the nerves of the lower spine. This stimulator then continuously sends electrical impulses to the nerves and muscles that control the lower bowel (rectum and anus). The aim is to improve bowel control. Previous studies have reported a great benefit of sacral neuromodulation in some patients, but others have little or no response. The SUBsensory Sacral Neuromodulation for InContinence trial recruited 39 patients (of 90 intended) who met the current national criteria for sacral neuromodulation. It compared the effect on numbers of weekly faecal incontinence episodes with the device either on (active) or off (sham) using a special study design called a randomised crossover trial. All participants had the device on and off for 16 weeks in random order (crossing over in the middle). Using stimulation below the level that can be felt (subsensory), both the patients and the research team were unaware of whether the stimulator was on or off (called double blinding). Due to COVID-19, only 16 patients had complete data for analysis, which was much less than the intended number of 90. The results showed that patients experienced reductions in faecal incontinence episodes during both on and off periods (i.e. there was a strong placebo effect). However, slightly greater effects were seen during the on period suggesting a possible genuine biological effect of sacral neuromodulation. The study also showed that the way we record symptoms during research trials for example with paper bowel diaries needs improvement, as the bowel diaries were not fully completed by some participants. Although this is the first double-blind trial of its kind for sacral neuromodulation, all conclusions must bear in mind the poor recruitment and retention of patients. Scientific summary Background Faecal incontinence (FI), defined as the recurrent involuntary loss of faecal material leading to a social or hygienic problem, is a common and debilitating condition with profound effects on quality-of-life and high societal costs. Initial treatments including pharmacological and behavioural therapies (e.g. biofeedback) have variable outcomes and are poorly evidenced. Traditional surgical approaches focusing on anal sphincter reconstruction or augmentation are invasive, irreversible, and risk significant morbidity. A stoma is the final option. Chronic low-amplitude stimulation of the mixed sacral spinal nerves using an implanted electrode and pulse generator – sacral neuromodulation (SNM) is a less invasive alternative, now considered the first-line surgical treatment option for adults with FI in whom non-operative therapies have failed to alleviate symptoms. Current evidence for SNM is based on extensive observational data and few randomised trials that are heterogeneous in design and outcomes. Despite having widespread regulatory approval, SNM remains an expensive intervention with need for greater confidence in efficacy. A further concern regarding SNM therapy is the lack of evidence and understanding of the mechanism of any effect. Objectives Our primary aim was to determine the clinical efficacy of sub-sensory chronic low voltage electrical SNM using a commercially-available implantable device in adults with FI in whom conservative treatment has failed. We sought to determine whether SNM, compared to sham, led to a clinically important reduction in weekly FI episodes. The study also included mechanistic studies to examine whether clinical responses to sub-sensory SNM were biologically related to changes in the central pathway between the brain and anorectum. Methods Trial design SUBsensory Sacral Neuromodulation for InContinence (SUBSoNIC) was a multicentre, randomised double-blind crossover trial at nine UK sites and one site in Ireland in which SNM was compared to sham stimulation. We aimed to randomise 90 eligible participants (adults aged 18–80 years, where non-surgical approaches to National Institute for Health and Care Excellence (NICE) standard have failed and meeting minimum FI severity criterion) to two study arms after SNM implantation. Both arms had two intervention periods (ON-OFF or OFF-ON) of 16-week duration (T0–T16 and T16–T32). Efficacy outcomes were derived from assessments in the final 4 weeks of each cross-over period (T12–T16 and T28–T32) thus allowing for almost 3 months intervention before outcome assessments (and adequate washout for participants in the ON–OFF sequence). Mechanistic studies were performed in the final 2 weeks of the 4-week assessment periods in a subgroup of consecutively consenting participants from both arms until data saturation. After completing the crossover phase of the study, participants were followed up for a further 26 weeks. During this time, participants had either sub- or supra-sensory ‘open label’ stimulation based on preference as would have been normal for routine clinical practice. Further efficacy outcomes were recorded at T54–T58 to provide an indication of the short-term effectiveness of SNM within the rigor of a clinical trial unit (CTU)-monitored prospective study. Interventions Chronic low voltage stimulation of the third or fourth sacral root was achieved by surgical implantation of a commercially available Conformité Européenne-marked active implantable (class III) medical device [Medtronic InterStimTM (Medtronic, Minneapolis, MN, USA)] used in accord with the manufacturer’s instructions and local practice. For the active intervention (ON), the clinical team programmed the device using standard settings of a 14-Hz frequency and 210-µs pulse width. Optimal electrode configuration was determined by cumulatively increasing the amplitude of stimulation by 0.1 V from zero for each electrode until the sensory threshold was reached. The amplitude and site of stimulation were recorded for each electrode with the electrode configuration that achieved sensation in the anus or perineum at lowest amplitude being chosen for chronic stimulation. Sub-sensory chronic stimulation was initiated by reducing the amplitude to a level just below the habituated sensory threshold (for blinding). For the sham intervention (OFF), sensory thresholds were recorded identically; however, the level was then adjusted to zero volts or 0.05 V (the latter was required in some participants due to the new device handset limitations). Mechanistic studies were undertaken at the Institute of Health and Neurodevelopment (IHN) at Aston University in a subgroup of patients identified in the Midlands region (compared to 20 healthy volunteers without FI). A protocol including spatial registration (magnetic resonance imaging head) and a series of magnetoencephalographic (MEG) acquisitions measured induced and evoked cortical activity relevant to determining functional connectivity between the anus and brain (using anal electrical stimulation) and brain and anorectum (using volitional anal squeeze). Control paradigms (tibial nerve stimulation and fist clench) were used respectively. Outcomes The primary clinical outcome was reduction in FI events per week (recorded on paper bowel diaries over a 4-week period) in SNM versus sham phase of crossover (16 and 32 weeks). Secondary clinical outcomes including other bowel diary measures, e-event recording and a panel of summative questionnaires were recorded at 16, 32 and 58 weeks. Mechanistic outcomes included spatial localisation, relative cortical source signal strength and latencies of evoked and induced responses. Allocation and blinding Randomised allocation (1 : 1) to group 1 (SNM/sham) or group 2 (sham/SNM) was performed at the time of surgery using an online randomisation system managed by the Pragmatic Clinical Trials Unit at QMUL, with a randomisation list generated by an independent statistician to ensure allocation concealment. Randomisation was stratified by sex and centre with block sizes of four. Members of the research team, statisticians, surgeons who performed the surgical procedure, and participants were blinded to intervention status (SNM or sham). Participants were informed of the allocation ratio of 1 : 1 and that blinding prevented them from knowing in which group they were participating. Tamper-proof tape was used to mask stimulation settings. Sample size and statistics The study was designed to detect a mean 30% reduction between SNM and sham stimulation in FI event rate (ratio 0.7). At 90% power and 5% significance level with a cross-over design this required 90 participants (45 per group), allowing for 10% loss to follow-up. The pre-specified analysis for the primary outcome involved a mixed Poisson regression applied to the counts of FI events, with fixed effects of cross-over period and stratification factors, a random effect of individual, and a random effect of period within individual (the latter to allow for an over-dispersed Poisson distribution). When it came to the analysis, owing in part to the small numbers, the Poisson regression models did not converge for the count outcomes. Instead we applied a paired t-test to the FI rates in order to estimate the difference between SNM and sham with a 95% confidence interval and p-value. Results Clinical results The COVID-19 pandemic had a major effect on trial recruitment and patient retention. The trial was terminated on 24 July 2022 with just 39 patients randomised. Trial delivery was severely affected and terminated early due to COVID-19. Main barriers were the inability to continue face-to-face patient visits, redeployment of research staff to COVID-19 facing clinical roles and cancelling of SNM procedures due to lack of priority for non-urgent surgery. In total, 220 patients were screened for eligibility at nine sites from the UK and one site from Ireland between February 2018 and July 2022. Of these, 155 patients declined study participation or were ineligible due to study specific exclusion criteria. A total of 65 patients were pre-enrolled and consented to the study, of whom 26 did not meet the baseline minimum frequency criteria of FI episodes per week or did not receive an implant. The remaining 39 patients were randomised (arm 1: N = 17; arm 2: N = 22); however, only 16 completed the primary outcome during both cross-over periods (arm 1: N = 9; arm 2: N = 7). The remaining 23 participants withdrew from the study (N = 12), were excluded on the basis of problems of eligibility (N = 5) or did not complete the primary outcome data (N = 6: still included in the cohort follow-up phase). A total of 22 participants started the cohort follow-up phase, although 3 of these participants did not complete the final follow-up visit, leaving 19 participants for the 1-year effectiveness assessment. There were no major differences at baseline between allocated groups. As predicted, about 90% participants were female with mean age about 57 years. Almost all participants reported symptoms of urgency, combined with varying combinations of passive and urge FI. All participants reported previous conservative management for their FI symptoms (as per NICE guidance). Numbers of FI events at baseline were concordant with design assumptions (based on approx. seven events in a 1-week period). Median St Mark’s incontinence score was 19 in both groups, indicating severe symptoms (max score 24). E-event recordings were only undertaken by a minority (14/39) of participants. Test stimulation was performed using a tined lead in 68.6% participants. General anaesthesia was used in 70.6% of procedures and median operating time was 36 minutes (range 30–55 minutes). The lead was positioned in foramina S3 in most participants (91.4%) with some variations in fidelity of siting based on individual electrode responses (only 50% lead placements achieved the ideal published standard of motor or sensory responses for three electrodes

