Modelling the impacts of pasture contamination and stocking rate for the development of targeted selective treatment strategies for Ostertagia ostertagi infection in calves

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Stocking rate effect on design of targeted selective treatments (TST) was evaluated.

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Initial pasture contamination effect on the design of TST was evaluated.

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Different phenotypic traits and methods of selection for treatment were addressed.

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Benefit was assessed as weight gain/frequency of resistant alleles in helminths.

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Treatment according to threshold triggers of average daily gain was most beneficial.

A simulation study was carried out to assess whether variation in pasture contamination or stocking rate impact upon the optimal design of targeted selective treatment (TST) strategies. Two methods of TST implementation were considered: 1) treatment of a fixed percentage of a herd according to a given phenotypic trait, or 2) treatment of individuals that exceeded a threshold value for a given phenotypic trait. Four phenotypic traits, on which to base treatment were considered: 1) average daily bodyweight gain, 2) faecal egg count, 3) plasma pepsinogen, or 4) random selection. Each implementation method (fixed percentage or threshold treatment) and determinant criteria (phenotypic trait) was assessed in terms of benefit per R (BPR), the ratio of average benefit in weight gain to change in frequency of resistance alleles R (relative to an untreated population). The impact of pasture contamination on optimal TST strategy design was investigated by setting the initial pasture contamination to 100, 200 or 500 O. ostertagi L3/kg DM herbage; stocking rate was investigated at a low (3calves/ha), conventional (5 calves/ha) or high (7 calves/ha) stocking rates. When treating a fixed percentage of the herd, treatments according to plasma pepsinogen or random selection were identified as the most beneficial (i.e. resulted in the greatest BPR) for all levels of initial pasture contamination and all stocking rates. Conversely when treatments were administered according to threshold values ADG was most beneficial, and was identified as the best TST strategy (i.e. resulted in the greatest overall BPR) for all levels of initial pasture contamination and all stocking rates.

Short communication: Genetic and nongenetic factors influencing Ostertagia ostertagi antibodies in UK Holstein-Friesian cattle

The purpose of this study was to estimate and discuss the genetic variation, heritability, and effects of nongenetic factors on the ability of Holstein-Friesian cows to produce an immune response by producing IgG antibodies to Ostertagia ostertagi. Total IgG (IgG(1) and IgG(2)) antibody levels were determined using an ELISA and measured using optical density ratio (ODR=OD(sample) - OD(negative control)/OD(positive control) - OD(negative control)) from milk samples collected from 1,276 Holstein-Friesian cattle in 229 commercial dairy farms from 2002 to 2004 during their first (82%) and other (2 to 12) lactations. A sire (n=461) model was fitted to the ODR data using ASREML software, and variance components were estimated. The ability to produce O. ostertagi antibodies as measured by ODR had a heritability of 0.13+/-0.12, and both season of sample and herd had a significant effect on total IgG levels. To conclude, this study has ascertained that genetic variation is present in the ability of dairy cows to mount an immune response to the parasite O. ostertagi. Inasmuch as evidence exists that IgG is linked to protective immunity against the parasite via a reduction in its reproductive ability, this trait may be of potential interest to genetic selection programs as an aid to reduce the effect of O. ostertagi in dairy herds.

Information content of stepped wedge designs with unequal cluster-period sizes in linear mixed models: Informing incomplete designs

In practice, stepped wedge trials frequently include clusters of differing sizes. However, investigations into the theoretical aspects of stepped wedge designs have, until recently, typically assumed equal numbers of subjects in each cluster and in each period. The information content of the cluster-period cells, clusters, and periods of stepped wedge designs has previously been investigated assuming equal cluster-period sizes, and has shown that incomplete stepped wedge designs may be efficient alternatives to the full stepped wedge. How this changes when cluster-period sizes are not equal is unknown, and we investigate this here. Working within the linear mixed model framework, we show that the information contributed by design components (clusters, sequences, and periods) does depend on the sizes of each cluster-period. Using a particular trial that assessed the impact of an individual education intervention on log-length of stay in rehabilitation units, we demonstrate how strongly the efficiency of incomplete designs depends on which cells are excluded: smaller incomplete designs may be more powerful than alternative incomplete designs that include a greater total number of participants. This also serves to demonstrate how the pattern of information content can be used to inform a set of incomplete designs to be considered as alternatives to the complete stepped wedge design. Our theoretical results for the information content can be extended to a broad class of longitudinal (ie, multiple period) cluster randomized trial designs.

Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

Background: Systematic reviews are used to inform healthcare decision making. In reviews that aim to examine the effects of organisational, policy change or public health interventions, or exposures, evidence from interrupted time series (ITS) studies may be included. A core component of many systematic reviews is meta-analysis, which is the statistical synthesis of results across studies. There is currently a lack of guidance informing the choice of meta-analysis methods for combining results from ITS studies, and there have been no studies examining the meta-analysis methods used in practice. This study therefore aims to describe current meta-analysis methods used in a cohort of reviews of ITS studies. Methods: We will identify the 100 most recent reviews (published between 1 January 2000 and 11 October 2019) that include meta-analyses of ITS studies from a search of eight electronic databases covering several disciplines (public health, psychology, education, economics). Study selection will be undertaken independently by two authors. Data extraction will be undertaken by one author, and for a random sample of the reviews, two authors. From eligible reviews we will extract details at the review level including discipline, type of interruption and any tools used to assess the risk of bias / methodological quality of included ITS studies; at the meta-analytic level we will extract type of outcome, effect measure(s), meta-analytic methods, and any methods used to re-analyse the individual ITS studies. Descriptive statistics will be used to summarise the data. Conclusions: This review will describe the methods used to meta-analyse results from ITS studies. Results from this review will inform future methods research examining how different meta-analysis methods perform, and ultimately, the development of guidance.

How well do doctors know their patients with severe asthma?

BACKGROUND

Rates of asthma mortality have fallen in Australia since the commencement of the National Asthma Campaign and promotion of the Australian asthma management plan. New strategies are now needed to further reduce mortality.

AIM

To examine agreement about key features between asthma patients and their general practitioners (GPs).

METHODS

We interviewed: (i) the next of kin of 56 asthma deaths, (ii) 91 asthma patients presenting to emergency departments with acute severe asthma and (iii) 147 of their GPs.

RESULTS

Agreement was substantial for usage of oral symptomatic medication, but poor for inhaled symptomatic and preventive medications. There was moderate agreement regarding hospital admissions within the last 12 months among the cases, but little about other markers of severity. There was moderate agreement where the presenting or fatal attack was triggered by an upper respiratory-tract infection or aspirin. The next of kin and GPs agreed about family problems, but not about other psychosocial issues. They also agreed about which cases had been given action plans or verbal instructions, but few other aspects of asthma management. There was also moderate agreement regarding the use of peak flow meters by the controls.

CONCLUSIONS

Doctors often have relatively poor insights into self-management practices, social background or trigger factors, even in high-risk patients. This should be considered when planning future campaigns to improve asthma management and further reduce mortality.

The staircase cluster randomised trial design: A pragmatic alternative to the stepped wedge

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. Staircase designs are already being implemented, although in the absence of a dedicated methodology, approaches to sample size and power calculations have been inconsistent. We provide expressions for the variance of the treatment effect estimator when a linear mixed model for an outcome is assumed for the analysis of staircase designs in order to enable appropriate sample size and power calculations. These include explicit variance expressions for basic staircase designs with one pre- and one post-switch measurement period. We show how the variance of the treatment effect estimator is related to key design parameters and demonstrate power calculations for examples based on a real trial.

Is antibiotic treatment effective in the management of chronic low back pain with disc herniation? Study protocol for a randomised controlled trial

Background

There has been immense interest and debate regarding the effectiveness of antibiotic treatment for chronic low back pain. Two randomised controlled trials have examined the efficacy of antibiotics for chronic low back pain with disc herniation and Modic changes, but have reported conflicting results. The aim of this double-blind, randomised, placebo-controlled trial is to determine the efficacy of antibiotic treatment in a broader patient subgroup of chronic low back pain with disc herniation and investigate whether the presence of Modic changes predicts response to antibiotic therapy.

