Moving to a New Era of Clinical Trials

Frequently on rounds,  my colleagues argue that we should not do something to a patient since “there is no evidence that it works.”   This phenomenon of avoiding practice that has insufficient clinical trial evidence is often more common among young trainees in academic settings.    The practice of evidence-based medicine inherently involves integrating doctor’s experience, patient preferences and best available research. In an ideal world, every single question would have been tested in a clinical trial; but in reality this is not possible.   In fact, even the majority of recommendations in practice guidelines in cardiovascular disease are not supported by clinical trials.

Even for questions where there is a dire need for clinical trial evidence, such as adding new therapies to current standard of care or expanding or narrowing indications of existing therapies, multiple barriers remain.   Clinical trials are very expensive. In a recent analysis, the median cost of a clinical trial was estimated at 19 million U.S. dollars.   For pivotal cardiovascular disease trials, the numbers are much higher (north of 150 million USD) since those trials have to be larger and for longer duration to detect clinically meaningful outcomes (e.g. heart attack) and to also compare new interventions to current standards of care.   While cost is the biggest barrier, it is not the only one. Finding patients for trials has been a challenge that often leads to long periods of completion or even worse, aborting the trial due to inability to meet enrollment targets.  Even when patient enroll, they can easily lose interest and eventually dropout. Regulatory hurdles around accessing trial data add to the complexity. Even after successful trial completion, extensive inclusion and exclusion criteria_which often enable the trial to prove a positive outcome_ limit our ability to generalize the findings to many patients who do not fit those criteria.

A lot has changed in the world since we started doing randomized clinical trials in the mid 20th century, whether in science, health, technology, media, or even people’s behavior. Yet, we still do our trials the same.  It’s about time to move into a new era of clinical trials by thinking outside the box.  Smaller, smarter trials are possible. Analysis of big data from the real world could help drive hypotheses that we can test in clinical trials. For example in genomics a technique known as  Mendelian randomization uses genetic variation present as birth as a natural experiment to identify a causal relationship between an exposure and disease. Insights from big data could also help identify clusters of patients that are most likely to benefit from a treatment, have higher chance of having the outcome, or higher chance of having the side effect of the treatment, all of which could inform inclusion and exclusion criteria and increase the chance of having a smaller but more informative trial.

Another potential for innovating in design is by recruiting through direct-to-patient approaches. The Apple Heart Study recruited more than 400,000 people in a very short time and showed that this approach is possible. That should also be a coupled with  new approaches in statistical design as well as re-envisioning how we  ascertain outcomes, by capitalizing on the use of technology and patient engagement though ownership of their data. Changes in regulation are necessary to enable those innovations. Finally, despite the fact that clinical trials are so expensive, the value (yield divided by cost) has been low because we traditionally focused only on strong effects on the primary outcome. With appropriate data sharing of patient level data including those for negative trials, so much more could be learned.

As medical and scientific knowledge continues to increase, the cost of an incremental yield to health outcomes from new interventions will exponentially increase. Healthcare providers should be conscious of their practice of evidence-based medicine by always remembering that not all interventions necessarily require the highest level of evidence.  At the same time, we should re-envision our approaches to clinical research using the tools around us in today’s world to generate better evidence at lower cost.