Researchers with mediation hypotheses must consider which design to use: within-subject or between-subject? In this paper, I argue that three factors should influence design choice: validity, causality, and statistical power. Threats to validity include carry-over effects, participant awareness, measurement, and more. Causality is a core element of mediation, and the assumptions required for causal inference differ between the two designs. Between-subject designs require more restrictive no-confounder assumptions, but within-subject designs require the assumption of no carry-over effects. Statistical power should be higher in within-subject designs, but the degree and conditions of this advantage are unknown for mediation analysis. A Monte Carlo simulation compares designs under a broad range of sample sizes, effect sizes, and correlations among repeated measurements. The results show within-subject designs require about half the sample size of between-subject designs to detect indirect effects of the same size, but this difference can vary with population parameters. I provide an empirical example and R script for conducting power analysis for within-subject mediation analysis. Researchers interested in conducting mediation analysis should not select within-subject designs merely because of higher power, but they should also consider validity and causality in their decision, both of which can favor between-subject designs.

Indirect standardization, and its associated parameter the standardized incidence ratio, is a commonly-used tool in hospital profiling for comparing the incidence of negative outcomes between an index hospital and a larger population of reference hospitals, while adjusting for confounding covariates. In statistical inference of the standardized incidence ratio, traditional methods often assume the covariate distribution of the index hospital to be known. This assumption severely compromises one's ability to compute required sample sizes for high-powered indirect standardization, as in contexts where sample size calculation is desired, there are usually no means of knowing this distribution. This paper presents novel statistical methodology to perform sample size calculation for the standardized incidence ratio without knowing the covariate distribution of the index hospital and without collecting information from the index hospital to estimate this covariate distribution. We apply our methods to simulation studies and to real hospitals, to assess both its capabilities in a vacuum and in comparison to traditional assumptions of indirect standardization.

Modeling and drawing inference on the joint associations between single-nucleotide polymorphisms and a disease has sparked interest in genome-wide associations studies. In the motivating Boston Lung Cancer Survival Cohort (BLCSC) data, the presence of a large number of single nucleotide polymorphisms of interest, though smaller than the sample size, challenges inference on their joint associations with the disease outcome. In similar settings, we find that neither the debiased lasso approach (van de Geer et al., 2014), which assumes sparsity on the inverse information matrix, nor the standard maximum likelihood method can yield confidence intervals with satisfactory coverage probabilities for generalized linear models. Under this large n, diverging p scenario, we propose an alternative debiased lasso approach by directly inverting the Hessian matrix without imposing the matrix sparsity assumption, which further reduces bias compared to the original debiased lasso and ensures valid confidence intervals with nominal coverage probabilities. We establish the asymptotic distributions of any linear combinations of the parameter estimates, which lays the theoretical ground for drawing inference. Simulations show that the proposed refined debiased estimating method performs well in removing bias and yields honest confidence interval coverage. We use the proposed method to analyze the aforementioned BLCSC data, a large-scale hospital-based epidemiology cohort study investigating the joint effects of genetic variants on lung cancer risks.

BackgroundThe statistical plan of a phase II trial should balance minimizing the premature termination of potentially beneficial therapies (i.e. false negatives) and the further, costly testing of ineffective drugs (i.e. false positives). We sought to examine the methodology, reporting, and bias in the interpretation of outcomes of phase II oncology trials in recent years.Materials and methodsIn a retrospective cross-sectional analysis, we reviewed all full-length articles published on PubMed from 1 January 2021 to 20 June 2022. We searched for data regarding the sample size calculation (number, α value, power, and expected effect size), the primary and secondary outcomes and results, and the authors' conclusion of the study.ResultsAbout 5.4% of studies (n = 10) used a statistical power that was inferior to 80%, and 16.7% (n = 34) did not indicate the level of power for the sample size calculation. Approximately 16.7% (n = 31) of studies used a one-sided α level of ≤0.025; 17.7% (n = 33) of studies used a predefined threshold (no comparator effect size or difference between groups) to determine the sample size for efficacy. The percentage of studies with a positive authors' conclusion but not meeting the primary endpoint, or the endpoint was equivocal, was 27.4% (n = 51).ConclusionMany randomized phase II studies in oncology failed to report essential data for determining sample size calculations, many did not actually use a comparator to determine efficacy even though the studies were randomized, and many had positive conclusions even though the results were indeterminate or the primary endpoint was not met.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

When identifying differentially expressed genes between two conditions using human population RNA-seq samples, we found a phenomenon by permutation analysis: two popular bioinformatics methods, DESeq2 and edgeR, have unexpectedly high false discovery rates. Expanding the analysis to limma-voom, NOISeq, dearseq, and Wilcoxon rank-sum test, we found that FDR control is often failed except for the Wilcoxon rank-sum test. Particularly, the actual FDRs of DESeq2 and edgeR sometimes exceed 20% when the target FDR is 5%. Based on these results, for population-level RNA-seq studies with large sample sizes, we recommend the Wilcoxon rank-sum test.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

We have previously derived power calculation formulas for cohort studies and clinical trials using the longitudinal mixed effects model with random slopes and intercepts to compare rate of change across groups [Ard & Edland, Power calculations for clinical trials in Alzheimer's disease. J Alzheim Dis 2011;21:369-77]. We here generalize these power formulas to accommodate 1) missing data due to study subject attrition common to longitudinal studies, 2) unequal sample size across groups, and 3) unequal variance parameters across groups. We demonstrate how these formulas can be used to power a future study even when the design of available pilot study data (i.e., number and interval between longitudinal observations) does not match the design of the planned future study. We demonstrate how differences in variance parameters across groups, typically overlooked in power calculations, can have a dramatic effect on statistical power. This is especially relevant to clinical trials, where changes over time in the treatment arm reflect background variability in progression observed in the placebo control arm plus variability in response to treatment, meaning that power calculations based only on the placebo arm covariance structure may be anticonservative. These more general power formulas are a useful resource for understanding the relative influence of these multiple factors on the efficiency of cohort studies and clinical trials, and for designing future trials under the random slopes and intercepts model.

In planning randomized clinical trials (RCTs) for diseases such as Alzheimer's disease (AD), researchers frequently rely on the use of existing data obtained from only two time points to estimate sample size via the subtraction of baseline from follow-up measurements in each subject. However, the inadequacy of this method has not been reported. The aim of this study is to discuss the limitation of sample size estimation based on the subtraction of available data from only two time points for RCTs. Mathematical equations are derived to demonstrate the condition under which the obtained data pairs with variable time intervals could be used to adequately estimate sample size. The MRI-based hippocampal volume measurements from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Monte Carlo simulations (MCS) were used to illustrate the existing bias and variability of estimates. MCS results support the theoretically derived condition under which the subtraction approach may work. MCS also show the systematically under- or over-estimated sample sizes by up to 32.27 % bias. Not used properly, such subtraction approach outputs the same sample size regardless of trial durations partly due to the way measurement errors are handled. Estimating sample size by subtracting two measurements should be treated with caution. Such estimates can be biased, the magnitude of which depends on the planned RCT duration. To estimate sample sizes, we recommend using more than two measurements and more comprehensive approaches such as linear mixed effect models.

