Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

An amendment to this paper has been published and can be accessed via the original article

Sex differences in the association between neck circumference and asthma.

INTRODUCTION: The association between obesity and asthma control/quality of life commonly relies on body mass index (BMI) as the anthropomorphic measure. Due to limitations of BMI and the existence of alternative measures, such as neck circumference (NC), we examined the association between NC and asthma control/quality of life, with particular attention to male–female differences MATERIALS AND METHODS: The AsthMaP-2 Project is an observational study of youth with physician–diagnosed asthma. NC was stratified according to age- and sex-specific cutoffs and associated with asthma control (via Asthma Control Test [ACT]) and quality of life (via Integrated Therapeutics Group [ITG]—Asthma Short Form) RESULTS: The mean±SD age was 11.9±3.6 years, and 53% were male (N=116). The mean BMI percentile was at the 71±28 percentile. Thirty-one participants (27%) met criteria for high NC. Males with high NC had significantly worse asthma control (P =0.02) and lower quality of life than those with low NC. No similar association was found for females and the proportion of variability in ACTand ITG was best explained by BMI percentile. Conversely, for males, the proportion of variability in these scores explained by NC was larger than BMI percentile alone (Cohen’s f(2) =0.04–0.09, a small to medium effect size) DISCUSSION: Among male youth with asthma, combined use of NC and BMI percentile explained asthma control and quality of life better than BMI alone. Future studies of asthma should include measurement of NC and other anthropogenic measures of regional adiposity to clarify sex differences in asthma

Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials

Introduction: Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent. Methods: The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have. Results: Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation. Discussion: Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal