I recently saw a Twitter post mentioning "Micro-Randomized Study Design Example - Maryland Alcohol-Dependent Moms Abstinence (MAMA) Study" and found the term 'micro-randomization' interesting and prompted me to compare the concept of randomization, re-randomization, and micro-randomization. Based on the number of times that a subject can be randomized in a study, we can differentiate the studies as randomized, re-randomized, and micro-randomized trials.
Randomization is the process of assigning subjects (patients, clinical trial participants) by chance to groups that receive different treatments. In the simplest trial design (parallel-group design), the investigational group receives the new treatment and the control group receives standard therapy. At several points during and at the end of the clinical trial, researchers compare the groups to see which treatment is more effective or has fewer side effects. Randomization helps prevent bias. Bias occurs when a trial's results are affected by human choices or other factors not related to the treatment being tested.
ICH Topic E 9Statistical Principles for Clinical Trials has an entire section discussing randomization as the key design technique to avoid biases:
"2.3.2 Randomisation
Randomisation introduces a deliberate element of chance into the assignment of treatments to subjects in a clinical trial. During subsequent analysis of the trial data, it provides a sound statistical basis for the quantitative evaluation of the evidence relating to treatment effects. It also tends to produce treatment groups in which the distributions of prognostic factors, known and unknown, are similar. In combination with blinding, randomisation helps to avoid possible bias in the selection and allocation of subjects arising from the predictability of treatment assignments.
The randomisation schedule of a clinical trial documents the random allocation of treatments to subjects. In the simplest situation it is a sequential list of treatments (or treatment sequences in a crossover trial) or corresponding codes by subject number. The logistics of some trials, such as those with a screening phase, may make matters more complicated, but the unique pre-planned assignment of treatment, or treatment sequence, to subject should be clear. Different trial designs will require different procedures for generating randomisation schedules. The randomisation schedule should be reproducible (if the need arises).
......"
In typical clinical trials, the study participants will be randomized only one time whether to different treatments or different treatment sequences. For clinical trials with parallel-group design, subjects are randomized to receive one of two or more treatments. For clinical trials with cross-over design, subjects are randomized to follow one of two or more treatment sequences. Once the treatment sequence is determined, subjects will follow the sequence to receive multiple treatments (for example, treatment A then treatment B or treatment B than treatment A,...)
The vast majority of randomized clinical trials are falling into this category and this includes:
- randomized double-blind trials: randomization + blinding
- randomized open-label trials: randomization without blinding
- randomized cross-over trials: randomization to the sequence of treatments
- adaptive randomized trials: adjust the randomization ratio
- "N of 1" clinical trials: can be considered as a high order crossover, once the sequence is decided, the treatments at various stages are decided
re-randomization in SMART trial design framework - SMART stands for Sequential Multiple Assignment Randomized Trial. In a trial with SMART designs, the same subject may be randomized more than once depending on the response to the initial assigned treatment after the initial randomization. According to the paper by Kidwell et al "Sequential, Multiple Assignment, Randomized Trial Designs in Immuno-oncology Research", A SMART is a multistage, randomized trial in which each stage corresponds to an important treatment decision point. Participants are enrolled in a SMART and followed throughout the trial, but each participant may be randomized more than once. Subsequent randomizations allow for unbiased comparisons of post-initial randomization treatments and comparisons of treatment pathways. The goal of a SMART is to develop and find evidence of effective treatment pathways that mimic clinical practice.
In a review paper by Wallace at el "SMART Thinking: a Review of Recent Developments in Sequential Multiple Assignment Randomized Trials", the following general diagram was given for SMART design:
We saw that SMART design with re-randomization was used in clinical trials in different therapeutic areas:
In a paper by Almirall et al "Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research", the following diagram was used to illustrate a SMART design for weight loss research. After the initial randomized treatment period, the responders and non-responders are identified. The non-responders were re-randomized to different treatments.
Ruppert et al described a study with SMART design in CLL "Application of a sequential multiple assignment randomized trial (SMART) design in older patients with chronic lymphocytic leukemia" where patients with complete response after stage 1 were re-randomized to receive two different treatments at stage 2.
