Distal Radius Interventions for Fracture Treatment

INTRODUCTION Distal radius fractures (DRFs) make up 20-25% of all pediatric fractures (Brudvik 2003, Cooper 2004), and are the most common fractures seen in the emergency department in children in the United States. (Naranje 2016) The available evidence on distal radius fracture (DRF) reduction/non-reduction is based on case series, observational comparisons, and expert opinions. Displaced metaphyseal distal radius fracture (DRFs) have historically been treated with attempts at closed reduction (under conscious sedation or anesthesia). This approach was supported by retrospective studies and consensus opinion that anatomical alignment was necessary for normal function.(Rockwood 2010 text, Bae 2012 JPO) Furthermore, it is unsettling for physicians and families to see bones overlapped on a radiograph when a straightening procedure can be completed in a straightforward fashion. However, simple immobilization without attempted reduction has recently been reported for management of DRFs in children under age 10.(Crawford 2012) This approach is conceptually supported by the fracture's proximity to the distal radial physis and the remaining growth of the child, which provides significant remodeling potential and can allow for improvement of malalignment as the child grows.(Crawford 2010 JBJSAm, Price 1990 JPO) There is a paucity of literature comparing reduced to non-reduced fractures to guide management. No established or standardized guidelines exist for the optimal management of completely displaced fractures. Surveys have identified widely discrepant recommendations and high practice variation for treatments for identical DRF patterns.(Georgiadis 2019 POSNA or JPO 2020) Although these studies provide preliminary data to support clinical management, the studies lack a control population for comparison, are retrospective, lack randomization, have variable follow-up times and have no standard definitions of outcomes. In addition, the studies used radiographic or non-validated outcome measures to make conclusions, limiting their utility in identifying optimal management. It appears that children may be undergoing unnecessary procedures, sedations, and anesthetics. The use of anesthesia and sedation has recently come into question as studies examine their effects on cognitive development. (Loepke 2013, Flick 2011) There could be a significant cost savings in terms of procedure costs, hospital costs, and lost time from work if non-procedure management is found to be a non-inferior treatment regimen. The physician investigators want to tell patients that they know why they are proposing treatments, the risks and benefits of the treatment, and use evidence to inform these recommendations and the family's decisions. The proposed trial will compare the effectiveness of alignment under sedation/anesthesia with simple immobilization for management of displaced DRFs in children, providing critical data regarding optimal management of this common fracture. Therefore, this study's primary question is: does anatomic reduction under sedation/anesthesia of DRF result in improved patient outcomes at six months compared to immobilization without attempted reduction? Multiple reasons exist for comparing these treatment strategies for DRF, including: 1) these are the most common treatments for DRF, 2) the strategies are widely divergent (operative vs. non-operative), and 3) there is a large potential to change clinical practice. QUALITY ASSURANCE AND QUALITY CONTROL Quality control (QC) procedures will be implemented beginning with the data entry system and data QC checks that will be run on the database will be generated. Any missing data or data anomalies will be communicated to the site(s) for clarification/resolution. Following written Standard Operating Procedures (SOPs), the monitors will verify that the clinical trial is conducted and data are generated and biological specimens are collected, documented (recorded), and reported in compliance with the protocol, International Conference on Harmonisation Good Clinical Practice (ICH GCP), and applicable regulatory requirements (e.g., Good Laboratory Practices (GLP), Good Manufacturing Practices (GMP)). The investigational site will provide direct access to all trial related sites, source data/documents, and reports for the purpose of monitoring and auditing by the sponsor, and inspection by local and regulatory authorities. For specific details regarding quality assurance and quality control, please see the data management plan. DATA HANDLING AND RECORD KEEPING DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES Data collection is the responsibility of the clinical trial staff at the site under the supervision of the site investigator. The investigator is responsible for ensuring the accuracy, completeness, legibility, and