Background and purposeStroke is the leading cause of death and long-term disability worldwide. Previous genome-wide association studies identified 51 loci associated with stroke (mostly ischemic) and its subtypes among predominantly European populations. Using whole-genome sequencing in ancestrally diverse populations from the Trans-Omics for Precision Medicine (TOPMed) Program, we aimed to identify novel variants, especially low-frequency or ancestry-specific variants, associated with all stroke, ischemic stroke and its subtypes (large artery, cardioembolic, and small vessel), and hemorrhagic stroke and its subtypes (intracerebral and subarachnoid).MethodsWhole-genome sequencing data were available for 6833 stroke cases and 27 116 controls, including 22 315 European, 7877 Black, 2616 Hispanic/Latino, 850 Asian, 54 Native American, and 237 other ancestry participants. In TOPMed, we performed single variant association analysis examining 40 million common variants and aggregated association analysis focusing on rare variants. We also combined TOPMed European populations with over 28 000 additional European participants from the UK BioBank genome-wide array data through meta-analysis.ResultsIn the single variant association analysis in TOPMed, we identified one novel locus 13q33 for large artery at whole-genome-wide significance (P

Background/aimsWhen participants in individually randomized group treatment trials are treated by multiple clinicians or in multiple group treatment sessions throughout the trial, this induces partially nested clusters which can affect the power of a trial. We investigate this issue in the Whole Health Options and Pain Education trial, a three-arm pragmatic, individually randomized clinical trial. We evaluate whether partial clusters due to multiple visits delivered by different clinicians in the Whole Health Team arm and dynamic participant groups due to changing group leaders and/or participants across treatment sessions during treatment delivery in the Primary Care Group Education arm may impact the power of the trial. We also present a Bayesian approach to estimate the intraclass correlation coefficients.MethodsWe present statistical models for each treatment arm of Whole Health Options and Pain Education trial in which power is estimated under different intraclass correlation coefficients and mapping matrices between participants and clinicians or treatment sessions. Power calculations are based on pairwise comparisons. In practice, sample size calculations depend on estimates of the intraclass correlation coefficients at the treatment sessions and clinician levels. To accommodate such complexities, we present a Bayesian framework for the estimation of intraclass correlation coefficients under different participant-to-session and participant-to-clinician mapping scenarios. We simulated continuous outcome data based on various clinical scenarios in Whole Health Options and Pain Education trial using a range of intraclass correlation coefficients and mapping matrices and used Gibbs samplers with conjugate priors to obtain posteriors of the intraclass correlation coefficients under those different scenarios. Posterior means and medians and their biases are calculated for the intraclass correlation coefficients to evaluate the operating characteristics of the Bayesian intraclass correlation coefficient estimators.ResultsPower for Whole Health Team versus Primary Care Group Education is sensitive to the intraclass correlation coefficient in the Whole Health Team arm. In these two arms, an increased number of clinicians, more evenly distributed workload of clinicians, or more homogeneous treatment group sizes leads to increased power. Our simulation study for the intraclass correlation coefficient estimation indicates that the posterior mean intraclass correlation coefficient estimator has less bias when the true intraclass correlation coefficients are large (i.e. 0.10), but when the intraclass correlation coefficient is small (i.e. 0.01), the posterior median intraclass correlation coefficient estimator is less biased.ConclusionKnowledge of intraclass correlation coefficients and the structure of clustering are critical to the design of individually randomized group treatment trials with partially nested clusters. We demonstrate that the intraclass correlation coefficient of the Whole Health Team arm can affect power in the Whole Health Options and Pain Education trial. A Bayesian approach provides a flexible procedure for estimating the intraclass correlation coefficients under complex scenarios. More work is needed to educate the research community about the individually randomized group treatment design and encourage publication of intraclass correlation coefficients to help inform future trial designs.

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and children's health in the United States. A cohort of n = 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