Methods

One hundred and seventy individuals with chronic low back pain will be recruited through hospital and private medical and allied health clinics; advertising in national, community and social media; and posting of flyers in community locations. They will be randomly allocated to receive either amoxicillin-clavulanate (500 mg/125 mg) twice per day for 90 days or placebo. The primary outcome measure of pain intensity will be assessed using the Low Back Pain Rating scale and a 100-mm visual analogue scale at 12 months. Secondary measures of self-reported low back disability and work absence and hindrance will also be examined, and an economic analysis will be conducted. Intention-to-treat analyses will be performed.

Discussion

There is uncertainty about whether antibiotic treatment is effective for chronic low back pain and, if effective, which patient subgroup is most likely to respond. We will conduct a clinical trial to investigate the efficacy of antibiotics compared with placebo in individuals with chronic low back pain and a disc herniation. Our findings will provide high-quality evidence to assist in answering these questions.

Trial registration

Australian New Zealand Clinical Trials Registry ACTRN12615000958583. Registered on 11 September 2015

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-021-05728-1.

Inference for the treatment effect in longitudinal cluster randomized trials when treatment effect heterogeneity is ignored

In cluster-randomized trials, sometimes the effect of the intervention being studied differs between clusters, commonly referred to as treatment effect heterogeneity. In the analysis of stepped wedge and cluster-randomized crossover trials, it is possible to include terms in outcome regression models to allow for such treatment effect heterogeneity yet this is not frequently considered. Outside of some simulation studies of specific cases where the outcome is binary, the impact of failing to include terms for treatment effect heterogeneity on the variance of the treatment effect estimator is unknown. We analytically examine the impact of failing to include terms for treatment effect heterogeneity on the variance of the treatment effect estimator, when outcomes are continuous. Using analysis of variance and feasible generalized least squares we provide expressions for this variance. For both the cluster-randomized crossover design and the stepped wedge design, our analytic derivations indicate that failing to include treatment effect heterogeneity results in the estimates for variance of the treatment effect that are too small, leading to inflation of type I error rates. We therefore recommend assessing the sensitivity of sample size calculations and conclusions drawn from the analysis of cluster randomized trials to the inclusion of treatment effect heterogeneity.

Impact of the duration of control of cattle lice with eprinomectin on leather quality

The relationship between lice infestation in calves during their first winter and damage to the leather produced was investigated in a trial involving 500 calves, 100 of which were treated with a pour-on endectocide during the first winter. All the calves received routine lice treatment in the second winter and were reared to slaughter weight. The hides were removed at the abattoir, tanned, inspected for lice-related damage, and graded according to their suitability for the production of high quality leather. The untreated group developed natural infestations of the chewing louse (Bovicola bovis) during the first winter but none was observed in the second winter. Hides from cattle infested with lice in their first winter had higher levels of lice damage than hides from those treated with eprinomectin, at both the chrome-tanned and dried dyed-crust stages of leather production.

Evaluation of statistical methods used to meta-analyse results from interrupted time series studies: A simulation study

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. All meta-analysis methods yielded unbiased estimates of the interruption effects. All random effects meta-analysis methods yielded coverage close to the nominal level, irrespective of the ITS analysis method used and other design parameters. However, heterogeneity was frequently overestimated in scenarios where the ITS study standard errors were underestimated, which occurred for short series or when the ITS analysis method did not appropriately account for autocorrelation. The performance of meta-analysis methods depends on the design and analysis of the included ITS studies. Although all random effects methods performed well in terms of coverage, irrespective of the ITS analysis method, we recommend the use of effect estimates calculated from ITS methods that adjust for autocorrelation when possible. Doing so will likely to lead to more accurate estimates of the heterogeneity variance.

Evaluating the performance of Bayesian and restricted maximum likelihood estimation for stepped wedge cluster randomized trials with a small number of clusters

Background

Stepped wedge trials are an appealing and potentially powerful cluster randomized trial design. However, they are frequently implemented with a small number of clusters. Standard analysis methods for these trials such as a linear mixed model with estimation via maximum likelihood or restricted maximum likelihood (REML) rely on asymptotic properties and have been shown to yield inflated type I error when applied to studies with a small number of clusters. Small-sample methods such as the Kenward-Roger approximation in combination with REML can potentially improve estimation of the fixed effects such as the treatment effect. A Bayesian approach may also be promising for such multilevel models but has not yet seen much application in cluster randomized trials.

