Sylvia Syvenky went for a routine dental appointment in early October, expecting to have two caps on her teeth replaced, but something went terribly wrong. She was rushed by ambulance to University Hospital near her home in Edmonton, Alberta, where doctors placed a mask on her face and forced air into her lungs,The New York Times writes. They told her she had heart failure.
And after her condition improved, they asked her to sign up for a study of a new drug to help with breathing. Syvenky is like many with heart failure who arrive at hospitals, unable to breathe. Yet she is the last person who would normally be asked to join a research study, the Times notes, adding that, at age 70, she was much older than typical study participants and her symptoms were too complex.
But now there is a growing movement to gather a new kind of evidence to fill in some of the biggest gaps in medical science: What treatment is best for typical patients with complex symptoms? Many are elderly with several chronic conditions and taking several unrelated meds. And, the Times asks, what are the long-term effects, such as death rates, side effects and disease progression?
A group of advocates, including medical researchers, medical societies and insurers, is lobbying Congress to pay for an Institute for Comparative Effectiveness Research that would assess treatments and identify gaps in evidence, the Times reports. When there are gaps, the institute would initiate what are being called “real world,” or “pragmatic,” clinical research trials to gather the evidence.
Some leading researchers who used to defend the status quo say they have switched. “There has been a 90-degree turn” in thinking, Eugene Braunwald, an eminent cardiologist at Harvard Medical School, tells the Times. “I personally have swung around.”
Although thousands of medical studies are completed every year, most have relatively limited goals. They often carefully select patients who have few medical problems other than the one under study, making it easier to get one clear result, the Times notes, adding that studies may not look at effects over the long term, assuming that if a treatment helps initially, patients will be better off.
But while such studies can help a drug acquire approval or answer a restricted research question, they may not tell how a new drug will work once it is tried in real patients with complex problems. Such limited studies, while they can have value, may no longer be enough, particularly when care has become so expensive and real evidence more crucial.
“They are at the heart of why we have trouble making decisions,” Scott Ramsey, a professor of medicine at the University of Washington, tells the Times.
The FDA does not have a specific rule about what it takes to show that a drug is effective, according to Bob Temple, director for medical policy at the FDA’s Center for Drug Evaluation and Research. A lot depends on what is known about a drug’s short-term effects and how well it can predict long-term outcomes. But there are practical concerns with large trials because drugmakers have to look at a wide range of possible effects when they test a drug. “If you do a large outcome study in 10,000 people in the same way you do short-term studies, you’ll never finish,” Temple tells the Times.
“There’s no white hat, black hat here,” Kevin Weiss, president and chief executive of the American Board of Medical Examiners, tells the paper. “Pharmaceutical companies are trying to do what they are supposed to do. The FDA is trying to do what it is supposed to do. But they are not fully connected to what the public needs.”
5 Comments
This makes so much more sense than half the "targeted" clincal studies being done by most companies. When looking across a broad range of complicating symptoms make so much more sense.
Compliance Analyst:
You have to keep in mind that when you attempt to generate increased external validity (a "real world" approach that is applicable to the general population), you do so by sacrificing internal validity (the ability for an experiment to accurately measure what you're attempting to measure).
This is a problem with science, generally, not just the medical sciences. The more you control an experiment, the less "real world" that experiment becomes and the more detached and artificial the results. The less you control an experiment, the less you know what you're really measuring.
As a counter point to your statement, some argue that medical studies are messy enough as they are currently carried out. Perhaps what we need is a better general understanding of how to control medical experiments--and incentives for conducting unlikely experiments (e.g. head to head studies, non-biased pharmacoeconomic analyses, long-term studies in properly powered sub-populations, etc.).
This is a complex area, however there are things that should have already been done.
For example, in clinical practice patients are placed on antidepressants for 6 months, even with a first episode. This is not considered long term treatment for prevention of a second episode. Yet when there was a proposal for FDA to extend the requirement for antidepressant studies from 3 months to 6 months drug companies and the Key Opinion Leaders who consult for them got the proposed requirement killed.
Safety is another big issue. Current ICH requirements are 500 subjects at ANY clinically used dose for 6 months and 100 subjects for 1 year and was implemented around the time Phen-Fen and Zyprexa was under development. This could definitely be increased. In addition there is no reason why these subjects could not continue to be studied as it takes approximately 18 months from the completion of phase III studies until a drug is approved.
Thus even if you have 100 subjects at 1 year at filing you might have several hundred at 1 year by the time of approval and another couple of hundred on the drug for up to 2.5 - 3 years. It's not perfect but it's a lot better than we have now.
Salmon
A very substantial part of this problem would be solved if clinical records were being properly analyzed. The FDA has a mandate to start completing this process with a goal of having over 100 million patient records being analyzed (I think within 10 years although I could be wrong on the timing). The entire point of this process is to allow for "real world" analysis without the need to establish trials which, by definition, cease to be "real world" as soon as they are set up.
Of course, the question will arise as to who should be completing the analysis of these data. i suggest that this should be the true role of the proposed Institute for Comparative Effectiveness Research. It is only through the analysis of millions of records, examined with true longitudinal integrity, that we will be able to arrive at reliable results for the multitude of relevant subsets. In effect everyone becomes an observed trial participant without having to undergo any modification to their treatment, location of care or anything else. It also allows for proper analysis of different doctor behavior without creating a false environment within a trial.
The only problem is that those proposing the ICER are already salivating at the thought of the huge budgets that will be involved. The alternative idea is to take the proposals already around for the use of EMRs as standard, feed the anonymized data into an analytical capability and derive real knowledge from real behavior instead of pseudo-knowledge from "controlled" trials.
I agree Michael, but do some of the clinical studies only point where you want them to? When you add external factors into experiments, it changes the outcome. It almost seems equivalent of doing animal behavior studies on a captive vs. wild animal. I am just saying the idea behind doing clinical studies that bring in some of those external "real world" examples is not a bad idea.