Background Randomised controlled trials (‘trials’) are susceptible to poor participant recruitment and retention. Studies Within A Trial are the strongest methods for testing the effectiveness of strategies to improve recruitment and retention. However, relatively few of these have been conducted. Objectives PROMoting THE Use of Studies Within A Trial aimed to facilitate at least 25 Studies Within A Trial evaluating recruitment or retention strategies. We share our experience of delivering the PROMoting THE Use of Studies Within A Trial programme, and the lessons learnt for undertaking randomised Studies Within A Trial. Design A network of 10 Clinical Trials Units and 1 primary care research centre committed to conducting randomised controlled Studies Within A Trial of recruitment and/or retention strategies was established. Promising recruitment and retention strategies were identified from various sources including Cochrane systematic reviews, the Study Within A Trial Repository, and existing prioritisation exercises, which were reviewed by patient and public members to create an initial priority list of seven recruitment and eight retention interventions. Host trial teams could apply for funding and receive support from the PROMoting THE Use of Studies Within A Trial team to undertake Studies Within A Trial. We also tested the feasibility of undertaking co-ordinated Studies Within A Trial, across multiple host trials simultaneously. Setting Clinical trials unit-based trials recruiting or following up participants in any setting in the United Kingdom were eligible. Participants Clinical trials unit-based teams undertaking trials in any clinical context in the United Kingdom. Interventions Funding of up to £5000 and support from the PROMoting THE Use of Studies Within A Trial team to design, implement and report Studies Within A Trial. Main outcome measures Number of host trials funded. Results Forty-two Studies Within A Trial were funded (31 host trials), across 12 Clinical Trials Units. The mean cost of a Study Within A Trial was £3535. Twelve Studies Within A Trial tested the same strategy across multiple host trials using a co-ordinated Study Within A Trial design, and four used a factorial design. Two recruitment and five retention strategies were evaluated in more than one host trial. PROMoting THE Use of Studies Within A Trial will add 18% more Studies Within A Trial to the Cochrane systematic review of recruitment strategies, and 79% more Studies Within A Trial to the Cochrane review of retention strategies. For retention, we found that pre-notifying participants by card, letter or e-mail before sending questionnaires was effective, as was the use of pens, and sending personalised text messages to improve questionnaire response. We highlight key lessons learnt to guide others planning Studies Within A Trial, including involving patient and public involvement partners; prioritising and selecting strategies to evaluate and elements to consider when designing a Study Within A Trial; obtaining governance approvals; implementing Studies Within A Trial, including individual and co-ordinated Studies Within A Trials; and reporting Study Within A Trials. Limitations The COVID-19 pandemic negatively impacted five Studies Within A Trial, being either delayed (n = 2) or prematurely terminated (n = 3). Conclusions PROMoting THE Use of Studies Within A Trial significantly increased the evidence base for recruitment and retention strategies. When provided with both funding and practical support, host trial teams successfully implemented Studies Within A Trial. Future work Future research should identify and target gaps in the evidence base, including widening Study Within A Trial uptake, undertaking more complex Studies Within A Trial and translating Study Within A Trial evidence into practice. Study registration All Studies Within A Trial in the PROMoting THE Use of Studies Within A Trial programme had to be registered with the Northern Ireland Network for Trials Methodology Research Study Within A Trial Repository. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 13/55/80) and is published in full in Health Technology Assessment; Vol. 28, No. 2. See the NIHR Funding and Awards website for further award information. Plain language summary Aims of the research A Study Within A Trial is a research study nested inside a larger ‘host trial’, promoting the use of Studies Within A Trial aimed to do Study Within A Trial routine practice in clinical trial units by funding and supporting at least 25 Studies Within A Trial. Background The best way to test health and social care treatments is to do a randomised controlled trial (‘trial’), where some patients get the treatment being tested and some do not. The results of different groups are compared to see if the treatment improves care. Recruiting patients and keeping them involved in trials is often very difficult. Research teams often do not know how best to recruit and keep patients engaged as the methods have not been tested to see if they work. The best way to test these methods is by doing a Study Within A Trial. We test a programme of Studies Within A Trial for recruiting and keeping patients engaged in trials. Methods Trial teams were able to apply for funding of up to £5000 and receive support from Promoting the use of Study Within A Trial team to do Studies Within A Trial. We used our experience of doing Studies Within A Trial to outline lessons learnt for doing Studies Within A Trial. Results We funded 42 Studies Within A Trial and gave teams necessary advice to do them. We significantly increased the knowledge for both recruitment and retention strategies, and found ‘pre-notifying’ before sending questionnaires, sending pens and personalised text messages were all effective for increasing responses by participants. We tested Studies Within A Trial across several different trials at the same time to find out more quickly whether their methods worked. We highlight key lessons learnt to guide others doing Studies Within A Trial, including involving patient partners; picking the right strategy to test; getting ethical approvals; how to do and report Studies Within A Trial. Conclusions Promoting the use of studies within a trial was successful and supported more Studies Within A Trial than planned. We hope our experience will support those doing Studies Within A Trial in the future. Scientific summary Background Many delivery aspects of randomised controlled trials (RCTs) have not been subjected to rigorous evaluation. Strategies to enhance recruitment and retention often tend to not be based on evidence. However, there is an increasing interest in embedding RCTs of such strategies. The Medical Research Council (MRC) funded systematic techniques for assisting recruitment to trials (START), which found it feasible to test two strategies for recruitment and retention across a number of trials by performing randomised ‘Studies Within A Trial (SWATs)’. Aims The aim of the PROMoting THE USE of Studies Within A Trial (PROMETHEUS) programme was to build on the START initiative and make embedding SWATs standard practice across Clinical Trials Units (CTUs). We intended to pump prime and facilitate the start of at least 25 SWATs across multiple CTUs within 30 months. The ultimate aim was to make the inclusion of SWATs routine when conducting a trial in a CTU. We share our experience of delivering the PROMETHEUS programme, along with the lessons learnt for undertaking randomised SWATs of recruitment and retention methods. Methods A network of 10 CTUs and one primary care research centre committed to conducting randomised controlled SWATs of recruitment and/or retention interventions was established by the PROMETHEUS team. We identified promising recruitment and retention interventions from a variety of sources including Cochrane systematic reviews, the Northern Ireland Network for Trial Methodology Research SWAT Repository Store, and existing prioritisation exercises. Promising strategies were reviewed by our patient and public (PPI) members to create an initial priority list of seven recruitment and eight retention interventions. The programme allowed host trial teams to apply for funding of up to £5000 and receive support from the PROMETHEUS team to design, implement and report SWATs. We also tested the feasibility of undertaking co-ordinated SWATs, across multiple host trials simultaneously. Results The PROMETHEUS programme funded 42 SWATs, embedded within 31 host trials, across 12 CTUs. The mean cost of a funded SWAT was £3535. Of the 42 SWATs, 12 tested the same SWAT across multiple host trials using a co-ordinated SWAT design and four tested more than one strategy in a factorial design. Two recruitment and five retention strategies were evaluated in more than one host trial. In the space of just 4 years, PROMETHEUS will add 18% more SWATs to the Cochrane review of global recruitment strategies, and 79% more SWATs to the Cochrane review of global retention strategies. The results from the SWATs reported to date found there was no evidence of a significant difference in recruitment for any of the strategies tested. For retention, pre-notifying participants by card prior to sending questionnaires was effective [risk difference 3.3%, 95% confidence interval (CI) −3.0% to 9.6%]; as was pre-notifying participants by letter or e-mail (risk difference 3.8%, 95% CI −6.1% to 13.6%). Sending personalised text messages was more effective for improving the return of postal questionnaires compared to non-personalised text messages (risk ratio 1.16, 95% CI 1.00 to 1.33); and resulted in fewer completions via telephone compared with a non-personalised text [adjusted odds ratio (OR) 0.44, 95% CI 0.22 to 0.87]. Including a pen with a questionnaire probably increases retention and response rate (pooled OR 1.21, 95% CI 1.09 to 1.35). We highlight key lessons learnt below (see Recommendations section). Conclusions The PROMETHEUS programme significantly increased the international evidence base for both recruitment and retention strategies within RCTs. The funded SWATs evaluated a wide range of recruitment and retention strategies; however, the COVID-19 pandemic negatively impacted five funded SWATs, with two being delayed and three prematurely terminated. Through this project, we identified that when provided with both funding and practical support, host trial teams successfully implemented SWATs. PROMETHEUS led to an overall increase in the evidence base; however, ongoing ‘routine’ application of SWATs across RCTs employing the lessons learnt is required to ensure that efficient trial conduct strategies are identified. Recommendations Recommendations for funders All trial funders should contribute to the effort to improve the efficiency of trials. Funders should encourage the teams that they fund to undertake SWATs. Funding streams specifically designed to support SWATs must be made available to trial teams to continue building the trial process evidence base, for recruitment and retention as well as for other stages of the trial design and delivery process. This includes funding streams for undertaking specific SWATs, as well as infrastructure funding to support CTUs and other centres to undertake co-ordination activities that will support the design, conduct, reporting, and implementation of SWATs and their findings to inform the work of the National Institute for Health and Care Research (NIHR), the MRC, and other funders. PROMETHEUS has demonstrated that co-ordination of activity remains crucial to the delivery of SWATs. A central, national co-ordination point that provides hands-on support needs to continue and funding should be allocated for this. Additionally, CTUs should identify a lead for SWATs, to support SWAT activities and evidence-based trial conduct within the CTU, as well as links with others undertaking SWATs elsewhere to share best practice. The funding for both central and CTU-based support should be ongoing. SWAT priorities need to be identified and communicated clearly to funders, and funders should use these priorities to inform their funding decisions. Funders should develop a mechanism to promote SWAT questions that have been identified as a priority during the funding application process. The mean cost of funding requested for a standalone SWAT within PROMETHEUS was £3535 (range £500–5000). The co-ordinated SWATs cost was £10,668 (training SWAT) and £1306.40 (Christmas cards); however, these did not include costs for central co-ordination, data preparation and sharing by the host trial teams, data cleaning, analysis and write-up. These costs suggest that the £10,000 being offered by the NIHR for trial teams to include a SWAT should be sufficient for most planned SWATs. However, there may be occasions where trial teams may wish to test strategies that may be more expensive. When applying for SWAT funding, trial teams should be asked to indicate whether the question they are addressing is a priority SWAT question, and to provide a clear rationale for selecting that particular question. If teams are unable to undertake a SWAT, funders should ask that recruitment and retention methods are clearly reported to support the evidence base. Recommendations for Sponsors Our experience suggests that there is a need for clear, easily accessible information about the nature of SWATs, as well as the role of the funder in supporting SWATs. Any future changes proposed by the Health Research Authority (HRA) to the approvals process need to be communicated clearly and applied consistently to each SWAT. Recommendations for involving patient and public involvement partners in Studies Within A Trial research PPI should be considered when undertaking a SWAT, in the same way PPI is expected to be undertaken in the main trial. PPI partners should be involved to develop novel and untested recruitment and retention strategies, as well as to adapt existing strategies to the context of their specific host trial and the population being enrolled. Recommendations for oversight committees Our experience suggests that Trial Management Groups (TMGs) play a key role in decisions about whether a SWAT is undertaken and continued in the host trial or not. TMG members should encourage the uptake of SWATs in their trials. While the findings of SWATs may not always directly inform their host trial, the findings of SWATs undertaken during the early, or internal pilot, phase of the trial may inform the decisions about which strategies should be used at a later stage, such as in the main trial. Trial Steering Committees should review the SWAT activity and progress, in the same way that they review substudies in a trial. Data Monitoring Committee review is dependent on the specific host trial and SWAT strategy being evaluated. Recommendations for journals and reviewers Journal peer reviewer profiles should be updated to include methodological interests and expertise, to support evidence of suitability to undertake a peer review for a SWAT. When selecting peer reviewers, the SWAT and methodology interests as registered by reviewers should be used where possible. SWATs are a niche area and so to increase the pool of reviewers, journals should consider being more flexible when assessing reviewer credentials to review a SWAT, such as allowing relevant experience in place of a PhD. Reviewers should be advised that in many instances informed consent from participants need not be obtained when undertaking a SWAT, due to the low risk associated with the intervention and in the case of retention SWATs due to existing consent for further research being in place. This may depend on the jurisdiction. In the UK, this approach is supported by HRA guidance in relation to grading for SWAT interventions and approvals. Robust and transparent reporting is necessary, that is compliant with CONsolidated Standards Of Reporting Trials (CONSORT). Recommendations for trial teams and methodologists undertaking SWAT research There remains a need for continually updated research priorities to allow researchers to address the questions relevant at that time. When SWAT priorities are set, methodologists need to provide enough information to enable teams to make informed decisions about evaluating the priorities set. Further work is needed to help teams identify suitable SWAT strategies for their host trials. SWAT priorities need to be communicated clearly and consistently to trial teams. Recommendation for trial conduct and using SWAT evidence As the evidence base develops for effective and cost-effective recruitment and retention strategies, it will become increasingly important for trial teams to use this evidence base to inform their recruitment and retention activities. Trial teams need to actively engage with the evidence base to inform their practice. Funders will need to actively support the trials they fund to use evidence-informed recruitment and retention strategies. Recommendations for future research There remains a substantial need for more high-quality SWAT evidence and so Chief Investigators should be encouraged to consider the embedding of a SWAT at the funding stage. Further work is therefore needed to increase the awareness of the methodological importance of SWAT research with research teams, and to develop engagement strategies to increase SWAT activity. Future research needs to focus on identifying whether further replications are needed for existing evidence. If so, the gaps in the evidence base should be targeted. More co-ordination and replication of SWAT evaluations are encouraged. A ‘real-time’ and dynamic communication strategy including a clear cost and resource breakdown for each suggested SWAT should be developed. This will alleviate the burden on trials teams to begin costing exercises and enable them to make an informed decision more quickly as to whether they can embed a given SWAT. There is a need to aid teams to identify and select a suitable SWAT for their host trial populations. Pragmatic decisions on which SWAT may be appropriate and feasible to include should be taken as required. A mechanism to communicate SWAT research priorities is needed, and this information needs to be readily accessible for all trialists to refer to. Our findings demonstrate that within an individual host trial, there is often a capacity to address more than one SWAT question, either separately, or simultaneously using a factorial design. This suggests that there is a capacity to significantly speed up and strengthen the evidence base through teams undertaking more than one SWAT in their trials where relevant. For certain strategies, co-ordinated SWATs should be encouraged. This method could be used to rapidly replicate SWAT evaluations to plug the evidence gap, as well as to evaluate more complex recruitment and retention strategies that may be more challenging to undertake using individual SWATs. Materials should be developed to advise teams on how to undertake co-ordinated SWATs, as well as a method of networking to enable teams to promote their co-ordinated SWAT and collaborate. As the evidence base develops, it will become increasingly important for trialists to utilise the evidence base in a systematic way to identify both effective and ineffective strategies to inform their practice. Future work should therefore consider issues around the dissemination and implementation of SWATs and develop guidance to enable the wider trials community to undertake, report and adopt the findings of SWATs. Implementation science, the study of methods to promote the uptake of evidence-based practice, could be used to inform any such future work. Funders can also help by questioning strategies proposed by trial teams that are known to be either ineffective or not cost-effective. Improving the knowledge of the potential ‘harms’ from implementing interventions that have no evidence of benefit is an important next step to help improve uptake. While establishing the effectiveness of recruitment or retention strategies is important, the high costs of research waste and limited public finance mean that cost considerations around SWATs are just as important. With only one retention strategy having high Grading of Recommendations, Assessment, Development and Evaluations (GRADE) certainty of cost effectiveness, we encourage trial teams to undertake streamlined economic evaluations alongside all their SWATs in the future, for strategies shown to be effective, as well as those that are ineffective. For cost effectiveness, trial teams should look to report the cost per additional participant recruited or retained (i.e. the incremental cost-effectiveness ratio). Value of information analyses can help determine the need for further SWAT evidence where several SWATs already exist. Many trial teams wish to contribute to developing the evidence base by undertaking non-randomised SWATs. Future work that informs the development of guidance for undertaking non-randomised SWATs would be helpful. Working with trial teams to develop engagement strategies and training to undertake SWATs would be beneficial. Audience specific guidance should be developed to support SWAT research. Trial teams have expressed they want to undertake SWATs that are important and necessary to increase the evidence base. Collaboration with funders, working groups involved in priority setting, and trial teams is needed to develop a mechanism to communicate this dynamic and evolving information once priority SWATs have been identified. Work is needed to identify the barriers that teams have when undertaking a SWAT, and strategies and solutions for addressing these barriers should be identified and implemented. Continued and proactive collaboration is needed with working groups to enable networking, and collaboration with teams undertaking SWAT research. Reporting guidance is needed to support teams when writing publications to ensure sufficient information is included to GRADE evaluation can be undertaken. Study registration All SWATs in the PROMETHEUS programme had to be registered with the Northern Ireland Network for Trials Methodology Research SWAT Repository. Funding details This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 13/55/80) and is published in full in Health Technology Assessment; Vol. 28, No. 2. See the NIHR Funding and Awards website for further award information.

In modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term 'variance stratification'. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We develop a procedure to compute variant-specific inflation factors, and show how it can be used for diagnosis of genetic association analyses on pooled individual level data from multiple studies. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We illustrate the variance stratification problem, its solutions, and the proposed diagnostic procedure, in simulations and in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI.

The contralateral delay activity (CDA) is an event-related potential component commonly used to examine the online processes of visual working memory. Here, we provide a robust analysis of the statistical power that is needed to achieve reliable and reproducible results with the CDA. Using two very large EEG datasets that examined the contrast between CDA amplitude with set sizes 2 and 6 items and set sizes 2 and 4 items, we present a subsampling analysis that estimates the statistical power achieved with varying numbers of subjects and trials based on the proportion of significant tests in 10,000 iterations. We also generated simulated data using Bayesian multilevel modeling to estimate power beyond the bounds of the original datasets. The number of trials and subjects required depends critically on the effect size. Detecting the presence of the CDA-a reliable difference between contralateral and ipsilateral electrodes during the memory period-required only 30-50 clean trials with a sample of 25 subjects to achieve approximately 80% statistical power. However, for detecting a difference in CDA amplitude between two set sizes, a substantially larger number of trials and subjects were required; approximately 400 clean trials with 25 subjects to achieve 80% power. Thus, to achieve robust tests of how CDA activity differs across conditions, it is essential to be mindful of the estimated effect size. We recommend researchers designing experiments to detect set-size differences in the CDA collect substantially more trials per subject.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

We present a full-likelihood method to infer polygenic adaptation from DNA sequence variation and GWAS summary statistics to quantify recent transient directional selection acting on a complex trait. Through simulations of polygenic trait architecture evolution and GWASs, we show the method substantially improves power over current methods. We examine the robustness of the method under stratification, uncertainty and bias in marginal effects, uncertainty in the causal SNPs, allelic heterogeneity, negative selection, and low GWAS sample size. The method can quantify selection acting on correlated traits, controlling for pleiotropy even among traits with strong genetic correlation (|rg|=80%) while retaining high power to attribute selection to the causal trait. When the causal trait is excluded from analysis, selection is attributed to its closest proxy. We discuss limitations of the method, cautioning against strongly causal interpretations of the results, and the possibility of undetectable gene-by-environment (GxE) interactions. We apply the method to 56 human polygenic traits, revealing signals of directional selection on pigmentation, life history, glycated hemoglobin (HbA1c), and other traits. We also conduct joint testing of 137 pairs of genetically correlated traits, revealing widespread correlated response acting on these traits (2.6-fold enrichment, p = 1.5 × 10-7). Signs of selection on some traits previously reported as adaptive (e.g., educational attainment and hair color) are largely attributable to correlated response (p = 2.9 × 10-6 and 1.7 × 10-4, respectively). Lastly, our joint test shows antagonistic selection has increased type 2 diabetes risk and decrease HbA1c (p = 1.5 × 10-5).

We demonstrate the possibility of conducting synchronous, repeated, multi-game economic decision-making experiments with hundreds of subjects in-person or remotely with live streaming using entirely mobile platforms. Our experiment provides important proof-of-concept that such experiments are not only possible, but yield recognizable results as well as new insights, blurring the line between laboratory and field experiments. Specifically, our findings from 8 different experimental economics games and tasks replicate existing results from traditional laboratory experiments despite the fact that subjects play those games/task in a specific order and regardless of whether the experiment was conducted in person or remotely. We further leverage our large subject population to study the effect of large (N = 100) versus small (N = 10) group sizes on behavior in three of the scalable games that we study. While our results are largely consistent with existing findings for small groups, increases in group size are shown to matter for the robustness of those findings.

