Publications by authors named "Andrew B Forbes"

Study Objective: Trauma resuscitation guidelines across the world have incorporated the administration of tranexamic acid (TXA) within 3 hours of injury. The 3-hour window was deduced from the Clinical Randomisation of an Antifibrinolytic in Significant Haemorrhage (CRASH-2) trial and has not been replicated. The aim of this study was to determine whether death within 28 days after trauma varied according to time from injury to the first TXA dose and, if so, precisely determine the therapeutic window.

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Background: Staircase designs are incomplete stepped wedge designs that, unlike standard stepped wedge designs, require clusters to contribute data for only a limited number of trial periods. Previous work has provided formulae based on asymptotic results for the calculation of the power of staircase designs to detect treatment effects of interest.

Methods: We conduct a simulation study to assess the finite sample performance of these formulae, and the impact of misspecifying the correlation structure when analysing data from staircase designs on inference for the treatment effect, under a range of realistic trial settings.

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Stepped wedge trials can be costly and burdensome. Recent work has investigated the iterative removal of cluster-period cells from stepped wedge designs, producing a series of candidate incomplete designs that are less burdensome. We propose a novel way to explore the space of incomplete stepped wedge designs, by considering their cost efficiency, seeking to identify designs that retain high power while limiting the total trial cost.

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Background: Frailty is highly prevalent in older people with chronic kidney disease (CKD) and associated with more complex healthcare needs. As part of person-centred care, healthcare planning should be tailored to the individual's needs and their desired outcomes. Comprehensive Geriatric Assessment (CGA) is an intervention which can help facilitate this by identifying a person's medical, functional, and psychosocial problems, and then tailoring a coordinated, targeted management plan.

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Background: Guidance exists to inform the content of statistical analysis plans in clinical trials. Though not explicitly stated, this guidance is generally focused on clinical trials in which the randomization units are individual patients and not groups of patients. There are critical considerations for the analysis of cluster randomized trials, such as accounting for clustering, the risk of imbalances between the arms due to post-randomization recruitment, and the need to use small sample corrections when the number of clusters is small.

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The stepped wedge design is an appealing longitudinal cluster randomised trial design. However, it places a large burden on participating clusters by requiring all clusters to collect data in all periods of the trial. The staircase design may be a desirable alternative: treatment sequences consist of a limited number of measurement periods before and after the implementation of the intervention.

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Objectives: The interrupted time series (ITS) design is commonly used to investigate the impact of an intervention or exposure in public health. There are many statistical methods that can be used to analyse ITS data and to meta-analyse their results. We undertook two empirical studies to investigate: (i) how effect estimates (and associated statistics) compared when six statistical methods were applied to 190 real-world datasets; and (ii) how meta-analysis effect estimates (and associated statistics) compared when the combinations of two ITS analysis methods and five meta-analysis methods were applied to 17 real-world meta-analyses including 283 ITS datasets.

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This article presents the CONSORT (consolidated standards of reporting trials) extension for cluster randomised crossover trials. A cluster randomised crossover trial involves randomisation of groups of individuals (known as clusters) to different sequences of interventions over time. The design has gained popularity in settings where cluster randomisation is required because it can largely overcome the loss in power due to clustering in parallel cluster trials.

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Background: Simulation is an important tool for assessing the performance of statistical methods for the analysis of data and for the planning of studies. While methods are available for the simulation of correlated binary random variables, all have significant practical limitations for simulating outcomes from longitudinal cluster randomised trial designs, such as the cluster randomised crossover and the stepped wedge trial designs. For these trial designs as the number of observations in each cluster increases these methods either become computationally infeasible or their range of allowable correlations rapidly shrinks to zero.

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Dung beetles provide a variety of ecosystem services in both natural and farmed landscapes. Amongst these services, reductions in the abundance of the free-living stages of pests and parasites that develop in faeces is considered to be of great importance. There is evidence from Australia that enhanced dung beetle populations can reduce populations of pest fly species, particularly the bush fly, however, there is little empirical evidence for reductions in the incidence and impact of nematode parasitism in grazing ruminants.

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Introduction: Despite universal access to government-funded direct-acting antivirals (DAAs) in 2016, the rate of hepatitis C treatment uptake in Australia has declined substantially. Most hepatitis C is related to injecting drug use; reducing the hepatitis C burden among people who inject drugs (PWID) is, therefore, paramount to reach hepatitis C elimination targets. Increasing DAA uptake by PWID is important for interrupting transmission and reducing incidence, as well as reducing morbidity and mortality and improving quality of life of PWID and meeting Australia's hepatitis C elimination targets.

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Linear mixed models are commonly used in analyzing stepped-wedge cluster randomized trials. A key consideration for analyzing a stepped-wedge cluster randomized trial is accounting for the potentially complex correlation structure, which can be achieved by specifying random-effects. The simplest random effects structure is random intercept but more complex structures such as random cluster-by-period, discrete-time decay, and more recently, the random intervention structure, have been proposed.

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Randomized controlled trials can be used to generate evidence on the efficacy and safety of new treatments in eating disorders research. Many of the trials previously conducted in this area have been deemed to be of low quality, in part due to a number of practical constraints. This article provides an overview of established and more innovative clinical trial designs, accompanied by pertinent examples, to highlight how design choices can enhance flexibility and improve efficiency of both resource allocation and participant involvement.

