Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial.

The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease) is a two-arm, multi-centre, randomised controlled trial being run in India and Australia that investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The trial was designed as a Bayesian adaptive sample size trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here, we describe the statistical analysis plan for the trial and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment.Trial registrationClinicalTrials.gov NCT04394117 . Registered on 19 May 2020Clinical Trial Registry of India CTRI/2020/07/026831Version and revisionsVersion 1.0. No revisions.

Personalised treatments for acute whiplash injuries: A pilot study of nested N-of-1 trials in a multiple baseline single-case experimental design.

BACKGROUND: Whiplash associated disorder (WAD), a common and disabling condition, incurs huge burden and costs to Australia. Yet, current treatments for whiplash are not very effective; improved outcomes are urgently needed. Clinical guidelines recommend simple analgesia (paracetamol and non-steroidal anti-inflammatory drugs) but there have been no trials of guideline-recommended drugs. This study will investigate the effectiveness of evidence-based advice (EBA), paracetamol, naproxen, and both paracetamol and naproxen, in reducing daily neck pain and preventing chronic neck pain after whiplash injury. METHODS: This study is a pilot series of multi-cycle, double-blinded, randomised N-of-1 trials, nested in a multiple baseline design. The design will comprise three baselines of 5, 8 or 11 days duration. Post enrolment, participants will be randomly assigned to one of the baselines. Fifteen participants with acute (<2 weeks) Grade II WAD, experiencing at least moderate pain (NRS: ≥ 5/10), and at risk of poor recovery will be recruited from hospitals in Queensland, Australia, and through local physiotherapists. Patients will receive EBA plus a randomised sequence of three cycles of ten day treatment triplets (paracetamol designated as a C phase, naproxen, designated as a D phase, and both paracetamol and naproxen, designated as an E phase). DISCUSSION: We will test the effects of different treatments on the primary outcome of average neck pain intensity collected daily and at 4 and 7 months post-injury. Secondary outcomes, including disability, depression, post-traumatic stress symptoms, pain catastrophizing, and feasibility of study procedures, will also be evaluated. The results of this study will inform a larger trial aiming to strengthen the evidence on EBA and simple analgesics for WAD. TRIAL REGISTRATION: Clinical Trials Primary Registry: Australian and New Zealand Clinical Trials Registry. CLINICAL TRIAL REGISTRATION NUMBER: ACTRN12618001291279. DATE OF REGISTRATION: 31/07/2018. PRIMARY TRIAL SPONSOR: The University of Queensland, Brisbane QLD 4072 Australia. FUNDING: The University of Queensland.

Protocol: Using N-of-1 tests to identify responders to melatonin for sleep disturbance in Parkinson's disease.

BACKGROUND: 40% of Parkinson's Disease (PD) sufferers experience insomnia, impacting health and quality of life for patients and family members, especially carers. There is little evidence that current treatments are effective. OBJECTIVES: To determine the effectiveness of melatonin in reducing insomnia in 44 individuals with PD using N-of-1 trials. To aggregate group data to arrive at population estimates of effectiveness (measured by improvements in PDSS-2) and safety (measured by adverse events) of melatonin in improving insomnia in PD. To assess the feasibility of offering N-of-1 trials for insomnia in PD. METHODOLOGY: Participants will receive either immediate-release melatonin or placebo in random order in 3 paired two-week treatment periods (12 weeks total). Based on their response in a two-week run-in period on 3 mg daily, they will trial either 3 mg or 6 mg. Patients will keep daily sleep diaries and wear a MotionWatch throughout. After the trial patients will discuss their individual report with their doctor, which provides direct feedback about effectiveness and safety of melatonin for them. STATISTICAL METHODS: We will analyse N-of-1 tests 1) individually: effects of melatonin on PDSS-2 and safety will be reported; and 2) aggregated across individual N-of-1 studies, combined using a Bayesian multilevel random effects model, which will account for repeated measures on individuals over time, and will return posterior estimates of overall treatment effect, and effect in each individual. CLINICAL TRIAL REGISTRATION NUMBER: ACTRN12617001103358.