Effect sizes are commonly interpreted using heuristics established by Cohen (e.g., small: r = .1, medium r = .3, large r = .5), despite mounting evidence that these guidelines are mis-calibrated to the effects typically found in psychological research. This study's aims were to 1) describe the distribution of effect sizes across multiple instruments, 2) consider factors qualifying the effect size distribution, and 3) identify examples as benchmarks for various effect sizes. For aim one, effect size distributions were illustrated from a large, diverse sample of 9/10-year-old children. This was done by conducting Pearson's correlations among 161 variables representing constructs from all questionnaires and tasks from the Adolescent Brain and Cognitive Development Study® baseline data. To achieve aim two, factors qualifying this distribution were tested by comparing the distributions of effect size among various modifications of the aim one analyses. These modified analytic strategies included comparisons of effect size distributions for different types of variables, for analyses using statistical thresholds, and for analyses using several covariate strategies. In aim one analyses, the median in-sample effect size was .03, and values at the first and third quartiles were .01 and .07. In aim two analyses, effects were smaller for associations across instruments, content domains, and reporters, as well as when covarying for sociodemographic factors. Effect sizes were larger when thresholding for statistical significance. In analyses intended to mimic conditions used in "real-world" analysis of ABCD data, the median in-sample effect size was .05, and values at the first and third quartiles were .03 and .09. To achieve aim three, examples for varying effect sizes are reported from the ABCD dataset as benchmarks for future work in the dataset. In summary, this report finds that empirically determined effect sizes from a notably large dataset are smaller than would be expected based on existing heuristics.

The point-biserial correlation is a commonly used measure of effect size in two-group designs. New estimators of point-biserial correlation are derived from different forms of a standardized mean difference. Point-biserial correlations are defined for designs with either fixed or random group sample sizes and can accommodate unequal variances. Confidence intervals and standard errors for the point-biserial correlation estimators are derived from the sampling distributions for pooled-variance and separate-variance versions of a standardized mean difference. The proposed point-biserial confidence intervals can be used to conduct directional two-sided tests, equivalence tests, directional non-equivalence tests, and non-inferiority tests. A confidence interval for an average point-biserial correlation in meta-analysis applications performs substantially better than the currently used methods. Sample size formulas for estimating a point-biserial correlation with desired precision and testing a point-biserial correlation with desired power are proposed. R functions are provided that can be used to compute the proposed confidence intervals and sample size formulas.

Trials of candidate agents for HIV pre-exposure prophylaxis (PrEP) might randomly assign participants to be given a new PrEP agent or oral coformulated tenofovir disoproxil fumarate plus emtricitabine. This design presents unique challenges in interpretation. First, with two active arms, HIV incidence might be low. Second, the effectiveness of tenofovir disoproxil fumarate plus emtricitabine varies across populations; thus, similar HIV incidence between groups could be consistent with a wide range of effectiveness for the new PrEP. We propose a two-part approach to trial results. First, we use Bayesian methods to incorporate assumptions about the background incidence of HIV in the trial in the absence of PrEP, possibly augmented by external data. On the basis of the estimated background incidence, we estimate and compare the number of averted (or prevented) HIV infections in each of the two trial groups, calculating the averted infections ratio. We apply these methods to a completed trial of tenofovir alafenamide plus emtricitabine for PrEP. Our framework shows that leveraging external information to estimate averted infections and the averted infections ratio enhances the efficiency and interpretation of active-controlled PrEP trials.

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

UNLABELLED: Risk assessments of transfusion-transmitted emerging infectious diseases (EIDs) are complicated by the fact that blood donors demographics and behaviors can be different from the general population. Therefore, when assessing potential blood donor exposure to EIDs, the use of general population characteristics, such as U.S. travel statistics, may invoke uncertainties that result in inaccurate estimates of blood donor exposure. This may, in turn, lead to the creation of donor deferral policies that do not match actual risk. STUDY DESIGN AND METHODS: This article reports on the development of a system to rapidly assess EID risks for a nationally representative portion of the U.S. blood donor population. To assess the effectiveness of this system, a test survey was developed and deployed to a statistically representative sample frame of blood donors from five blood collecting organizations. Donors were directed to an online survey to ascertain their recent travel and potential exposure to Middle East respiratory syndrome coronavirus (MERS-CoV). RESULTS: A total of 7128 responses were received from 54 256 invitations. The age-adjusted estimated total number of blood donors potentially exposed to MERS-CoV was approximately 15 640 blood donors compared to a lower U.S. general population-based estimate of 9610 blood donors. CONCLUSION: The structured donor demographic sample-based data provided an assessment of blood donors potential exposure to an emerging pathogen that was 63% larger than the U.S. population-based estimate. This illustrates the need for tailored blood donor-based EID risk assessments that provide more specific demographic risk intelligence and can inform appropriate regulatory decision making.

Sparse high-dimensional massive sample size (sHDMSS) time-to-event data present multiple challenges to quantitative researchers as most current sparse survival regression methods and software will grind to a halt and become practically inoperable. This paper develops a scalable ℓ0 -based sparse Cox regression tool for right-censored time-to-event data that easily takes advantage of existing high performance implementation of ℓ2 -penalized regression method for sHDMSS time-to-event data. Specifically, we extend the ℓ0 -based broken adaptive ridge (BAR) methodology to the Cox model, which involves repeatedly performing reweighted ℓ2 -penalized regression. We rigorously show that the resulting estimator for the Cox model is selection consistent, oracle for parameter estimation, and has a grouping property for highly correlated covariates. Furthermore, we implement our BAR method in an R package for sHDMSS time-to-event data by leveraging existing efficient algorithms for massive ℓ2 -penalized Cox regression. We evaluate the BAR Cox regression method by extensive simulations and illustrate its application on an sHDMSS time-to-event data from the National Trauma Data Bank with hundreds of thousands of observations and tens of thousands sparsely represented covariates.

Background: Understanding the stability of quantitative sensory tests (QSTs) over time is important to aid clinicians in selecting a battery of tests for assessing and monitoring patients. This study evaluated the short- and long-term reliability of selected QSTs. Methods: Twenty healthy women participated in three experimental sessions: Baseline, 2 weeks, and 6 months. Measurements included pressure pain thresholds (PPT) in the neck, upper back, and leg; Pressure-cuff pain tolerance around the upper-arm; conditioned pain modulation during a pressure-cuff stimulus; and referred pain following a suprathreshold pressure stimulation. Intraclass correlation coefficients (ICC) and minimum detectable change (MDC) were calculated. Results: Reliability for PPT was excellent for all sites at 2 weeks (ICC, 0.96-0.99; MDC, 22-55 kPa) and from good to excellent at 6 months (ICC, 0.88--0.95; MDC, 47--91 kPa). ICC for pressure-cuff pain tolerance indicated excellent reliability at both times (0.91--0.97). For conditioned pain modulation, reliability was moderate for all sites at 2 weeks (ICC, 0.57--0.74; MDC, 24%--35%), while it was moderate at the neck (ICC, 0.54; MDC, 27%) and poor at the upper back and leg at 6 months. ICC for referred pain areas was excellent at 2 weeks (0.90) and good at 6 months (0.86). Conclusions: PPT, pressure pain tolerance, and pressure-induced referred pain should be considered reliable procedures to assess the pain-sensory profile over time. In contrast, conditioned pain modulation was shown to be unstable. Future studies prospectively analyzing the pain-sensory profile will be able to better calculate appropriate sample sizes. [ABSTRACT FROM AUTHOR]

Background: Mental health is important at every stage of life, from childhood and adolescence through adulthood. Worldwide interest in geriatric depression has increased but studies to assess the depression among the elderly population in urban slums has hardly been done. So this study would shed light on the risk factors of depression among geriatrics in urban slums. Aim & Objective: To study the epidemiological determinants such as age, marital status, education, financial dependency, economic status and chronic illness in relation to of depression among the geriatric population (60-80 years). Settings and Design: Community-based, cross-sectional study for 24 months with a sample size of 209. Methods & Material: Urban slum area represented by one health post was selected as the study area which caters to around 96,630 slum residents. Pre-tested semi-structured interviews were conducted after selecting households by systematic random sampling. Statistical analysis: Data was analyzed using SPSS version 21. A chi-square test was applied. Result: The present study shows overall prevalence of depression among the elderly above 60 years of age to be 48.6%. Depression is found to been significantly associated with an increase in age, living alone (72.7%), lower class economic status (100%), financial dependency (54%), history of chronic family illness (54.7%) and with no formal education (62.1%) among elderly dwelling in slums. Conclusions: There is a high prevalence of depression in the community and hence, a need to sensitize primary level health care services to institute screening tests considering the association of these determinants with depression and link them to specialized services for further management. [ABSTRACT FROM AUTHOR]

