Exposure–response modelling approaches for determining optimal dosing rules in children

Within paediatric populations, there may be distinct age groups characterised by different exposure–response relationships. Several regulatory guidance documents have suggested general age groupings. However, it is not clear whether these categorisations will be suitable for all new medicines and in all disease areas. We consider two model-based approaches to quantify how exposure–response model parameters vary over a continuum of ages: Bayesian penalised B-splines and model-based recursive partitioning. We propose an approach for deriving an optimal dosing rule given an estimate of how exposure–response model parameters vary with age. Methods are initially developed for a linear exposure–response model. We perform a simulation study to systematically evaluate how well the various approaches estimate linear exposure–response model parameters and the accuracy of recommended dosing rules. Simulation scenarios are motivated by an application to epilepsy drug development. Results suggest that both bootstrapped model-based recursive partitioning and Bayesian penalised B-splines can estimate underlying changes in linear exposure–response model parameters as well as (and in many scenarios, better than) a comparator linear model adjusting for a categorical age covariate with levels following International Conference on Harmonisation E11 groupings. Furthermore, the Bayesian penalised B-splines approach consistently estimates the intercept and slope more accurately than the bootstrapped model-based recursive partitioning. Finally, approaches are extended to estimate Emax exposure–response models and are illustrated with an example motivated by an in vitro study of cyclosporine

Missing steps in a staircase: a qualitative study of the perspectives of key stakeholders on the use of adaptive designs in confirmatory trials

Background Despite the promising benefits of adaptive designs (ADs), their routine use, especially in confirmatory trials, is lagging behind the prominence given to them in the statistical literature. Much of the previous research to understand barriers and potential facilitators to the use of ADs has been driven from a pharmaceutical drug development perspective, with little focus on trials in the public sector. In this paper, we explore key stakeholders’ experiences, perceptions and views on barriers and facilitators to the use of ADs in publicly funded confirmatory trials. Methods Semi-structured, in-depth interviews of key stakeholders in clinical trials research (CTU directors, funding board and panel members, statisticians, regulators, chief investigators, data monitoring committee members and health economists) were conducted through telephone or face-to-face sessions, predominantly in the UK. We purposively selected participants sequentially to optimise maximum variation in views and experiences. We employed the framework approach to analyse the qualitative data. Results We interviewed 27 participants. We found some of the perceived barriers to be: lack of knowledge and experience coupled with paucity of case studies, lack of applied training, degree of reluctance to use ADs, lack of bridge funding and time to support design work, lack of statistical expertise, some anxiety about the impact of early trial stopping on researchers’ employment contracts, lack of understanding of acceptable scope of ADs and when ADs are appropriate, and statistical and practical complexities. Reluctance to use ADs seemed to be influenced by: therapeutic area, unfamiliarity, concerns about their robustness in decision-making and acceptability of findings to change practice, perceived complexities and proposed type of AD, among others. Conclusions There are still considerable multifaceted, individual and organisational obstacles to be addressed to improve uptake, and successful implementation of ADs when appropriate. Nevertheless, inferred positive change in attitudes and receptiveness towards the appropriate use of ADs by public funders are supportive and are a stepping stone for the future utilisation of ADs by researchers

Hypercapnia augments resistive exercise‐induced elevations in intraocular pressure in older individuals

The present study assessed the effect of 6° head down (establishing the cephalad displacement noted in astronauts in microgravity) prone (simulating the effect on the eye) tilt during rest and exercise (simulating exercise performed by astronauts to mitigate the sarcopenia induced by unloading of weight‐bearing limbs), in normocapnic and hypercapnic conditions (the latter simulating conditions on the International Space Station) on IOP.Volunteers (average age = 57.8 ± 6 yrs.; N = 10) participated in two experimental sessions, each comprising: i) 10‐min rest, ii) 3‐min handgrip dynamometry (30% max), and iii) 2‐min recovery, inspiring either room air (NCAP), or a hypercapnic mixture (1% CO2, HCAP). We measured IOP in the right eye, cardiac output (CO), stroke volume (SV), heart rate (HR) and mean arterial pressure (MAP) at regular intervals. Baseline IOP in the upright seated position while breathing room air was 14.1 ± 2.9 mmHg. Prone 6° HDT significantly (p < 0.01) elevated IOP in all three phases of the NCAP (rest: 27.9 ± 3.7 mmHg; exercise: 32.3 ± 4.9 mmHg; recovery: 29.1 ± 5.8 mmHg) and HCAP (rest: 27.3 ± 4.3 mmHg; exercise: 34.2 ± 6.0 mmHg; recovery: 29.1) trials, with hypercapnia augmenting the exercise‐induced elevation in IOP (p < 0.01). CO, SV, HR and MAP were significantly increased during handgrip dynamometry, but there was no effect of hypercapnia. The observed IOP measured during prone 6°HDT in all phases of the NCAP and HCAP trials exceeded the threshold pressure defining ocular hypertension. The exercise‐induced increase in IOP is exacerbated by hypercapnia

Separate and Combined Effects of Hypoxia and Horizontal Bed Rest on Retinal Blood Vessel Diameters

Citation: Louwies T, Jaki Mekjavic P, Cox B, et al. Separate and combined effects of hypoxia and horizontal bed rest on retinal blood vessel diameters. Invest Ophthalmol Vis Sci. 2016;57:4927-4932. DOI:10.1167/ iovs.16-19968 PURPOSE. To assess the separate and combined effects of exposure to prolonged and sustained recumbency (bed rest) and hypoxia on retinal microcirculation. METHODS. Eleven healthy male subjects (mean 6 SD age ¼ 27 6 6 years; body mass index [BMI] ¼ 23.7 6 3.0 kg m À2 ) participated in a repeated-measures crossover design study comprising three 21-day interventions: normoxic bed rest (NBR; partial pressure of inspired O 2 , P i O 2 ¼ 133.1 6 0.3 mm Hg); hypoxic ambulation (HAMB; P i O 2 ¼ 90.0 6 0.4 mm Hg), and hypoxic bed rest (HBR; P i O 2 ¼ 90.0 6 0.4 mm Hg). Central retinal arteriolar (CRAE) and venular (CRVE) equivalents were measured at baseline and at regular intervals during each 21-day intervention. RESULTS. Normoxic bed rest caused a progressive reduction in CRAE, with the change in CRAE relative to baseline being highest on day 15 (DCRAE ¼ À7.5 lm; 95% confidence interval [CI]: À10.8 to À4.2; P &lt; 0.0001). Hypoxic ambulation resulted in a persistent 21-day increase in CRAE, reaching a maximum on day 4 (DCRAE ¼ 9.4 lm; 95% CI: 6.0-12.7; P &lt; 0.0001). During HBR, the increase in CRAE was highest on day 3 (DCRAE ¼ 4.5 lm; 95% CI: 1.2-7.8; P ¼ 0.007), but CRAE returned to baseline levels thereafter. Central retinal venular equivalent decreased during NBR and increased during HAMB and HBR. The reduction in CRVE during NBR was highest on day 1 (DCRVE ¼ À7.9 lm; 95 CI: À13.3 to À2.5), and the maximum DCRVE during HAMB (24.6 lm; 95% CI: 18.9-30.3) and HBR (15.2 lm; 95% CI: 9.8-20.5) was observed on days 10 and 3, respectively. CONCLUSIONS. The diameters of retinal blood vessels exhibited a dynamic response to hypoxia and bed rest, such that retinal vasodilation was smaller during combined bed rest and hypoxia than during hypoxic exposure

Point estimation for adaptive trial designs II: practical considerations and guidance

In adaptive clinical trials, the conventional end-of-trial point estimate of a treatment effect is prone to bias, that is, a systematic tendency to deviate from its true value. As stated in recent FDA guidance on adaptive designs, it is desirable to report estimates of treatment effects that reduce or remove this bias. However, it may be unclear which of the available estimators are preferable, and their use remains rare in practice. This article is the second in a two-part series that studies the issue of bias in point estimation for adaptive trials. Part I provided a methodological review of approaches to remove or reduce the potential bias in point estimation for adaptive designs. In part II, we discuss how bias can affect standard estimators and assess the negative impact this can have. We review current practice for reporting point estimates and illustrate the computation of different estimators using a real adaptive trial example (including code), which we use as a basis for a simulation study. We show that while on average the values of these estimators can be similar, for a particular trial realization they can give noticeably different values for the estimated treatment effect. Finally, we propose guidelines for researchers around the choice of estimators and the reporting of estimates following an adaptive design. The issue of bias should be considered throughout the whole lifecycle of an adaptive design, with the estimation strategy prespecified in the statistical analysis plan. When available, unbiased or bias-reduced estimates are to be preferred

Confidence intervals for adaptive trial designs I: a methodological review

Regulatory guidance notes the need for caution in the interpretation of confidence intervals (CIs) constructed during and after an adaptive clinical trial. Conventional CIs of the treatment effects are prone to undercoverage (as well as other undesirable properties) in many adaptive designs (ADs) because they do not take into account the potential and realized trial adaptations. This paper is the first in a two-part series that explores CIs for adaptive trials. It provides a comprehensive review of the methods to construct CIs for ADs, while the second paper illustrates how to implement these in practice and proposes a set of guidelines for trial statisticians. We describe several classes of techniques for constructing CIs for adaptive clinical trials before providing a systematic literature review of available methods, classified by the type of AD. As part of this, we assess, through a proposed traffic light system, which of several desirable features of CIs (such as achieving nominal coverage and consistency with the hypothesis test decision) each of these methods holds

Confidence Intervals for Adaptive Trial Designs II: Case Study and Practical Guidance

In adaptive clinical trials, the conventional confidence interval (CI) for a treatment effect is prone to undesirable properties such as undercoverage and potential inconsistency with the final hypothesis testing decision. Accordingly, as is stated in recent regulatory guidance on adaptive designs, there is the need for caution in the interpretation of CIs constructed during and after an adaptive clinical trial. However, it may be unclear which of the available CIs in the literature are preferable. This paper is the second in a two-part series that explores CIs for adaptive trials. Part I provided a methodological review of approaches to construct CIs for adaptive designs. In this paper (Part II), we present an extended case study based around a two-stage group sequential trial, including a comprehensive simulation study of the proposed CIs for this setting. This facilitates an expanded description of considerations around what makes for an effective CI procedure following an adaptive trial. We show that the CIs can have notably different properties. Finally, we propose a set of guidelines for researchers around the choice of CIs and the reporting of CIs following an adaptive design