The oral glucose test predicts laminitis risk in ponies fed a diet high in nonstructural carbohydrates.

The aim of this study was to investigate the relationship between laminitis development in ponies and insulin/glucose concentrations in response to the oral glucose test (OGT) and a dietary challenge high in nonstructural carbohydrates (NSCs). After undergoing an OGT (1 g dextrose/kg BW in feed), 37 ponies with 2-h serum insulin concentrations ranging from 22 to 1,133 µIU/mL were subjected to a diet challenge period (DCP), consuming 12 g NSC/kg BW/d for up to 18 d. Insulin and glucose responses were measured on day 2 of the DCP. Clinical laminitis was diagnosed by blinded experts and confirmed radiographically. Basal ACTH levels and clinical signs were assessed to investigate concurrent putative pituitary pars intermedia dysfunction (PPID). The diet induced Obel grade 1 or 2 laminitis in 14 ponies (38%). The ponies that developed laminitis had higher maximum concentrations of blood glucose (P = 0.04) and serum insulin (P = 0.02) in response to the diet. The geometric mean (95% CI) blood glucose concentration for laminitis cases was 14.9 (12.9-17.2) mM, compared to 10.7 (9.2-12.5) mM for ponies who did not develop laminitis. Similarly, the geometric mean (95% CI) for serum insulin was 396 (301-520) µIU/mL for laminitis cases, compared to 216 (148-316) µIU/mL for ponies who did not develop laminitis. Laminitis incidence was likewise associated with insulin concentrations measured during the OGT. Laminitis occurred at frequencies of 0% (0/7) if postdextrose insulin (µIU/mL) was <50; 35% (8/23) if insulin was 50 to 195; and 86% (6/7) if insulin was >195 µIU/mL. Basal ACTH concentrations were above seasonally accepted reference ranges in 16/37 ponies, and 8 of these animals (50%) developed laminitis. This included all 5 ponies in the study that had clinical signs of PPID (100%). In contrast, hyperinsulinemia and laminitis occurred in only 3/11 ponies (27%) with elevated ACTH concentrations and no clinical signs of PPID (P = 0.009). Thus, laminitis occurrence was associated with higher glucose and insulin responses to both the OGT and challenge diet, and the frequency of laminitis can be predicted based on insulin and glucose hyperresponsiveness to these oral carbohydrate challenges.

Equine hyperinsulinemia: investigation of the enteroinsular axis during insulin dysregulation.

Compared with some other species, insulin dysregulation in equids is poorly understood. However, hyperinsulinemia causes laminitis, a significant and often lethal disease affecting the pedal bone/hoof wall attachment site. Until recently, hyperinsulinemia has been considered a counterregulatory response to insulin resistance (IR), but there is growing evidence to support a gastrointestinal etiology. Incretin hormones released from the proximal intestine, glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide, augment insulin secretion in several species but require investigation in horses. This study investigated peripheral and gut-derived factors impacting insulin secretion by comparing the response to intravenous (iv) and oral d-glucose. Oral and iv tests were performed in 22 ponies previously shown to be insulin dysregulated, of which only 15 were classified as IR (iv test). In a more detailed study, nine different ponies received four treatments: d-glucose orally, d-glucose iv, oats, and commercial grain mix. Insulin, glucose, and incretin concentrations were measured before and after each treatment. All nine ponies showed similar iv responses, but five were markedly hyperresponsive to oral d-glucose and four were not. Insulin responsiveness to oral d-glucose was strongly associated with blood glucose concentrations and oral glucose bioavailability, presumably driven by glucose absorption/distribution, as there was no difference in glucose clearance rates. Insulin was also positively associated with the active amide of GLP-1 following d-glucose and grain. This study has confirmed a functional enteroinsular axis in ponies that likely contributes to insulin dysregulation that may predispose them to laminitis. Moreover, iv tests for IR are not reliable predictors of the oral response to dietary nonstructural carbohydrate.

A Bayesian approach for estimating detection times in horses: exploring the pharmacokinetics of a urinary acepromazine metabolite.