Methods

We conducted a simulation study comparing the performance of REML with and without a Kenward-Roger approximation to a Bayesian approach using weakly informative prior distributions on the intracluster correlation parameters. We considered a continuous outcome and a range of stepped wedge trial configurations with between 4 and 40 clusters. To assess method performance we calculated bias and mean squared error for the treatment effect and correlation parameters and the coverage of 95% confidence/credible intervals and relative percent error in model-based standard error for the treatment effect.

Results

Both REML with a Kenward-Roger standard error and degrees of freedom correction and the Bayesian method performed similarly well for the estimation of the treatment effect, while intracluster correlation parameter estimates obtained via the Bayesian method were less variable than REML estimates with different relative levels of bias.

Conclusions

The use of REML with a Kenward-Roger approximation may be sufficient for the analysis of stepped wedge cluster randomized trials with a small number of clusters. However, a Bayesian approach with weakly informative prior distributions on the intracluster correlation parameters offers a viable alternative, particularly when there is interest in the probability-based inferences permitted within this paradigm.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12874-022-01550-8).

Comparison of the time required to administer three different fluke and worm combination products to commercial beef cattle at housing

Larger livestock units, a decline in the farm labor force, animal welfare concerns, and a trend toward more selective use of drugs have increased the focus on animal handling, time management, convenience, and compliance in administering veterinary therapeutics. This study was undertaken to quantify and compare the time needed to treat commercial beef cattle with three fluke and worm combination products with different administration profiles. Young beef cattle (n = 270) weighing approximately 400 kg were allocated to batches of five, which were randomly assigned to receive ivermectin + clorsulon injection, ivermectin + closantel injection, or levamisole + triclabendazole oral drench. The mean time needed to administer ivermectin + clorsulon (single injection) to five cattle was 31 seconds, which was significantly less than the 100 seconds needed for ivermectin + closantel (two injections) and the 126 seconds needed for levamisole + triclabendazole (P < .001). Such quantitative data can allow for better planning and selection of parasiticide treatment approaches at the farm level.

Methods used to meta-analyse results from interrupted time series studies: A methodological systematic review protocol

Background: Systematic reviews are used to inform healthcare decision making. In reviews that aim to examine the effects of organisational, policy change or public health interventions, or exposures, evidence from interrupted time series (ITS) studies may be included. A core component of many systematic reviews is meta-analysis, which is the statistical synthesis of results across studies. There is currently a lack of guidance informing the choice of meta-analysis methods for combining results from ITS studies, and there have been no studies examining the meta-analysis methods used in practice. This study therefore aims to describe current meta-analysis methods used in a cohort of reviews of ITS studies. Methods: We will identify 100 reviews that include meta-analyses of ITS studies from a search of eight electronic databases covering several disciplines (public health, psychology, education, economics). Study selection will be undertaken independently by two authors. Data extraction will be undertaken by one author, and for a random sample of the reviews, two authors. From eligible reviews we will extract details at the review level including discipline and type of interruption; at the meta-analytic level we will extract type of outcome, effect measure(s), meta-analytic methods, and any methods used to re-analyse the individual ITS studies. Descriptive statistics will be used to summarise the data. Conclusions: This review will describe the methods used to meta-analyse results from ITS studies. Results from this review will inform future methods research examining how different meta-analysis methods perform, and ultimately, the development of guidance.

Effect of atorvastatin on skeletal muscles of patients with knee osteoarthritis: Post-hoc analysis of a randomised controlled trial

Objective

Populations with knee osteoarthritis (KOA) are at increased risk of cardiovascular disease, due to higher prevalence of risk factors including dyslipidaemia, where statins are commonly prescribed. However, the effect of statins on muscles and symptoms in this population is unknown. Thus, this study examined the effect of atorvastatin on muscle properties in patients with symptomatic KOA.