Introduction: Pre-hypertension is a borderline health state of increased blood pressure (BP) that falls short of the measurable parameters at which surveillance and/or therapy would be required. The approach of identifying people "At Risk" of developing hypertension can be more cost-effective and feasible for applying lifestyle interventions. Objectives: The objective of the present study is to find the prevalence of pre-hypertensives and associated bio-socio-demographic factors Materials and Methods: A cross-sectional study was conducted among 1946 participants aged 19 years and more in the Doiwala block of Dehradun, Uttarakhand. Multistage sampling was used to arrive at desired sample size. A pre-validated, structured questionnaire was used for data collection. The questionnaire included information on the socio-demographic profile (age, sex, education etc.), awareness about hypertension and its associated risk factors. Statistical Analysis: The chi-square test was used to compare proportions and draw inferences. Results: 958 (49.2%) study participants out of a total 1946 were found to be pre-hypertensives. A statistically significant association was found between pre-hypertension and factors such as male gender, age, education, occupation and waist-hip ratio. (p<0.05) Conclusion: It is recommended that identification on the pre-hypertensive group and subjecting them to lifestyle modification could be a fruitful strategy for preventing them from becoming hypertensive. [ABSTRACT FROM AUTHOR]

BACKGROUND:Biannual, mass azithromycin distribution has previously been shown to reduce all-cause child mortality in sub-Saharan Africa. Subgroup analysis suggested that the strongest effects were in the youngest children, leading to the hypothesis that targeting younger age groups might be an effective strategy to prevent mortality. We present the methods of two randomized controlled trials designed to evaluate mass and targeted azithromycin distribution for the prevention of child mortality in Burkina Faso, West Africa. METHODS/DESIGN:The Child Health with Azithromycin Treatment (CHAT) study consists of two nested, randomized controlled trials. In the first, communities are randomized in a 1:1 fashion to biannual, mass azithromycin distribution or placebo. The primary outcome is under-5 all-cause mortality measured at the community level. In the second, children attending primary healthcare facilities during the first 5-12 weeks of life for a healthy child visit (e.g., for vaccination) are randomized in a 1:1 fashion to a single orally administered dose of azithromycin or placebo. The primary outcome is all-cause mortality measured at 6 months of age. The trial commenced enrollment in August 2019. DISCUSSION:This study is expected to provide evidence on two health systems delivery approaches (mass and targeted treatment) for azithromycin to prevent all-cause child mortality. The results will inform global and national policies related to azithromycin for the prevention of child mortality. TRIAL REGISTRATION:ClinicalTrials.gov, ID: NCT03676764. Registered on 19 September 2018; prospectively registered pre results.

Power calculation prior to a genetic experiment can help investigators choose the optimal sample size to detect a quantitative trait locus (QTL). Without the guidance of power analysis, an experiment may be underpowered or overpowered. Either way will result in wasted resource. QTL mapping and genome-wide association studies (GWAS) are often conducted using a linear mixed model (LMM) with controls of population structure and polygenic background using markers of the whole genome. Power analysis for such a mixed model is often conducted via Monte Carlo simulations. In this study, we derived a non-centrality parameter for the Wald test statistic for association, which allows analytical power analysis. We show that large samples are not necessary to detect a biologically meaningful QTL, say explaining 5% of the phenotypic variance. Several R functions are provided so that users can perform power analysis to determine the minimum sample size required to detect a given QTL with a certain statistical power or calculate the statistical power with given sample size and known values of other population parameters.

BackgroundLow birth weight in term-born individuals correlates with adverse cardiometabolic outcomes; excess glucocorticoid exposure has been linked to these relationships. We hypothesized that cortisol and adrenal androgens would correlate inversely with birthweight and directly with markers of cardiometabolic risk in school-aged children born extremely preterm; further, preterm-born would have increased cortisol and adrenal androgens compared to term-born children.MethodsSaliva samples were obtained at age 6 from 219 preterm-born children followed since birth and 40 term-born children and analyzed for dehydroepiandrosterone (DHEA) and cortisol. Cortisol was also measured at home (awakening, 30' later, evening).ResultsFor preterm-born children, cortisol and DHEA correlated inversely with weight and length Z-scores at 36 weeks PMA and positively with systolic BP. DHEA was higher in preterm-born than term-born children (boys p

Saturation is commonly used to determine sample sizes in qualitative research, yet there is little guidance on what influences saturation. We aimed to assess saturation and identify parameters to estimate sample sizes for focus group studies in advance of data collection. We used two approaches to assess saturation in data from 10 focus group discussions. Four focus groups were sufficient to identify a range of new issues (code saturation), but more groups were needed to fully understand these issues (meaning saturation). Group stratification influenced meaning saturation, whereby one focus group per stratum was needed to identify issues; two groups per stratum provided a more comprehensive understanding of issues, but more groups per stratum provided little additional benefit. We identify six parameters influencing saturation in focus group data: study purpose, type of codes, group stratification, number of groups per stratum, and type and degree of saturation.

Although recent Genome-Wide Association Studies have identified novel associations for common variants, there has been no comprehensive exome-wide search for low-frequency variants that affect the risk of venous thromboembolism (VTE). We conducted a meta-analysis of 11 studies comprising 8,332 cases and 16,087 controls of European ancestry and 382 cases and 1,476 controls of African American ancestry genotyped with the Illumina HumanExome BeadChip. We used the seqMeta package in R to conduct single variant and gene-based rare variant tests. In the single variant analysis, we limited our analysis to the 64,794 variants with at least 40 minor alleles across studies (minor allele frequency [MAF] ~0.08%). We confirmed associations with previously identified VTE loci, including ABO, F5, F11, and FGA. After adjusting for multiple testing, we observed no novel significant findings in single variant or gene-based analysis. Given our sample size, we had greater than 80% power to detect minimum odds ratios greater than 1.5 and 1.8 for a single variant with MAF of 0.01 and 0.005, respectively. Larger studies and sequence data may be needed to identify novel low-frequency and rare variants associated with VTE risk.

BackgroundMotivated by an inconsistency between reports of high diagnosis-classification accuracies and known heterogeneity in attention-deficit/hyperactivity disorder (ADHD), this study assessed classification accuracy in studies of ADHD as a function of methodological factors that can bias results. We hypothesized that high classification results in ADHD diagnosis are inflated by methodological factors.MethodsWe reviewed 69 studies (of 95 studies identified) that used neuroimaging features to predict ADHD diagnosis. Based on reported methods, we assessed the prevalence of circular analysis, which inflates classification accuracy, and evaluated the relationship between sample size and accuracy to test if small-sample models tend to report higher classification accuracy, also an indicator of bias.ResultsCircular analysis was detected in 15.9% of ADHD classification studies, lack of independent test set was noted in 13%, and insufficient methodological detail to establish its presence was noted in another 11.6%. Accuracy of classification ranged from 60% to 80% in the 59.4% of reviewed studies that met criteria for independence of feature selection, model construction, and test datasets. Moreover, there was a negative relationship between accuracy and sample size, implying additional bias contributing to reported accuracies at lower sample sizes.ConclusionsHigh classification accuracies in neuroimaging studies of ADHD appear to be inflated by circular analysis and small sample size. Accuracies on independent datasets were consistent with known heterogeneity of the disorder. Steps to resolve these issues, and a shift toward accounting for sample heterogeneity and prediction of future outcomes, will be crucial in future classification studies in ADHD.

Clinical observations of patients with chronic diseases are often restricted in terms of duration. Therefore, obtaining a quantitative and comprehensive understanding of the chronology of chronic diseases is challenging, because of the inability to precisely estimate the patient's disease stage at the time point of observation. We developed a novel method to reconstitute long-term disease progression from temporally fragmented data by extending the nonlinear mixed-effects model to incorporate the estimation of "disease time" of each subject. Application of this method to sporadic Alzheimer's disease successfully depicted disease progression over 20 years. The covariate analysis revealed earlier onset of amyloid-β accumulation in male and female apolipoprotein E ε4 homozygotes, whereas disease progression was remarkably slower in female ε3 homozygotes compared with female ε4 carriers and males. Simulation of a clinical trial suggests patient recruitment using the information of precise disease time of each patient will decrease the sample size required for clinical trials.

