| Literature DB >> 25125365 |
Frederik Keus1, Iwan C C van der Horst, Maarten W Nijsten.
Abstract
BACKGROUND: Today's clinical research faces challenges such as a lack of clinical equipoise between treatment arms, reluctance in randomizing for multiple treatments simultaneously, inability to address interactions and increasingly restricted resources. Furthermore, many trials are biased by extensive exclusion criteria, relatively small sample size and less appropriate outcome measures.Entities:
Mesh:
Year: 2014 PMID: 25125365 PMCID: PMC4141104 DOI: 10.1186/1756-0500-7-530
Source DB: PubMed Journal: BMC Res Notes ISSN: 1756-0500
Figure 1Multiplex communication principle. In communications technology and in other fields multiplexing is used to combine multiple independent packages of information into a continuous single signal that after transmission can be decomposed into the original information packages.
Figure 2Conventional versus multiplex trial design. In most conventional randomized controlled trials, the effect of only one intervention is examined. Multiple questions are typically addressed in a serial manner. Thus in the first trial patients 1-1000 are studied to compare red and brown treatments, in the second trial patients 1200 -1600 (green vs. dark green) the third trial patients 1800-2000 (yellow vs. orange) and in the fourth trial patients 2200-3200 (light blue vs. dark blue). The different numbers of included patients result from different power requirements. The gaps in included patients are related with logistical issues. Within the multiplex trial concept as many questions as possible are addressed simultaneously, provided clinical equipoise exists between all treatments (and their combinations) that are examined. For example the three different subtrials may examine the two interventions for blood pressure, pain and fever respectively in patient 2000 through 4000. Although the subtrials use more patients and thus have greater power, a lower overall number of patients is required, underscoring the efficiency of factorial trial design. The continuous nature of the multiplex design also reduces “down-time” (as indicated by the breaks between the four convential trials). Interactions between treatments can only reliably be detected with a factorial design, although the needed sample size to do so requires advanced analysis.
Key elements, requirements and additional benefits of multiplex trial design
| Key elements | |
|---|---|
| A Clinical equipoise between treatment arms | |
| B Factorial design allows simultaneous participation in multiple subtrials | |
| C Continuous design so subtrials are embedded in a permanent infrastructure | |
| D Broad inclusion criteria | |
| E Relevant and robust outcome measures according to GRADE | |
| F Large sample sizes | |
|
| |
| Treatment arms reflect current practice (A) | |
| Increased involvement of patients (B) | |
| Streamlined consent procedure for multiple subtrials (B) | |
| Multiple principal investigators must closely collaborate (B) | |
| Mutual acceptance of multiple sponsors (B) | |
| Extensive involvement of institutional review board (A,B,C) | |
| Integration with existing outcome registries (C,E,F) | |
| Advanced ICT infrastructure (B,C) | |
|
| |
| Patients | More confidence in clinical research (A,B,E) |
| Scientific | Detection of interactions (B) |
| Results with low risks of bias (A,D,E,F) | |
| Results with low risks of random error (A,D,E,F) | |
| Higher external validity (C,D,F) | |
| Societal | More answers to relevant clinical questions (B,C,D,E,F) |
| More efficient use of resources (B,C,D) | |
Summary of the components of the multiplex concept (A through F) and the various requirements as well as further benefits that we foresee that are related with these components.