timeliness of the data reported. Clinical data and patient reported outcomes will be entered into REDCap, a 21 CFR Part 11-compliant data capture system provided by the DCRI. The data system includes password protection and internal quality checks, such as automatic range checks, to identify data that appear inconsistent, incomplete, or inaccurate. Clinical data will be entered directly from the source documents. SAFETY OVERSIGHT Safety oversight will be under the direction of a Data and Safety Monitoring Board (DSMB) composed of individuals with the appropriate expertise and knowledge of pediatric orthopaedic surgery usually obtained via an accredited pediatric orthopaedic fellowship. Members of the DSMB should be independent from the study conduct and free of conflict of interest, or measures should be in place to minimize perceived conflict of interest. The DSMB will meet at least semiannually to assess safety data on each arm of the study. The DMSB will operate under the rules of an approved charter that will be written and reviewed at the organizational meeting of the DSMB. At this time, each data element that the DSMB needs to assess will be clearly defined. The DSMB will provide its input to NIAMS. Statistical Hypotheses: • Primary Efficacy Endpoint(s): The null hypothesis is that there is no difference in PROMIS UE (CAT) at 1 year between arms. The alternative hypothesis is that there is a difference between arms. SAMPLE SIZE DETERMINATION Sample size calculations were based on detecting a clinically meaningful difference in the Patient Reported Outcomes Measurement Information System (PROMIS) Upper extremity computer adaptive test (CAT) of 4 points. PROMIS measures use a T-score metric with a mean of 50 and standard deviation of 10 in a reference population. A sample size of 133 per am, assuming a two-sided type I error rate of 0.05, will provide 90% power to detect a difference between arms of 4 points. To conservatively account for 20% lost-to-follow-up or missing data on the primary outcome at 12 months, the investigators have inflated the sample size to 167 per arm, for a total target enrollment of 334. A blinded sample size re-estimation based on the standard deviation of the primary outcome, after 100 participants have completed the 6 month follow-up, will be performed. GENERAL APPROACH Note: Statistical Analyses are described in depth in the Statistical Analysis Plan. Descriptive statistics will summarize all baseline variables by arm. Specifically, continuous variables will be summarized using mean and standard deviation, for normally distributed variables, and median and IQR, for non-normally distributed variables. Categorical variables will be summarized with frequency and percentages. There will be no formal hypothesis testing for comparison of baseline characteristics between treatment arms. Primary analyses of the primary outcome at 1 year will be assessed with a two-sided type I error rate of 0.05 for a MCID of 4 points. A false discovery rate (FDR) correction will be applied to analyses of all secondary outcomes to account for multiplicity. ANALYSIS OF THE PRIMARY EFFICACY ENDPOINT(S) Analysis for the primary aim will utilize a mixed effect model for the primary outcome, PROMIS Upper Extremity Function at 12 months, with a fixed effect for treatment arm and a random effect for site. Fixed effects will also include all variables considered in the randomization (site, sex, age), to control for imbalances in both the design and analysis. Incorporation of a random center effect will allow for separation of between site and within site variance components. Distributional assumptions will be assessed and transformations or inclusions of higher order terms may be considered, as appropriate. ANALYSIS OF THE SECONDARY ENDPOINT(S) Secondary analyses will employ similar methods for all secondary continuous outcomes. A generalized linear mixed effect model with Poisson distribution and log link will be used for the secondary count outcome, number of revisions, refractures, re-reductions, and reoperations. Distributional assumptions will be assessed, and a dichotomous version may be used instead if appropriate (any revisions, refractures, reductions, and reoperations vs never). Descriptive statistics will be used summarize satisfaction survey by treatment arm. Simple non-parametric test statistics or chi-squared test statistics may be used to compare ordinal and binary variables, respectively. Exploratory analyses may also consider trajectories of the primary outcome measured over time. Fixed effects for baseline PROMIS Upper Extremity Function, time, treatment arm, and the interaction will be included in a linear mixed effect model with random patient nested in center effects. A False Discovery Rate (FDR) correction will be applied to all secondary analyses to account for multiplicity.