Troponin I, Troponin T, Troponin is the Woe of Me

As a critical care physician, I have not infrequently been called to the emergency department to admit a patient on the basis of "abnormal laboratory tests" with no synthesis, no assimilation of the various results into any semblance of a unifying diagnosis. It is bad enough that patients' chests are no longer ausculted, respiratory rates and patterns not noted, neck veins not examined, etc. It is worse that the portable chest film (often incorrectly interpreted), the arterial blood gas (also often incorrectly interpteted), and the BNP level have supplanted any sort of logical and systematic approach to diagnosing a patient's problem. If we are going to replace physical examination with BNPs and d-dimers, we should at least insist that practitioners have one iota of familiarity with Bayes' Theorem and pre-test probabilities and the proper interpretation of test results.

Thus I raised at least one brow slightly on August 27th when the NEJM reported two studies of highly sensitive troponin assays for the "early diagnosis of myocardial infarction" (wasn't troponin sensitive enough already? see: http://content.nejm.org/cgi/content/abstract/361/9/858 and http://content.nejm.org/cgi/content/abstract/361/9/868 ). Without commenting on the studies' methodological quality specifically, I will emphasize some pitfalls and caveats related to the adoption of this "advance" in clinical practice, especially that outside of the setting of an appropriately aged person with risk factors who presents to an acute care setting with SYMPTOMS SUGGESTIVE OF MYOCARDIAL INFARCTION.

In such a patient, say a 59 year old male with hypertension, diabetes and a family history of coronary artery disease, who presents to the ED with chest pain, we (and our cardiology colleagues) are justified in having a high degree of confidence in the results of this test based on these and a decade or more of other data. But I suspect that only the MINORITY of cardiac troponin tests at my institution are ordered for that kind of indication. Rather, it is used as a screening test for just about any patient presenting to the ED who is ill enough to warrant admission. And that's where the problem has its roots. Our confidence in the diagnostic accuracy of this test in the APPROPRIATE SETTING (read appropriate clinical pre-test probability) should not extend to other scenarios, but all too often it does, and it makes a real conundrum when it is positive in those other scenarios. Here's why.
Suppose that we have a pregnancy test that is evaluated in women who have had a sexual encounter and who have missed two menstrual periods and it is found to be 99.9% sensitive and 99.9% specific. (I will bracket for now the possibility that you could have a 100% sensitive and/or specific test.) Now suppose that you administer this test to 10,000 MEN. Does a positive test mean that a man is pregnant? Heavens No! He probably has testicular cancer or some other malady. This somewhat silly example is actually quite useful to reinforce the principle that no matter how good a test is, if it is not used appropriately or in the appropriate scenario that the results are likely to be misleading. Likewise, consider this test's use in a woman who has not missed a menstrual cycle - does a negative test mean that she is not pregnant? Perhaps not, since the sensitivity was determined in a population that had missed 2 cycles. If a woman were obviously24 weeks pregnant and the test was negative, what would we think? It is important to bear in mind that these tests are NOT direct tests for the conditions we seek to diagnose, but are tests of ASSOCIATED biological phenomena, and insomuch as our understanding of those phenomena is limited or there is variation in them, the tests are liable to be fallible. A negative test in a woman with a fetus in utero may mean that the sample was mishandled, that the testing reagents were expired, that there is an interfering antibody, etc. Tests are not perfect, and indeed are highly prone to be misleading if not used in the appropriate clinical scenario.

And thus we return to cardiac troponins. In the patients I'm called to admit to the ICU who have sepsis, PE, COPD, pneumonia, respiratory failure, renal failure, metabolic acidosis, a mildly positive troponin which is a COMMON occurrence is almost ALWAYS an epiphenomenon of critical illness rather than an acute myocardial infarction. Moreover, the pursuit of diagnosis via cardiac catheterization or the empiric treatment with antiplatelet agents and anticoagulants almost always is a therapeutic misadventure in these patients who are at much greater risk of bleeding and renal failure via these interventions which are expected to have a much reduced positive utility for them. More often than not, I would just rather not know the results of a troponin test outside the setting of isolated acute chest pain. Other practitioners should be acutely aware of the patient populations in which these tests are performed, and the significant limitations of using these highly sensitive tests in other clinical scenarios.

Troponin Predicts Outcome in Heart Failure - But So What?

In today's NEJM, Peacock and others (http://content.nejm.org/cgi/content/short/358/20/2117 ) report that cardiac troponin is STATISTICALLY associated with hospital mortality in patients with acute decompensated heart failure, and that this association is independent of other predictive variables. Let us assume that we take the results for granted, and that this is an internally and externally valid study with little discernible bias.

In the first paragraph of the discussion, the authors state that "These results suggest that measurement of troponin adds important prognostic information to the initial evaluation of patients with acute decompensated heart failure and should be considered as part of an early assessment of risk."

Really?


The mortality in patients in the lowest quartile of troponin I was 2.0% and that in the highest quartile was 5.3%. If we make the common mistake of comparing things on a relative scale, this is in an impressive difference - in excess of a twofold increase in mortality. But that is like saying that I saved 50% off the price of a Hershey Kiss which costs 5 cents - so I saved 3 cents! As we approach zero, smaller and smaller absolute differences can appear impressive on a relative scale. But health should not be appraised that way. If you are "buying" something, be it health or some other commodity, you shouldn't care about your relative return on your investment, only the absolute return. You have after all, only some absolute quantity of money. Charlie (from the Chocolate Factory) may find 3 cents to be meaningful, but we are not here talking about getting a 3% reduction in mortality - we are talking about predicting for Charlie whether he will have to pay $0.05 for his kiss or $0.02 for it, and even if our prediction is accurate, we do not know how to help him get the discounted kiss - he's either lucky or he's not.

Imagine that you are a patient hospitalized for acute decompensated heart failure. Does it matter to you if your physician comes to you carrying triumphantly the results of your troponin I test and informs you that because it is low, your mortality is 2% rather than 5%? It probably matters very little. It matters even less if your physician is not going to do anything differently given the results of that test. Two percent, 5 percent, it doesn't matter if it can't be changed.

Then there is the cost associated with this test. My hospital charges on the order of $200 for this test. Consider the opportunity costs - what else could that $200 be spent on, in the care of American patients, and perhaps even more importantly in the context of global health and economics? Also consider the value of the test to a patient who might have to pay out of pocket for it - is it worth $200 to discriminate within an in-hospital mortality range of 2-5%?

This study, while meticulously conducted and reported, underscores the important distinction between statistical significance and clinical significance. With the aid of a ginormous patient registry, the authors clearly demonstrated a statistically significant result that is at least mildly interesting from a biological perspective (is it interesting that a failing heart spills some of its contents into the blodstream and that they can be detected by a highly sensitive assay?) But the clinical significance of the findings appears to be negligible, and I worry that this report will encourate the already rampant mindless use of this expensive test which, outside of the context of clinical pre-test probabilities, already serves to misguide care and run up healthcare costs in a substantial proportion of the patients in whom it is ordered.