Welcome to the deprescribing.org blog’s first literature roundup. For these pieces, we’ll be taking a closer look at recently published studies on deprescribing. Here we go!
STOPPFrail (we love it when tools are tested in clinical practice)
Many of us likely saw the RCT “Deprescribing in Older People Approaching End of Life: A Randomized Controlled Trial Using STOPPFrail Criteria” published in JAGS a few weeks ago.
The authors tested whether the STOPPFrail tool had an effect on the number of regular medications patients were taking compared to those receiving usual care. The study population was older patients with limited life expectancy who were being discharged from acute care to nursing homes.
It’s encouraging to see a deprescribing tool actually being tested in clinical practice since that doesn’t tend to happen for many of the tools out there. Such testing provides much-needed assurance that the tools we use are likely to be helpful for deprescribing. It’s also nice when the intervention and implementation of the tool are described in enough detail to allow us to replicate the intervention in our own settings (as they are in this RCT if you look into the useful supplementary material).
What is even more encouraging to see is that STOPPFrail led to the use of fewer medications compared to usual care (the mean difference was around 2 less medications at 3 months), and subsequently led to a 30% reduction in monthly medication costs.
A closer look
There are a few small things to keep in mind from this trial. Yes, this tool was tested in clinical practice. To us, it is still a little unclear whether your average healthcare provider can expect to see the similar effects from STOPPFrail in their practice, and whether the results translate to other settings.
As is often the case with deprescribing trials (and as the authors point out themselves), the intervention was implemented by one of the study authors who was unblinded to group allocation. One other thing to consider is that the STOPPFrail tool was originally developed by the university affiliated with the two hospitals involved in the study. Impressively, the deprescribing recommendations were accepted by attending physicians in 88% of cases. Since this is an explicit tool, there may not be as much concern here regarding variability in how the tool gets applied by different providers or in different settings. However, the tool was implemented in what may have been a particularly motivated group of (de-) prescribers, which is important to keep in mind.
We thought about whether three months was a bit short for follow-up. This is mainly because we know that medications often get represcribed, and that new ones get added in nursing home. Since we are dealing with a group with limited life expectancy, that may not be as much of a concern here. But there are likely still a lot of people in such a group surviving beyond 3 months and it would be helpful to see whether the reductions in medication use are sustained.
It’s good to put this trial into the context of what we already know about STOPPFrail.
Use of STOPPFrail by itself to identify deprescribing targets has been shown to have moderate agreement compared to a geriatrician-led “gold standard” deprescribing process involving a medication review. Further, there is good agreement between geriatricians, GPs, and palliative care physicians when using STOPPFrail.
When we consider this in the context of the RCT results, we have to acknowledge that STOPPFrail is probably among the most rigorously tested deprescribing tools out there.
In other words, we can likely feel pretty good about using STOPPFrail in practice.
Whether a tool like STOPPFrail should be used on its own is an important consideration. In our minds, these kinds of tools are still best used as points of reference throughout a deprescribing process that incorporates an implicit approach (and possibly other tools!) rather than being used alone. Such a tool needs to be applied in individual patient contexts and employed with clinical judgement.
We spoke with the lead author of the study, Dr. Denis Curtin, who offered some great additional points on this matter, and about the value of STOPPFrail:
“STOPPFrail, because it is an explicit tool, is not a catch-all for potentially inappropriate medications. It is a decision aid designed for physicians who do not have expertise in pharmacotherapy. For older people with advanced frailty, deprescribing is likely to be part of a care plan which involves providing end-of-life support and managing distressing symptoms. The real value of an explicit tool, like STOPPFrail, is that it enables the general practitioner, the oncologist, the cardiologist -in other words, the patient’s doctor – to make clinically sound deprescribing decisions.”
Going beyond medication numbers?
It’s great to see that the STOPPFrail RCT examined patient-important outcomes such as quality of life and hospital admissions. As the authors point out, it was, however, underpowered to detect any differences here. This seems to be the case for most deprescribing trials. They are powered to reduce number of medicines, not to show effects on patient outcomes. While tools and interventions are effective in terms of reducing medication numbers and improving medication appropriateness, we still don’t have much evidence on the effect of deprescribing on other outcomes important to the patients.
As Dr. Curtin points out, a reduction in medication use with no change in outcomes is still a good thing: “I completely agree that we need to go beyond medication numbers. It may, however, not be necessary to demonstrate a difference in outcomes. Deprescribing involves the withdrawal of a medical intervention. Therefore, simply showing that patients are no worse off will be enough to justify the process.”
This is a great point, and we definitely agree. But we also think about the central goal of deprescribing, which is to improve patient outcomes. Perhaps the focus in deprescribing trials needs to shift.
So, we have been asking ourselves this question: what about powering our deprescribing trials to detect differences in these kinds of outcomes?
It is nice, but perhaps not so surprising, that most of the deprescribing interventions we are testing lead to less medication use. So, are we now at the point where we need to start going beyond medication numbers as the primary outcome in deprescribing trials?
Photo by Kimberly Farmer on Unsplash
The deprescribing blog is hosted by pharmacists and PhD students, Carina Lundby and Wade Thompson. We hope to be your new best deprescribing friends and supply you with deprescribing content and analysis on a biweekly basis. Please reach out to us if you have any questions or comments, or would like to contribute.
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