We conducted an ICE study - a registration study with IGIV-C in CIDP (a rare neurology disease) "Intravenous immune globulin (10% caprylate chromatography purified) for the treatment of chronic inflammatory demyelinating polyradiculoneuropathy(ICE study): a randomised placebo-controlled trial". We did not explicitly state the SMART design but did employ the re-randomization in the study. The subjects who were responders (to the blinded treatment) were re-randomized to receive either IGIV-C or Placebo in additional six months follow-up period. The re-randomized portion of the study was to compare the relapse rate between two treatment groups - a key secondary efficacy endpoint. With the re-randomized portion of the study, we built in two randomizations in the same study and demonstrated the treatment effect of IGIV-C in the primary efficacy endpoint of improving the responder rate and also the treatment effect of IGIV-C in preventing the relapse in the additional follow-up period - essentially two studies in one. This was used as a rationale for a single pivotal trial (two studies in one) to provide substantial efficacy for effectiveness.
Re-randomization is also discussed for use in different settings where the subjects who complete the initial randomized period are put back to the randomization pool. Subjects were re-randomized to the study as if they are new to the study. In other words, the same subject was re-used and re-randomized into the study. Kahan et al described this type of re-randomized trial as the following:
This type of re-randomized design is very rarely used and may be used in clinical trials with ultra-rare diseases that patient recruitment is extremely challenging.
A Micro-randomized trial (MRTs) can be considered as an extension of the SMART design. The same subject can be randomized and re-randomized many times to different interventions. The time scale is much more frequent and short (for example several times in a day). The term 'micro-' can be confusing, but it is used to differentiate this type of randomization from the classical setting where randomization can not be too frequently. The term 'micro-' is used to describe a setting where the randomization/re-randomization needs to be conducted more frequently on a much short time scale - almost continuous time points. A Micro-randomized trial is good for the interventions that are delivered through mobile devices (such as push notification) and is good for interventions that are intended for changing subjects' behaviors.
Here is a website describing what the micro-randomized trial is:
In micro-randomized trials (MRTs), individuals are randomized hundreds or thousands of times over the course of the study. The goal of these trials is to optimize mobile health interventions by assessing the relative effect of different intervention options and assessing whether the intervention effects vary with time or the individual's current context. With MRTs we can gather data to construct optimized just-in-time adaptive interventions (JITAIs).
Intervention options can include either or both engagement strategies and therapeutic treatments. Consider the Heartsteps MRT (described below) that is designed to promote physical activity among sedentary people. Heartsteps includes phone notifications with tailored activity suggestions to encourage physical activity; these are therapeutic in focus. On the other hand the SARA MRT (also described below) is designed to promote engagement by young adults in substance abuse research. SARA includes rewards for participants who complete assessments; these are engagement strategies. The design of both of these projects can be seen in the “Projects Using MRTs” section, below.
In an MRT, each participant can be randomized many times. For example in the Heartsteps project, the researchers identified five times throughout the day when people are mostly likely to be available to take a brief walk. At each of the five time points, the application randomizes between delivering a phone notification containing a tailored activity suggesion or to not deliver anything; as a result over the course of the 42 days, each participant is randomized 210 times. This sequence of both within-participant and between-participant randomizations comprises the MRT.
The MRT data can then be used to assess the effectiveness of the tailored activity suggestions and to build rules for when to deliver the suggestions in order to help individuals be more active. To do this the application records a variety of outcomes. In this case, the app collects the minute-by-minute step count from the participant’s activity-tracking wristband throughout the day, the participant’s overall level of physical activity, and the participant’s context at each of the 5 times per day (using GPS to determine the person’s location and the local weather). The resulting data is used by researchers to assess the effectiveness of the activity suggestions and to build rules for when and where to deliver the suggestions. In other MRTs, the randomization could apply to what type of intervention to provide, rather than whether or not to provide an intervention. The ultimate goal of Heartsteps is the development of a JITAI that will successfully encourage higher levels of physical activity. The study design of the MRT used in Heartsteps is shown below.
MRTs are an emergent innovation in behavioral science.
We are in the digital era and digital tools will become more used in interventions (especially the adaptive intervention) for lifestyle and behavior changes. However, we don't think that the 'micro-randomized trials' will be suitable for drug trials for registration purposes.
- On this date, there are 16 registries in clinicaltrials.gov using micro-randomized trials. Not surprisely, all micro-randomized trials are in the behavioral science field.
- Xu et al "Multi-Level Micro-Randomized Trial: Detecting the Proximal Effect of Messages on physical activity"
- “Micro-randomized Trials in Mobile Health” with Zhenke Wu, PhD
- Dr. Susan Murphy: Micro-randomized Trials for JITAI Development
No comments:
Post a Comment