Table 1 Challenges and opportunities for clinical trials in critical care

Think Bayesian

Nearly all clinical trials are designed based on frequentist statistics, which yields less information about the probability of benefit and harm than Bayesian statistics

Unfamiliarity with the Bayesian framework and adaptive trial design

Skepticism about the perceived subjectivity of Bayesian prior distributions

Education for clinicians, investigators, and funders

Widespread appreciation for the close analogy between Bayesian statistics and routine clinical reasoning

Adapt when needed

Standard clinical trials employ rigid designs with fixed sample sizes based on educated estimates of event rates and treatment effect

Skepticism about the statistical validity of frequent interim analyses to guide adaptations in design

Methodological expertise in adaptive trial design and Bayesian trial design is not yet widespread

Dissemination of consensus on best practices for the design and conduct of adaptive trials

Successful completion and publication of arms and domains from ongoing adaptive trials

Build a platform

Traditional clinical trials typically build trial infrastructure (funding, regulatory approval, logistics, recruitment, investigator network, analysis, data monitoring committee) to address one research question

Funding is complex: Both the platform infrastructure and the individual interventional research questions require funding support

Authorship criteria can be challenging to establish

Proactive partnerships with funding agencies to support platform infrastructure

Academic community should intentionally place greater value on group authorship

Understand the noise

Some trials are criticized for being too pragmatic and providing fixed interventions regardless of mechanistically relevant physiological or biological characteristics of individual patients

Demonstrating heterogeneity of treatment effect increases sample size requirements

Clinical importance of different mechanistic pathways may not be clear prior to the conduct of the trial

Development and validation of short-term surrogate endpoints reflecting mechanistically relevant treatment response for phase II trials (similar to phase II oncology trials) before evaluation in phase III trials

Use of response-adaptive randomization and other adaptive trial techniques to enhance recognition of differential treatment response among relevant patient subgroups

Be inclusive

Most patients in critical care units are not enrolled in a clinical trial

Many trials do not include patients from resource-constrained settings

Restrictive inclusion and exclusion criteria

Challenges of obtaining informed consent in timely fashion for time-dependent interventions

Create potential incentives to including patients in clinical trials

Consider enrolment in trials as a quality performance marker for healthcare systems

Enhance patient engagement in trial design

Embed discovery within care

Trials employ dedicated electronic case report forms and data coordinating centers

Data entry is often duplicated across multiple interfaces, increasing both workload and errors

Widely accepted dissociation between clinical care and clinical research.  Widespread variability in electronic health record systems

Resource-constrained settings may not have access to electronic health record systems

Algorithms for detecting and reducing missing data are not routinely implemented outside of trials

Partner with healthcare administrators to design trials that contribute to quality and innovation within healthcare systems

Integrate clinical record-keeping with minimum datasets for clinical research

Develop low-cost electronic health record systems for widespread use