Design

Post-hoc analysis of a 2-year multicentre randomised, double-blind, placebo-controlled trial.

Setting

Australian community.

Participants

Participants aged 40–70 years (mean age 55.7 years, 55.6% female) with KOA who met the American College of Rheumatology clinical criteria received atorvastatin 40 mg daily (n = 151) or placebo (n = 153).

Main outcome measures

Levels of creatinine kinase (CK), aspartate transaminase (AST), and alanine transaminase (ALT) at 1, 6, 12, and 24 months; muscle strength (by dynamometry) at 12 and 24 months; vastus medialis cross-sectional area (CSA) on magnetic resonance imaging at 24 months; and self-reported myalgia.

Results

There were no significant between-group differences in CK and AST at all timespoints. The atorvastatin group had higher ALT than placebo group at 1 (median 26 vs. 21, p = 0.004) and 6 (25 vs. 22, p = 0.007) months without significant between-group differences at 12 and 24 months. Muscle strength increased in both groups at 24 months without between-group differences [mean 8.2 (95% CI 3.5, 12.9) vs. 5.9 (1.3, 10.4), p = 0.49]. Change in vastus medialis CSA at 24 months favoured the atorvastatin group [0.11 (−0.10, 0.31) vs. −0.23 (−0.43, −0.03), p = 0.02] but of uncertain clinical significance. There was a trend for more myalgia in the atorvastatin group (8/151 vs. 2/153, p = 0.06) over 2 years, mostly occurring within 6 months (7/151 vs. 1/153, p = 0.04).

Conclusions

In those with symptomatic KOA, despite a trend for more myalgia, there was no clear evidence of an adverse effect of atorvastatin on muscles, including those most relevant to knee joint health.

The SPICE III study protocol and analysis plan: a randomised trial of early goaldirected sedation compared with standard care in mechanically ventilated patients

BACKGROUND

Sedation strategy in critically ill patients who are mechanically ventilated is influenced by patient-related factors, choice of sedative agent and the intensity or depth of sedation prescribed. The impact of sedation strategy on outcome, in particular when delivered early after initiation of mechanical ventilation, is uncertain.

OBJECTIVES

To present the protocol and analysis plan of a large randomised clinical trial investigating the effect of a sedation strategy, in critically ill patients who are mechanically ventilated, based on a protocol targeting light sedation using dexmedetomidine as the primary sedative, termed "early goal-directed sedation", compared with usual practice.

METHODS

This is a multinational randomised clinical trial in adult intensive care patients expected to require mechanical ventilation for longer than 24 hours. The main exclusion criteria include suspected or proven primary brain pathology or having already been intubated or sedated in an intensive care unit for longer than 12 hours. Randomisation occurs via a secured website with baseline stratification by site and suspected or proven sepsis. The primary outcome is 90-day all-cause mortality. Secondary outcomes include death, institutional dependency, cognitive function and health-related quality of life 180 days after randomisation, as well as deliriumfree, coma-free and ventilation-free days at 28 days after randomisation. A predefined subgroup analysis will also be conducted. Analyses will be on an intention-to-treat basis and in accordance with this pre-specified analysis plan.

CONCLUSION

SPICE III is an ongoing large scale clinical trial. Once completed, it will inform sedation practice in critically ill patients who are ventilated.

Advancing randomized controlled trial methodologies: The place of innovative trial design in eating disorders research

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. Trial designs include individually randomized, cluster randomized, and designs with randomizations at multiple time points and/or addressing several research questions (master protocol studies). Design features include the use of adaptations and considerations for pragmatic or registry-based trials. The appropriate choice of trial design, together with rigorous trial conduct, reporting and analysis, can establish high-quality evidence to advance knowledge in the field. It is anticipated that this article will provide a broad and contemporary introduction to trial designs and will help researchers make informed trial design choices for improved testing of new interventions in eating disorders. PUBLIC SIGNIFICANCE: There is a paucity of high quality randomized controlled trials that have been conducted in eating disorders, highlighting the need to identify where efficiency gains in trial design may be possible to advance the eating disorder research field. We provide an overview of some key trial designs and features which may offer solutions to practical constraints and increase trial efficiency.