1. The formulation of the null hypothesis
2. The definition of the outcomes
3. The flow of patients through the diagnostic algorithm.
Let's see if we can clear some of that confusion.
The intent of the study was to see how adding the CCTA to the usual diagnostic testing in the ED impacted cardiac mortality or a myocardial infarction within 30 days. The null hypothesis was posed in an interesting way:
The study was powered to test the null hypothesis that the rate of major cardiac events among patients who did not have clinically significant coronary artery disease as assessed by CCTA would exceed 1%.This is confusing, and I had to read and reread several times to understand what it meant. I finally realized that what they were saying was that in order to disprove that CCTA is not a useful test (this is the alternative hypothesis) they would have to show that the rates of the primary outcome were not above 1%. Make sense?
The next issue I had trouble with, as I always do in cardiology studies is their choice of endpoints. The primary endpoint was 30-day cardiac death OR MI. This means that anyone who either died of a cardiac cause or had a heart attack within this time period was counted as an event, which would argue against CCTA usefulness if they reached the critical mass of over 1%. Mind you this was limited to those patients whose CCTA did not reveal significant disease. There were some secondary outcomes examined as well, all at the 30-day time point: death, MI, revascularization procedure, and resource utilization. Note these outcomes were not combined, but were examined singly, and the pool of patients for these were all those randomized.
As an aside, cardiology studies frequently use combined outcomes, such as death and MI due to sample size considerations. That is both cardiac death and MI should be rare events in the group examined. When these events are rare, in order to get at their statistical significance exceedingly large sample sizes are needed. For this reason, these trials frequently combine several events, so as to enrich the frequency and commensurately drop the needed sample size.
But here is where it gets a little confusing. Looking at the "Safety" section of the Results, the authors state that no one who received a CCTA had a cardiac death or an MI within the 30-day period. However, 1% of the patients randomized into the CCTA arm did have a MI within 30 days. How can this be? Well, we need to keep in mind that not all those randomized to CCTA (n=908) actually got a CCTA (n=767), and that the majority of those who did have one did NOT have significant coronary disease (n=640). Thus, both the numerator and the denominator for the primary and the secondary outcomes are different.
Then there is this quick sentence in the "Efficiency and Use of Resources" section:
Coronary disease was more likely to be diagnosed in patients in the CCTA group than in patients in the traditional-care group (9.0% vs. 3.5%; difference, 5.6 percentage points; 95% CI, 0 to 11.2).It is almost an afterthought, but it is important. It is puzzling that the outcomes in the two groups are completely identical, and this is not limited to those in the primary endpoint pool, namely people without significant disease. The question arises about what this means. Since there is no difference in cardiac death or MI, this increase in the diagnostic rate may imply overdiagnosis in the group receiving CCTA. There is a slight increase in the revascularization rates in the CCTA group (3%) over the standard care group (1%). This endpoint is much more subjective that most people realize, as a lot of judgment by the cardiologist and the surgeon goes into the decision. So this endpoint does not rule out overdiagnosis as a possibility. On the other hand, the study was not powered to detect a difference in the secondary outcomes, so it may be that the diagnoses are valid, but we do not have enough events to judge.
One final point of frustration with the study reporting was hitting dead ends in the flow of patients through the respective algorithms. I was, of course, looking for the rates of false positive CCTA tests and their outcomes. Unfortunately, I kept getting stuck at the catheterization and stress test steps, not knowing who exactly went on to have this testing. Since in the CCTA out of the 767 tests 47 were indeterminate and 80 were indicative of moderate-to-severe coronary disease, the 37 catheterizations performed were likely among these patients, though we are not told for sure. Of these catheterizations, 9 were negative for a significant stenosis, but again we are not told how this reflects back to the CCTA results. In fairness it is worth noting that fewer people in the CCTA arm (18%) underwent a follow-up test, compared to the standard care arm (62%). But again, this is just one test replacing another, or even being added on top of others. In addition, more of the former group were discharged from the ED (50%) than among the latter (23%) without being admitted.
So what does it all say to me? Well, CCTA seems to aid in the diagnosis of coronary disease among certain people presenting to the ED with chest pain. Given such a low pre-test probability of significant coronary disease (17%, derived by dividing the negative CCTA [640] by the total CCTA tests [767] and subtracting that from 1), I have to wonder about the performance of the test that is quite sensitive but not that specific (high risk of a false positive in a low-risk population). And even though fewer patients needed to be admitted from the ED in the CCTA group, I wonder if this does not have more to do with the differential availability of the testing rather than with its superiority.
Given the context that I laid out above for the results presented, I would not be rushing to adopt CCTA for all patients who present to the ED with a certain type of chest pain. And after all, though a "black swan" event, catastrophes do occur in follow-up catheterization even when the patient is disease-free. This is a good reason to be careful and circumspect in our quest for primum non nocere.
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Excellent analysis of an issue that really needs broad discussion. Do you have any thoughts about why the null hypothesis was framed in such a confusing way, and the analysis was so unclear? I was surprised the NEJM would publish an article structured this way.
ReplyDeleteHi, David, thanks for your comment. I am not sure why they did what they did, or why NEJM reviewers did not ask for clarifications. All I can say is that there is no shortcut to reading these studies ourselves and making judgments based on the study and not the hype. I am hoping that "Between the Lines" will help everyone become much more equipped at least to ask the right questions, if not to deconstruct medical literature per se.
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