INTRODUCTION

Fractures of the medial epicondyle are a common pediatric injury, with an estimated annualdence of 40-60/100,000 per year. The typical mechanism is a fall onto an outstretched hand, creating a valgus load at the elbow leading to avulsion of the epicondyle from pull ofher the flexor-pronator mass or ulnar collateral ligament. This injury is most frequent inhildren between the ages of 9 and 14, and is 4 times more likely in boys. Medial epicondyleures are associated with elbow dislocation in about 50% of cases, and ulnar nerve dysfunction is reported to occur nearly 10% of the time. No standard of care for medialdyle fractures exists, as similar outcomes have been demonstrated in observationaludies with both operative and nonoperative treatment. Historically, most treatment has beenurgical, with immobilization of the injured elbow in a long-arm cast until healing.gly, however, these injuries are being treated with surgical intervention, which ingle screw affixing the bony piece back to its donor site on the humerus.

No prospective studies have previously been performed evaluating the treatment of medialdyle fractures in children. All of the current literature on this issue has serioushodological limitations, such as lack of appropriate controls, retrospective assembly ofhorts, unstandardized assessment of outcomes, and irregular assessment of negative outcomesd adverse events. A 2009 systematic review of the literature identified 14 studies in whichbetween operative and nonoperative treatment of medial epicondyle fractures inhildren or adolescents was performed. Of these, all were retrospective and observational inure, with varying outcome measures utilized in the presentation of results.

There is considerable debate among clinicians as to the optimal management of medialdyle fractures, however, despite the lack of clear evidence of benefit, increasinglyhese injuries are being managed operatively. Explanations for the trend toward surgery focushe athletic demands of children and adolescents, and the expectations of patients,d coaches of early mobilization and return to sport. Because of the ongoing uncertainty as to best practice, a randomized trial is both ethical and indicated. High-quality data is necessary to better inform the decision regarding surgery and ensure both safe and effective treatment.

SAFETY OVERSIGHT

Safety oversight will be under the direction of a Data and Safety Monitoring Board (DSMB)d of individuals with the appropriate expertise and knowledge of pediatric orthopaedicurgery 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, orures should be in place to minimize perceived conflict of interest. The DSMB will meet atually 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 theganizational meeting of the DSMB. At this time, each data element that the DSMB needs towill be clearly defined. The DSMB will provide its input to NIAMS.

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 datawill be communicated to the site(s) for clarification/resolution.

Following written Standard Operating Procedures (SOPs), the monitors will verify that theducted and data are generated and biological specimens are collected, documented (recorded), and reported in compliance with the protocol, International ConferenceHarmonisation 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, andby local and regulatory authorities.

DATA HANDLING AND RECORD KEEPING

DATA COLLECTION AND MANAGEMENT RESPONSIBILITIES

Data collection is the responsibility of the clinical trial staff at the site under theupervision of the site investigator. The investigator is responsible for ensuring theuracy, 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 passwordd internal quality checks, such as automatic range checks, to identify data thaturate. Clinical data will be entered directly fromhe source documents.

STATISTICAL HYPOTHESES

• Primary Efficacy Endpoint(s):

The trial will employ a superiority framework. Specifically, the null hypothesis is thathere is no difference in PROMIS UE (CAT) at 1 year between arms. The alternative hypothesishat 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 computerdaptive test (CAT) of 4 points. PROMIS measures use a T-score metric with a mean of 50 anddard deviation of 10 in a reference population. A sample size of 133 per am, assuming awo-sided type I error rate of 0.05, will provide 90% power to detect a difference between.

To account for 20% lost-to-follow-up or missing data on the primary outcome at 12 months, we have inflated our 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,50% of participants have completed the 6-month follow-up, will be performed.

POPULATIONS FOR ANALYSES

Primary analyses will be based on an Intention-to-treat (ITT) principle. A per-protocolysis will be performed to assess the robustness of the ITT analysis. In the event of(<5%) missing outcome data, primary analyses will be based on complete cases,g a modified intent-to-treat analysis (mITT).

STATISTICAL ANALYSES

GENERAL APPROACH

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 testingbaseline characteristics between treatment arms.

Primary analyses of the primary outcome at 1 year will be assessed with a two-sided type I.05. A false discovery rate (FDR) correction will be applied to analyses ofdary 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 6 months, with a fixed effect for treatment arm and adom effect for site. Fixed effects will also include variables considered in thedomization (elbow dislocation status, age, sex) 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 bed, and transformations or inclusions of higher order terms may be considered, as.

ANALYSIS OF THE SECONDARY ENDPOINT(S)

Secondary analyses will employ similar methods for all secondary continuous outcomes. Generalized linear mixed modeling approaches will be used for secondary binary and countutcomes, with appropriate link and distributional assumptions. All models will incorporate adom center effect and fixed effects for additional covariate considered in randomization,described above.

Exploratory analyses may also consider trajectories of the primary outcome measured over. Fixed effects for baseline PROMIS Upper Extremity Function, time, treatment arm, andhe interaction will be included in a linear mixed effect model with random patient nested in.

A False Discovery Rate (FDR) correction will be applied to all secondary analyses to accountultiplicity.