Fracture healing is a complex cascade of cellular and molecular processes. These processes require the appropriate cellular and molecular environment to ensure the restoration of skeletal stability and resolution of inflammation. In order for fracture healing to occur, the necessary building blocks for bone metabolism and synthesis must be supplied through proper nutrition. Pharmacologic therapies aimed at modulating the inflammatory response to fractures have the potential to interfere with the synthesis of molecules needed for the production of bone. Infection can interfere with, and even prevent normal fracture healing from occurring. Cellular and genetic treatment strategies are actively being developed to target deficiencies, and bridge gaps that can influence how fractures heal. Evolving technologies, including nutritional supplementation, pharmacotherapies, antibiotics, surgical techniques, as well as genetic and cellular therapies, have the potential to enhance, optimize, and even revolutionize the process of fracture healing.

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 The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation.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.

Introduction

Pragmatic trials in comparative effectiveness research assess the effects of different treatment, therapeutic, or healthcare options in clinical practice. They are characterized by broad eligibility criteria and large sample sizes, which can lead to an unmanageable number of participants, increasing the risk of bias and affecting the integrity of the trial. We describe the development of a sampling strategy tool and its use in the PREPARE trial to circumvent the challenge of unmanageable work flow.

Methods

Given the broad eligibility criteria and high fracture volume at participating clinical sites in the PREPARE trial, a pragmatic sampling strategy was needed. Using data from PREPARE, descriptive statistics were used to describe the use of the sampling strategy across clinical sites. A Chi-square test was performed to explore whether use of the sampling strategy was associated with a reduction in the number of missed eligible patients.

Results

7 of 20 clinical sites (35%) elected to adopt a sampling strategy. There were 1539 patients excluded due to the use of the sampling strategy, which represents 30% of all excluded patients and 20% of all patients screened for participation. Use of the sampling strategy was associated with lower odds of missed eligible patients (297/4545 (6.5%) versus 341/3200 (10.7%) p < 0.001).

Conclusions

Implementing a sampling strategy in the PREPARE trial has helped to limit the number of missed eligible patients. This sampling strategy represents a simple, easy to use tool for managing work flow at clinical sites and maintaining the integrity of a large trial.