New blood tests find heart attacks

A new generation of blood tests can quickly and reliably show if a person is having a heart attack soon after chest pains start — a time when current tests are not definitive, two studies found.

The newer, sensitive tests give a much better way to tell who needs help fast. Each year, 15 million people in the United States and Europe go to emergency rooms with symptoms of a heart attack, but most are not truly suffering one.

Those having a heart attack need to have blocked arteries opened quickly to limit damage to the heart muscle from lack of blood.

Doctors currently have two main ways of diagnosing a heart attack. They can use an electrocardiogram, or EKG, to measure the electrical activity of the heartbeat for abnormalities. But that test is not always conclusive.

Doctors also use blood tests to detect elevated levels of a heart muscle protein known as troponin — a sign of heart muscle injury. A drawback with the older troponin tests is they take longer to detect increased troponin levels and by that time, heart damage may have already occurred.

Two European studies published in Thursday's New England Journal of Medicine found that the newer blood tests can improve early diagnosis of a heart attack soon after a person feels chest pain. The studies looked at four tests made by Abbott Laboratories, Roche and Siemens AG. The Abbott and Siemens tests are approved for use in the United States.

"Until this point, we really did not have direct evidence that they improved overall diagnostic accuracy," said cardiologist Dr. David Morrow of Brigham and Women's Hospital in Boston. Morrow wrote an accompanying editorial in the journal and has consulted for Siemens.

In one study, doctors led by the University Hospital in Basel, Switzerland, took blood samples from 718 patients who came into the emergency room with heart attack symptoms such as chest discomfort and shortness of breath. Doctors compared the accuracy of four of the new blood tests with an older test.

In the second study, researchers led by Johannes Gutenberg University in Mainz, Germany, studied 1,818 people who came in with chest pain. Their troponin level was detected by a sensitive Siemens test and a conventional test.

In both cases, the accuracy of the newer tests was 94 to 96% compared with 85 to 90% for the older tests.

Mayo Clinic cardiologist Dr. Allan Jaffe advocates using the newer tests. Several doctors said the new tests do not cost more than the older versions they are replacing, and are usually covered by insurance.

"You diagnose heart attacks faster and you detect more people who are having heart attacks," said Jaffe, who had no role in the studies.

Further studies are needed to determine if earlier detection of heart injury results in more lives saved, the researchers said.

The Swiss study was funded by the Swiss National Science Foundation, Swiss Heart Foundation and the three makers of the tests. One of the authors reported receiving fees from the three companies. The German study was funded by diagnostic company Brahms Aktiengesellschaft. Two of the authors reported receiving fees from test makers.

Column: In the pipeline

Derek Lowe wonders why some diseases are easier to drug than others

What's the most difficult therapeutic area for drug discovery? They're certainly not all created equal - or if they were, they have definitely diverged since then. The question may be impossible to answer precisely, but it can be narrowed down quite a bit.

Several years ago, a study came up with some success rates across several broad areas, covering the 1990-2002 period.¹ Looking at how many drugs emerged onto the market after having gone into human trials, the clear winner was the cardiovascular area - despite a solid 80 per cent failure rate during the clinical and regulatory approval phases. The average failure rate across the industry was just over 90 per cent, which might give people some idea of what it's like to work in this business.

© JUPITER IMAGES

Keep in mind that this study looked at projects which, as far as the people in the discovery labs were concerned, were already thought of as successful. After all, they made it to the clinic - the majority don't even get that far. We don't have good exact numbers on the preclinical phase of development; since companies are loath to talk about how many (un)successful projects they initiate. But my experience over the last twenty years suggests that preclinical failure is definitely more common than not.

Some areas do seem to have a peculiarly hard time getting to the clinic. For example, an antiinfectives team at GlaxoSmithKline found that of the 67 bacterial targets on which they ran high-throughput screens during the late 1990s, only 16 gave any hits, and only five of those turned into any sort of lead compound series.² That's very much below the usual average, and has led to speculation that there may be some sort of mismatch between prokaryotic targets and the screening collections that we use in industry. It does seem likely that the sorts of compounds that can penetrate bacterial membranes may not be well represented. Bacteria, of course, can also fight back in all sorts of ways, which makes targeting them a special challenge.

On the other hand, the animal models in the antiinfectives area are relatively believable, if you ever manage to get that far. Oncology animal models, though, are notorious for their necessary-but-not-sufficient readouts, and central nervous system (CNS) models can be even fuzzier. Alzheimer's research is a perfect example of an area that has suffered tremendously over the years from a lack of believable models.

Not coincidentally, oncology and CNS were the two areas with the worst clinical trial prospects of all during the 1990s. Both showed knuckle-whitening failure rates of between 90 and 95 per cent (note, however, that this data was collected before the advent of kinase inhibitors that have shown reasonable success rates in cancer trials). But these two areas came to those figures through different routes.

The reason is the cost and difficulty of the respective clinical trials. Cancer trials can be relatively inexpensive, since they tend to be shorter and have clear endpoints. (The difficult step in oncology is patient recruitment). CNS trials, on the other hand, can be lengthy, and often need large cohorts of patients to show convincing statistics. Participants in trials for anxiety and depression benefit just from the clinical trial setting, which leads to the high placebo responses that are very rare in cancer.

The big hitters

If companies are willing to try more marginal candidates in oncology, but step carefully into the clinic in CNS, that argues for the latter area being (perhaps) the toughest of them all. In my experience, the people who've worked in it will make that case themselves, given even the slightest bit of encouragement. Having put in some time working against dementia and Alzheimer's targets, I can't exempt myself from that set!

But if I had to pick a contender to take on CNS as the hardest therapeutic area, I might go with the broad autoimmune disease category. That's because while it is possible to treat some symptoms, the real disease mechanisms remain largely obscure. The animal model problems are accordingly quite severe. I haven't seen a breakdown of clinical success rates, but some of the diseases in this area (such as lupus) have relentlessly consumed clinical candidates.

So those are my picks, and I invite suggestions to add to the list. We can only hope that these categories will eventually lose some of their distinctive character.

Derek Lowe is a medicinal chemist working on preclinical drug discovery in the US