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Background: The Interrupted Time Series (ITS) is a robust design for evaluating public health and policy interventions or exposures when randomisation may be infeasible. Several statistical methods are available for the analysis and meta-analysis of ITS studies. We sought to empirically compare available methods when applied to real-world ITS data.

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This article introduces the 'staircase' design, derived from the zigzag pattern of steps along the diagonal of a stepped wedge design schematic where clusters switch from control to intervention conditions. Unlike a complete stepped wedge design where all participating clusters must collect and provide data for the entire trial duration, clusters in a staircase design are only required to be involved and collect data for a limited number of pre- and post-switch periods. This could alleviate some of the burden on participating clusters, encouraging involvement in the trial and reducing the likelihood of attrition.

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Interrupted time series (ITS) are often meta-analysed to inform public health and policy decisions but examination of the statistical methods for ITS analysis and meta-analysis in this context is limited. We simulated meta-analyses of ITS studies with continuous outcome data, analysed the studies using segmented linear regression with two estimation methods [ordinary least squares (OLS) and restricted maximum likelihood (REML)], and meta-analysed the immediate level- and slope-change effect estimates using fixed-effect and (multiple) random-effects meta-analysis methods. Simulation design parameters included varying series length; magnitude of lag-1 autocorrelation; magnitude of level- and slope-changes; number of included studies; and, effect size heterogeneity.

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Stepped wedge trials are increasingly adopted because practical constraints necessitate staggered roll-out. While a complete design requires clusters to collect data in all periods, resource and patient-centered considerations may call for an incomplete stepped wedge design to minimize data collection burden. To study incomplete designs, we expand the metric of information content to discrete outcomes.

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A frequently applied assumption in the analysis of data from cluster randomised trials is that the outcomes from all participants within a cluster are equally correlated. That is, the intracluster correlation, which describes the degree of dependence between outcomes from participants in the same cluster, is the same for each pair of participants in a cluster. However, recent work has discussed the importance of allowing for this correlation to decay as the time between the measurement of participants in a cluster increases.

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Background: Standard stepped wedge trials, where clusters switch from the control to the intervention condition in a staggered manner, can be costly and burdensome. Recent work has shown that the amount of information contributed by each cluster in each period differs, with some cluster-periods contributing a relatively small amount of information. We investigate the patterns of the information content of cluster-period cells upon iterative removal of low-information cells, assuming a model for continuous outcomes with constant cluster-period size, categorical time period effects, and exchangeable and discrete-time decay intracluster correlation structures.

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In a randomized controlled trial, outcomes of different subjects may be independent at baseline, but correlated at a follow-up measurement due to treatment. This treatment-related clustering at follow-up can arise for instance because the treatment is given in a group or because subjects are treated individually but by the same therapist (therapist effect). There is substantial literature on the design and analysis of such trials when estimation of the intervention effect is based on a follow-up measurement (eg, directly after treatment or at a later time point).

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Background: Whether prehospital administration of tranexamic acid increases the likelihood of survival with a favorable functional outcome among patients with major trauma and suspected trauma-induced coagulopathy who are being treated in advanced trauma systems is uncertain.

Methods: We randomly assigned adults with major trauma who were at risk for trauma-induced coagulopathy to receive tranexamic acid (administered intravenously as a bolus dose of 1 g before hospital admission, followed by a 1-g infusion over a period of 8 hours after arrival at the hospital) or matched placebo. The primary outcome was survival with a favorable functional outcome at 6 months after injury, as assessed with the use of the Glasgow Outcome Scale-Extended (GOS-E).

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Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis.

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Objectives: To assess the mental health and wellbeing of health and aged care workers in Australia during the second and third years of the coronavirus disease 2019 (COVID-19) pandemic, overall and by occupation group.

Design, Setting, Participants: Longitudinal cohort study of health and aged care workers (ambulance, hospitals, primary care, residential aged care) in Victoria: May-July 2021 (survey 1), October-December 2021 (survey 2), and May-June 2022 (survey 3).

Main Outcome Measures: Proportions of respondents (adjusted for age, gender, socio-economic status) reporting moderate to severe symptoms of depression (Patient Health Questionnaire-9, PHQ-9), anxiety (Generalized Anxiety Disorder scale, GAD-7), or post-traumatic stress (Impact of Event Scale-6, IES-6), burnout (abbreviated Maslach Burnout Inventory, aMBI), or high optimism (10-point visual analogue scale); mean scores (adjusted for age, gender, socio-economic status) for wellbeing (Personal Wellbeing Index-Adult, PWI-A) and resilience (Connor Davidson Resilience Scale 2, CD-RISC-2).

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Synopsis of recent research by authors named "Andrew B Forbes"

  • - Andrew B Forbes focuses on advancing methodologies for statistical analysis in clinical research, particularly in the context of cluster randomized trials, emphasizing innovative designs such as staircase and stepped wedge approaches to enhance participant involvement and reduce data collection burdens.
  • - His research explores the ecological role of dung beetles in controlling ruminant parasites, highlighting their potential as biological agents in livestock management, amid a broader exploration of ecosystem services in agricultural landscapes.
  • - Forbes also evaluates statistical methods for meta-analysis in public health studies, comparing techniques for interrupted time series data and assessing the implications of intricate correlation structures in mixed models, aiming to improve the overall robustness of research findings in clinical and environmental health contexts.