Why Has a Run-In Period Been a Design Element in Most Landmark Clinical Trials? Analysis of the Critical Role of Run-In Periods in Drug Development

A proposal from the liver forum for the management of comorbidities in non-alcoholic steatohepatitis therapeutic trials

The current document has been developed by the Liver Forum who mandated the NAFLD-Associated Comorbidities Working Group - a multistakeholder group comprised of experts from academic medicine, industry and patient associations - to identify aspects of diverse comorbidities frequently associated with non-alcoholic steatohepatitis (NASH) that can interfere with the conduct of therapeutic trials and, in particular, impact efficacy and safety results. The objective of this paper is to propose guidance for the management of relevant comorbidities in both candidates and actual participants in NASH therapeutic trials. We relied on specific guidelines from scientific societies, when available, but adapted them to the particulars of NASH trials with the aim of addressing multiple interacting requirements such as maintaining patient safety, reaching holistic therapeutic objectives, minimising confounding effects on efficacy and safety of investigational agents and allowing for trial completion. We divided the field of action into: first, analysis and stabilisation of the patient's condition before inclusion in the trial and, second, management of comorbidities during trial conduct. For the former, we discussed the concept of acceptable vs. optimal control of comorbidities, defined metabolic and ponderal stability prior to randomisation and weighed the pros and cons of a run-in period. For the latter, we analysed non-hepatological comorbid conditions for changes or acute events possibly occurring during the trial, including changes in alcohol consumption, in order to detail when specific interventions are necessary and how best to manage concomitant drug intake in line with methodological constraints. These recommendations are intended to act as a guide for clinical trialists and are open to further refinement when additional data become available.

Perspective: Design and Conduct of Human Nutrition Randomized Controlled Trials

In the field of human nutrition, randomized controlled trials (RCTs) are considered the gold standard for establishing causal relations between exposure to nutrients, foods, or dietary patterns and prespecified outcome measures, such as body composition, biomarkers, or event rates. Evidence-based dietary guidance is frequently derived from systematic reviews and meta-analyses of these RCTs. Each decision made during the design and conduct of human nutrition RCTs will affect the utility and generalizability of the study results. Within the context of limited resources, the goal is to maximize the generalizability of the findings while producing the highest quality data and maintaining the highest levels of ethics and scientific integrity. The aim of this document is to discuss critical aspects of conducting human nutrition RCTs, including considerations for study design (parallel, crossover, factorial, cluster), institutional ethics approval (institutional review boards), recruitment and screening, intervention implementation, adherence and retention assessment, and statistical analyses considerations. Additional topics include distinguishing between efficacy and effectiveness, defining the research question(s), monitoring biomarker and outcome measures, and collecting and archiving data. Addressed are specific aspects of planning and conducting human nutrition RCTs, including types of interventions, inclusion/exclusion criteria, participant burden, randomization and blinding, trial initiation and monitoring, and the analysis plan.

Whole grain food diet slightly reduces cardiovascular risks in obese/overweight adults: a systematic review and meta-analysis

BACKGROUND

The effects of whole grain diet on cardiovascular risks in obese and overweight adults is not well established. Our goal was to conduct a systematic review and meta-analysis on the effect of whole grain diet on cardiovascular risks in obese/overweight adults.

METHODS

PubMed, Embase and Cochrane were systematically scanned for randomized controlled trials (RCTs), and studies were selected based on certain inclusion and exclusion criteria. The primary outcome was the effectiveness of whole grain food consumption in reducing body weight. The secondary outcomes were the effect of whole grain food consumption on cardiovascular disease (CVD) risk factors including plasma low-density lipoprotein cholesterol (LDL-C), insulin resistance index, blood pressure, body mass index (BMI), C-reactive protein (CRP), and waist circumference in obese/overweight adults.

RESULTS

Our results showed that whole grain consumption was associated with lower body weight (mean difference (MD) = - 0.5, 95% confidence intervals (CI) [- 0.74, 0.25], I2 = 35%, P < 0.0001) and lower CRP (MD = -0.36, 95% CI [- 0.54, - 0.18], I2 = 69%, P < 0.0001), compared with the control group. However, there were no significant differences in LDL-C (MD = -0.08, 95% CI [- 0.16, 0.00], I2 = 27%, P = 0.05), waist circumference (MD = -0.12, 95% CI [- 0.92, 0.68], I2 = 44%, P = 0.76), systolic blood pressure (MD = -0.11, 95% CI [- 1.55, 1.33], I2 = 3%, P = 0.88), diastolic blood pressure (MD = -0.44, 95% CI [- 1.44, 0.57], I2 = 15%, P = 0.39), and fasting glucose (MD = -0.05, 95% CI [- 0.12, 0.01], I2 = 31%, P = 0.11) between the two groups.

CONCLUSION

This study suggests that whole grain food consumption can slightly reduce body weight and CRP in obese/overweight population.

Two-period linear mixed effects models to analyze clinical trials with run-in data when the primary outcome is continuous: Applications to Alzheimer's disease

Introduction

Study outcomes can be measured repeatedly based on the clinical trial protocol before randomization during what is known as the “run-in” period. However, it has not been established how best to incorporate run-in data into the primary analysis of the trial.

Methods

We proposed two-period (run-in period and randomization period) linear mixed effects models to simultaneously model the run-in data and the postrandomization data.

Results

Compared with the traditional models, the two-period linear mixed effects models can increase the power up to 15% and yield similar power for both unequal randomization and equal randomization.

Discussion

Given that analysis of run-in data using the two-period linear mixed effects models allows more participants (unequal randomization) to be on the active treatment with similar power to that of the equal-randomization trials, it may reduce the dropout by assigning more participants to the active treatment and thus improve the efficiency of AD clinical trials.