The MAMS design aims to maximise the efficiency of testing treatments. It offers flexible features, including:
MAMS trials have been successful in improving treatments for cancer and infectious diseases.
Below, there is a selection of clinical trials that implemented our MAMS design framework:
|Trial name||Disease area|
|WHO-RED trial||Postpartum haemorrhage|
We are extending the underlying methodology of the MAMS design to increase its efficiency and broaden its application to more disease areas.
Some of our recent and ongoing work on the extension of the MAMS methodology are as follows:
Factorial designs and MAMS platform designs have many advantages. Factorial designs can improve the efficiency of RCTs by allowing two or more randomised evaluations independently in the same sample of patients without a substantial increase in sample size; they can also allow testing for interactions or synergy between interventions. MAMS platform designs improve efficiency by allowing for dropping (or adding) new experimental interventions during the course of a trial.
The combined factorial-MAMS design allows the testing of multiple primary research hypotheses, which will lead to faster decisions about experimental treatments.
The main features of the combined design include:
In a MAMS design, all the experimental interventions reach the final stage if they pass the interim lack-of-benefit stopping boundaries. As a result, the number of experimental interventions in each stage is not pre-determined, so there can be large variations in the final sample size. In some MAMS designs, particularly those with a large number of interventions the maximum sample size might be too large either to achieve or for any funding agency to fund it.
The following figure shows seven surgical interventions (B-H) in the ROSSINI 2 MAMS selection trial that are compared against the control arm A.
In MAMS selection designs, the maximum number of experimental interventions that will be taken to each stage is pre-specified, alongside a criterion for selecting them: for example, based on ranking a combination of efficacy and safety results. Traditionally, the selection of the most promising treatments has been made in phase II trials where the strict control of operating characteristics is not a particular concern. Here our goal is to select the most promising treatments with a high probability of correct selection in the phase III setting where strong control of the error rates is required.
Different disease areas use different types of outcome measures. The MAMS design was originally developed for settings where both the intermediate and definitive outcome measures are time-to-event, as these are prominent in the initial applications in specific cancer types – ovarian and prostate cancer.
We are developing the MAMS design to allow for different combinations of outcome measures, the so-called generic MAMS design. The generic MAMS design allows any type of intermediate and definitive outcome. This will make use of all available data and will make the efficiency of the MAMS approach more widely available.
To share our experience of the MAMS design, we have developed several resources including software updates, papers, book chapters, and tutorials. We also run MAMS courses periodically, and we provide advice on MAMS design through the "MAMS clinic".
Our MRC CTU at UCL Symposium "Innovative phase III randomised clinical trial designs" took place in June 2023 and it covered trial designs that have successfully been used to address multiple research questions (e.g. MAMS, MAMS-ROCI, PRACTical).
The next courses will be advertised on the UCL-ICTM website.
We have recorded several workshop tutorials covering different aspects of MAMS platform trials - introduction, motivation, analysis, etc. They are available in the link below.
You can watch a tutorial on nstage examples in the link below.
We have developed the nstage software for the MAMS settings.
For the latest update, please contact email@example.com.
We run the “MAMS clinic”, an advisory service on how to optimise the design, implementation, and analysis of your multi-arm multi-stage (MAMS) randomised platform trial.