Table Of Content
The stepped wedge design is increasingly popular in a wide variety of settings, including public health intervention evaluations and clinical and health service research. Previous studies presenting power calculation methods for stepped wedge designs have focused on continuous outcomes and relied on normal approximations for binary outcomes. Dr. Xin Zhou introduces two new methods, using maximum likelihood and generalized estimating equations, to improve the power calculation for binary outcomes. Dr. Zhou has also developed user-friendly software, including a SAS macro, an R package, and a Shiny app, for power calculations in stepped wedge designs. In this presentation, uses the R package to show how to use the software for power calculations in stepped wedge designs. This presentation explains the unique characteristics of the stepped wedge cluster randomized design and its implications for sample size calculation and analysis, and discusses its strengths and weaknesses compared to traditional designs.
Stepped Wedge Randomized Controlled Trials
A stepped wedge design also allows investigators to examine the way in which the impact of the intervention develops (over time) once it is introduced into a cluster. This might be important where an intervention needs an initial period of adjustment before becoming fully embedded in the setting. In such cases the length of the period (up to the current observation) during which the cluster has been exposed to the intervention can be included in the model as an effect modifier. Adjusting for the systematically different observation periods and for clustering in the data is accomplished by fitting an appropriate generalised linear mixed model or using generalised estimating equations. Interviewees reported that many sites had difficulty contributing data for every time block of the implementation timeline on the specified cardiovascular disease outcome measures. In comparison, a parallel CRT does not require measurements across multiple time blocks and has a shorter time frame.
Epidemiology and study details
The Better Health Outcomes through Mentoring and Assessment (BHOMA) study is an SWT of a health systems strengthening intervention in Zambia, conducted in 42 clusters divided into three districts. There were seven clusters in district A, 14 clusters in district B, and 21 clusters in district C, so at each crossover point one cluster from district A, two from district B, and three from district C crossed over from the control to intervention [18]. As there were six clusters in each group, the stratification of the randomisation of clusters to groups assured balance of districts across the order of rollout.
Table 3
In a closed cohort trial, in particular, this may also imply a high measurement burden on individual participants, and there may be little marginal gain in information from excessively increasing the number of measurements per individual. A schematic of stepped wedge design for the Early Recognition and Response to Increases in Surgical Site Infection (Early 2RIS) Trial. There are 12 randomization sequences (defined by the first time period during which each group of clusters crossover to intervention). In the Early 2RIS trial, the baseline period is one year, and each subsequent period is 3 months.
Authors' contributions
SWT designs where individuals experience both conditions may be a good choice, given constraints and the research question. In our opinion however, researchers should consider the possibility of carry-over effects and other bias a priori, and report these considerations when publishing the results of the trial. There is a wide range of stepped wedge trial designs, and key aspects such as the exposure of individuals and their measurement should be reported more clearly.
David Murray Archives - Rethinking Clinical Trials
David Murray Archives.
Posted: Thu, 19 Oct 2023 04:02:11 GMT [source]
For example, cross-sectional measurement to assess change within a closed cohort (T1/D1/M3) is less sensitive than measuring the same individuals. Researchers planning SWTs must consider a range of design issues, starting with how individuals from within clusters will participate. The design literature makes little distinction between SWTs where individuals are exposed to one condition only, or to both control and intervention conditions. The literature has also not clearly addressed the role of data collected before and/or after the rollout period in the study. The limited range of designs considered has also hampered the growth of terminology to describe the conduct of SWTs, and allow them to be reported in a transparent and consistent way, though others have begun this process [6].
January 3, 2024: Special Biostatistics Series Concludes With Missing Data in Cluster Randomized Trials - Rethinking Clinical Trials
January 3, 2024: Special Biostatistics Series Concludes With Missing Data in Cluster Randomized Trials.
Posted: Wed, 03 Jan 2024 08:00:00 GMT [source]
Analysis
AC led the writing of the text, except the text on randomisation methods which was led by JL. GB and all other authors discussed the content of the paper in meetings, contributed to the text, and suggested edits to earlier drafts. The necessary statistical tools for the planning and evaluation of SWD trials now stand at our disposal. Such trials nevertheless are subject to major risks, as valid results can be obtained only if the far-reaching assumptions of the model are, in fact, justified. The number of individuals is based on recruitment to the trial, rather than completed follow-up numbers.
Defining characteristics of stepped wedge cluster randomised trials, allocation and terminology
There was also the risk that facilitators working across multiple sequences were delivering the intervention to sites that were in the control period. For example, in New York City facilitators continued to visit sites in the control period to deliver other programs that the network leadership was implementing. The Oklahoma cooperative attempted to decrease cross-contamination by strengthening training and quality control. Specifically the attendance of pupils in a term when the intervention is introduced (school breakfasts) is unlikely to be affected by whether a school had exposed pupils to the control condition (no breakfast) for one or two more terms more than in other schools. In case study three, carry-over effects are again unlikely as the control condition is a standard approach that staff will have experienced for a while before the trial, and the outcome is likely to remain stable.
Special methods are needed for analysis and sample size estimation for these studies, as detailed below and in the SWGRT sample size calculator. Aldo’s 5-inch wedges look dangerously steep but are designed with the brand’s Pillow Walk foam padded insoles, along with memory foam to simultaneously absorb impact while comfortably molding to your foot and providing key support in places like your heel and the ball of your foot. The delicate, adjustable ankle strap helps hold your foot in place, so you can actually walk in this pair, too. In SW-CRTs, all sites are introduced to the intervention before their intervention starts, in some cases more than a year in advance. This might lead to the Hawthorne effect, which is when study subjects modify their behavior when made aware that they are being observed. The North Carolina cooperative might have experienced the effect more acutely than others, owing to its institutional policies, which required contracts be signed up front specifying the outcome measures of interest.
In the course of that project, a large-scale vaccination program was implemented in Gambia, for which 17 teams were formed. The aim was to have vaccinated all children against hepatitis B viruses (HBVs) after approximately 4 years. The main reason given for proceeding in this way was logistics, including vaccine availability. Indirect evidence that vaccination effectively reduced HBV infection had already been confirmed before in a number of studies in high-risk groups. According to the authors of the trial, it would be valuable to obtain direct evidence that vaccination reduced the incidence of liver tumors. With respect to this trial, there was also debate as to whether a 4-year traditional parallel-group trial should be conducted instead of the SWD.
The ICC measures the similarity among values on the outcome variable for different members of the same group or cluster within a given time period. It is often described as the average correlation among members within the same group or cluster and within the same time period or as the proportion of variance due to group or cluster membership. The CAC is the correlation between the population means from the same group or cluster at two different time periods; it is sometimes called over-time correlation at the group level. The IAC is the correlation on the outcome variable for the same individual at two different time periods; it is sometimes called over-time correlation at the member level. Four groups of units initiated the intervention at four separate points in time between April 2009 and March 2011.
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