Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT05131685 |
Other study ID # |
2021-4883 |
Secondary ID |
|
Status |
Recruiting |
Phase |
N/A
|
First received |
|
Last updated |
|
Start date |
February 16, 2022 |
Est. completion date |
September 2028 |
Study information
Verified date |
May 2024 |
Source |
Ann & Robert H Lurie Children's Hospital of Chicago |
Contact |
Jamie Burgess, PhD |
Phone |
312-227-6531 |
Email |
jburgess[@]luriechildrens.org |
Is FDA regulated |
No |
Health authority |
|
Study type |
Interventional
|
Clinical Trial Summary
This protocol describes a multicenter, prospective randomized superiority trial comparing
functional outcomes between children treated with sedated reduction versus no formal
reduction.
Description:
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 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.