We describe the population pharmacokinetics of an acepromazine (ACP) metabolite (2-(1-hydroxyethyl)promazine) (HEPS) in horses for the estimation of likely detection times in plasma and urine. ACP (30 mg) was administered to 12 horses, and blood and urine samples were taken at frequent intervals for chemical analysis. A bayesian hierarchical model was fitted to describe concentration-time data and cumulative urine amounts for HEPS. The metabolite HEPS was modelled separately from the parent ACP as the half-life of the parent was considerably less than that of the metabolite. The clearance (Cl/F(PM)) and volume of distribution (V/F(PM)), scaled by the fraction of parent converted to metabolite, were estimated as 769 L/h and 6874 L, respectively. For a typical horse in the study, after receiving 30 mg of ACP, the upper limit of the detection time was 35 h in plasma and 100 h in urine, assuming an arbitrary limit of detection of 1 lg/L and a small (≈0.01) probability of detection. The model derived allowed the probability of detection to be estimated at the population level. This analysis was conducted on data collected from only 12 horses, but we assume that this is representative of the wider population.

A sequential Monte Carlo approach to derive sampling times and windows for population pharmacokinetic studies.

Here we present a sequential Monte Carlo approach that can be used to find optimal designs. Our focus is on the design of population pharmacokinetic studies where the derivation of sampling windows is required, along with the optimal sampling schedule. The search is conducted via a particle filter which traverses a sequence of target distributions artificially constructed via an annealed utility. The algorithm derives a catalog of highly efficient designs which, not only contain the optimal, but can also be used to derive sampling windows. We demonstrate our approach by designing a hypothetical population pharmacokinetic study, and compare our results with those obtained via a simulation method from the literature.

Simultaneous versus sequential optimal design for pharmacokinetic-pharmacodynamic models with FO and FOCE considerations.

We consider nested multiple response models which are used extensively in the area of pharmacometrics. Given the conditional nature of such models, differences in predicted responses are a consequence of different assumptions about how the models interact. As such, sequential versus simultaneous and First Order (FO) versus First Order Conditional Estimation (FOCE) techniques have been explored in the literature where it was found that the sequential and FO approaches can produce biased results. It is therefore of interest to determine any design consequences between the various methods and approximations. As optimal design for nonlinear mixed effects models is dependent upon initial parameter estimates and an approximation to the expected Fisher information matrix, it is necessary to incorporate any influence of nonlinearity (or parameter-effects curvature) into our exploration. Hence, sequential versus simultaneous design with FO and FOCE considerations are compared under low, typical and high degrees of nonlinearity. Additionally, predicted standard errors of parameters are also compared to empirical estimates formed via a simulation/estimation study in NONMEM. Initially, design theory for nested multiple response models is developed and approaches mentioned above are investigated by considering a pharmacokinetic-pharmacodynamic model found in the literature. We consider design for situations where all responses are continuous and extend this methodology to the case where a response may be a discrete random variable. In particular, for a binary response pharmacodynamic model, it is conjectured that such responses will offer little information about all parameters and hence a sequential optimization, in the form of product design optimality, may yield near optimal designs.

Compound optimal design criteria for nonlinear models.

Three approaches for combining parameter estimation with opposing design criteria are proposed for nonlinear models. The first method discussed is the technique found in the literature and as such is the reference method for this paper. The compound crtierion is formed by maximizing a weighted product of efficiencies. The second criterion involves maximizing an opposing criterion while minimizing a defined loss function. The third method simultaneously maximizes both efficiencies with respect to parameter estimation and an opposing criterion with a multiple objective simulated annealing algorithm. The examples presented are based on a PK-model and a generalized linear model found in the literature.

Optimal designs for studying bioimpedance.

D-optimal designs for nonlinear fixed and mixed effects models are explored, and the theory is applied to the measurement and analysis of bioelectrical impedance. Bioimpedance is known to vary more at extreme frequencies than others. D-optimal designs that account for this variation, and also possible mis-specification of initial parameter estimates, are considered in an attempt to find designs that will provide good parameter estimates in practice.