Background: Contemporary society has led to the increasing use of electronic equipment that is very much responsible for the burden of electronic waste (e-waste). E-waste contains very hazardous substance that harms health and environmental conditions. There is no delicate mechanism for the management of e-waste in Lucknow city, Uttar Pradesh. This study assessed knowledge, practice, and awareness of e-waste management among residents of this city. Material and methods: The study was conducted amongst users of electronic equipment living in the Lucknow City of Uttar Pradesh. The study was a cross-sectional descriptive study. Multi-stage random sampling was done for the selection of participants for the study. A predesigned and pretested questionnaire was administered in a single setting for all phases. The total optimum sample size is 700 individuals who participated in the study. Data were entered in MS Excel 2016 and descriptive statistics such as frequencies and percentages were calculated, applying the chi-square test for association using R-4.2.1 Statistical software. Aim and objectives: To assess the knowledge, attitude and practices regarding the management of electronic waste among users of electronic equipment residing in Lucknow city. Results: Only 37% of users are aware that e-waste adversely affects health. Only 34.3% of users knew that e-waste should be given to the seller or manufacturer for recycling while rest told that it should be stored at home, sold to a scrap dealer, or disposed with normal waste. 87.3% users are not aware about e-waste govt guidelines. In the current study electronic and print media like television, radio and news paper were not found to be source of information for e-waste disposal. Conclusion: Education regarding the ill effects of e-waste is essential for people and awareness of proper disposal of e-waste is the need of the hour. Electronic and print media as well as companies producing electronic equipment should play a significant role to awaken the respondent about the disposal of e-waste. [ABSTRACT FROM AUTHOR]

Introduction: Hypertension (HTN) is a modifiable risk factor for coronary artery disease, heart failure, cerebrovascular disease and chronic renal failure. HTN affects about 1 billion people globally; by 2025, up to 1.58 billion adults worldwide are likely to suffer from complications of HTN. This study was done to know the diet and physical activity patterns and HTN among the population of three districts of Western Rajasthan. Objectives: To study the dietary and physical activity patterns among the population of Western Rajasthan. and to compare key findings among three districts Pali, Jodhpur and Barmer so that lifestyle changes can be recommended. Methods: A case-control study was done among attendees of NCD clinics of tertiary-level centers in Pali, Barmer and Jodhpur. Hospital controls were matched to age (± 5 years) and gender considering the prevalence of HTN to be 20%*, the proportion of exposure in the general population as 0.2, odds ratio to be 2.2, power =80%, alpha=5% sample size is estimated to be 102 cases & 102 controls (from each district). Results: Overall 'being married' (OR= 3.3), having diabetes/Cardiac disease(OR= 2.6), excessive salt consumption (OR= 2.7), moderate physical exercise less than 30 minutes (OR=1.9), using oil other than vegetable oil(OR=1.8), Age > 60 years (OR = 1.4) were the key risk factors. It was found that high BMI (BMI>27), consumption of non-vegetable oils (12.7%) was highest in Jodhpur, lack of moderate exercise for at least 30 minutes (81%), lack of sports activity (92%) was highest in Pali, least number of days/week of fruits and vegetables consumption (~1.64 days) was seen in Barmer. Conclusions: Change in quantity of salt consumption and incorporation of moderate physical exercise for >30 minutes was most followed in control of HTN among the attendees of NCD Clinics from the multiple advise given. [ABSTRACT FROM AUTHOR]

BackgroundPropensity score adjustment is a popular approach for confounding control in observational studies. Reliable frameworks are needed to determine relative propensity score performance in large-scale studies, and to establish optimal propensity score model selection methods.MethodsWe detail a propensity score evaluation framework that includes synthetic and real-world data experiments. Our synthetic experimental design extends the 'plasmode' framework and simulates survival data under known effect sizes, and our real-world experiments use a set of negative control outcomes with presumed null effect sizes. In reproductions of two published cohort studies, we compare two propensity score estimation methods that contrast in their model selection approach: L1-regularized regression that conducts a penalized likelihood regression, and the 'high-dimensional propensity score' (hdPS) that employs a univariate covariate screen. We evaluate methods on a range of outcome-dependent and outcome-independent metrics.ResultsL1-regularization propensity score methods achieve superior model fit, covariate balance and negative control bias reduction compared with the hdPS. Simulation results are mixed and fluctuate with simulation parameters, revealing a limitation of simulation under the proportional hazards framework. Including regularization with the hdPS reduces commonly reported non-convergence issues but has little effect on propensity score performance.ConclusionsL1-regularization incorporates all covariates simultaneously into the propensity score model and offers propensity score performance superior to the hdPS marginal screen.

To describe the international landscape of clinical trials in carbon-ion radiotherapy (CIRT), the authors reviewed the current status of 63 ongoing clinical trials (median, 47 participants) involving CIRT identified from the US clinicaltrials.gov trial registry and the World Health Organization International Clinical Trials Platform Registry. The objectives were to evaluate the potential for these trials to define the role of this modality in the treatment of specific cancer types and identify the major challenges and opportunities to advance this technology. A significant body of literature suggested the potential for advantageous dose distributions and, in preclinical biologic studies, the enhanced effectiveness for CIRT compared with photons and protons. In addition, clinical evidence from phase I/II trials, although limited, indicated the potential for CIRT to improve cancer outcomes. However, current high-level phase III randomized clinical trial evidence does not exist. Although there has been an increase in the number of trials investigating CIRT since 2010, and the number of countries and sites offering CIRT is slowly growing, this progress has excluded other countries. Several recommendations are proposed to study this modality to accelerate progress in the field, including: 1) increasing the number of multinational randomized clinical trials, 2) leveraging the existing CIRT facilities to launch larger multinational trials directed at common cancers combined with high-level quality assurance; and 3) developing more compact and less expensive next-generation treatment systems integrated with radiobiologic research and preclinical testing.

Sample size estimates are critical to the planning and interpretation of clinical studies, whether they are descriptive or analytical. Too small a sample size will result in imprecise estimates in a descriptive study and failure to achieve 'statistical significance' in an analytic or comparative study. Here we discuss what both researchers and readers should understand about the reasons for sample size estimates, how they are done and how achieving or not achieving the desired sample size can affect the interpretation of the outcomes.

The number of individuals in a random sample with close relatives in the sample is a quantity of interest when designing Genome Wide Association Studies and other cohort based genetic, and non-genetic, studies. In this paper, we develop expressions for the distribution and expectation of the number of p-th cousins in a sample from a population of size N under two diploid Wright-Fisher models. We also develop simple asymptotic expressions for large values of N. For example, the expected proportion of individuals with at least one p-th cousin in a sample of K individuals, for a diploid dioecious Wright-Fisher model, is approximately [Formula: see text]. Our results show that a substantial fraction of individuals in the sample will have at least a second cousin if the sampling fraction (K / N) is on the order of [Formula: see text]. This confirms that, for large cohort samples, relatedness among individuals cannot easily be ignored.

BackgroundThere are currently no treatments for empathy deficits in neuropsychiatric disorders. Acute administration of the hormone oxytocin has been associated with symptomatic improvements across animal models and several neuropsychiatric disorders, but results of the majority of oxytocin randomised controlled trials (RCTs) of longer duration have been negative or inconclusive. This lack of efficacy of may be due to rapid habituation to oxytocin with chronic dosing. The objective of the present study is to describe the design of a phase 2 adaptive randomised controlled crossover trial of intranasal oxytocin in frontotemporal dementia (FOXY) as an efficient model for future investigations of symptomatic treatments in neuropsychiatric and neurodegenerative disorders.MethodsStage 1 will identify which of three dose schedules is most promising based on change in the primary outcome measure, the Neuropsychiatric Inventory apathy/indifference domain score, over 6 weeks of treatment. In stage 2, additional patients are enrolled at the most promising dose for preliminary efficacy analysis when combined with stage 1 to determine if a phase 3 trial is warranted. Objective measures include facial expression recognition, cerebrospinal fluid (CSF) oxytocin levels, and behavioural ratings of videotaped interactions.ResultsA total of 20 patients per arm will be entered into stage 1 for a total of 60 patients. In stage 2, an additional 40 patients will be enrolled in the most promising dose arm.ConclusionsThe use of adaptive, crossover designs and inclusion of objective measures of change in CSF oxytocin levels and social behaviour will improve the efficiency and conclusiveness of RCTs of oxytocin and other symptomatic treatments in neuropsychiatric disorders.Trial registrationClinicalTrials.gov, NCT03260920 . Registered on August 24, 2017.