Risk, Odds, Hazard...More on The Language

For every 100 g of processed meat people eat, they are 16% more likely to develop colorectal cancer during their lives. For asthma sufferers, the odds of suffering an attack for those who took dupilumab in a recent trial were reduced 87% over a placebo. What does all this mean, and how do we contextualize it? What is risk, and how does it differ from hazard? Truthfully, there's several ways to compare the effects of an exposure to some drug or substance, and the only one that's entirely intuitive is the one that you're least likely to encounter unless you read the results section of a study.

When you see statistics like those above, and pretty much every story revealing results of a study in public health will have them, each way of comparing risk elicits a different kind of reaction in a reader. I'll go back to the prospective cohort study suggesting that vegetarians are 1/3rd less likely to suffer from ischemic heart disease (IHD) than those who eat meat, because I think it's such a great example of how widely the interpretations can seem based upon which metric you use. According to this study, IHD was a pretty rare event; only 2.7% out of over 44,500 individuals developed it at all. For the meat-eaters, 1.6% developed IHD vs. 1.1% in vegetarians. If you simply subtract 1.6% and 1.1%, you might intuitively sense that eating meat didn't really add that much risk. Another way of putting it is out of every 1,000 people, 16 people who eat meat will develop IHD vs. 11 for vegetarians. This could be meaningful if you were able to extrapolate these results to an entire population of say 300 million people, where 1.5 million less incidences of IHD would develop, but I think most epidemiologists would be very cautious in zooming out that far based upon one estimate from a single cohort study. Yet another way of looking at the effect is the "number needed to treat" (NNT), which refers to how many people would need to be vegetarian for one person to benefit. In this case, the answer is 20 200 (oops!). That means 199 people who decide to change their diet to cut out meat entirely wouldn't even benefit in terms of developing IHD during their lifetime.

The EWG Dirty Dozen: Whoever Said Ignorance is Bliss Definitely Didn't Have Chemistry in Mind

Each year, the Environmental Working Group (EWG) compiles a "Dirty Dozen" list of the produce with the highest levels of pesticide residues on them. The 2013 version was just released this week, framed as a handy shopping guide that can help consumers reduce their exposure to pesticides. Although they do say front and center that it's not intended to steer consumers away from "conventional" produce if that's what they have access to, this strikes me a little as talking out of both sides of their mouth. How can you say that if you really believe that the uncertainties are meaningful enough to create the list, and to do so with the context completely removed? I'm pretty certain the Dirty Dozen preaches to the choir and doesn't change many people's behavior, but the underlying message behind it, while perhaps done with good intentions, to me does some genuine harm regardless. The "appeal to nature" fallacy and "chemophobia" overwhelm legitimate scientific debate, have the potential to polarize a nuanced issue, and tend to cause people stress and worry that's just not all that necessary. This is not hardly going to be a defense of pesticides, but a defense of evidence-based reasoning, and an examination of how sometimes evidence contradicts or complicates simplified narratives. You should eat any fruits and vegetables that you have access to, period, no asterisk.

This latte should not be so happy. It's full of toxins. (Source)

Almost 500 years ago, the Renaissance physician Paracelsus established that the mere presence of a chemical is basically meaningless when he wrote, to paraphrase, "the dose makes the poison." The question we should really be asking is "how much of the chemical is there?" Unfortunately, this crucial context is not accessible from the Dirty Dozen list, because context sort of undermines the reason for this list's existence. When we are absorbing information, it comes down to which sources we trust. I understand why people trust environmental groups more than regulatory groups, believe me. However, one of the recurring themes on this blog is how evidence-based reasoning often doesn't give the answers the public is looking for, whether it's regarding the ability to reduce violent crime by cleaning up lead pollution, or banning BPA. I think a fair amount of the mistrust of agencies can be explained by this disconnect rather than a chronic inability to do their job. However true it may be that agencies have failed to protect people in the past, it's not so much because they're failing to legitimately assess risk, it's for reasons such as not sounding an alarm and looking the other way when we know that some clinical trials are based on biased or missing data. Calling certain produce dirty without risk assessment is sort of like putting me in a blindfold and yelling "FIRE!", without telling me if it's in a fireplace or whether the next room is going up in flames. When 2 scientists at UC Davis looked into the methodology used by the EWG for the 2010 list, they determined that it lacked scientific credibility, and decided to create their own model based upon established methods. Here's what they found:

The Antibody for CD47: How a Promising Treatment Can Get to Patients

Perhaps (I hope) you've heard that imagining all forms of cancer as a single disease is pretty misleading. Some tumors are liquid, some are solid. Some develop on tissue lining one of the many cavities within or on the outside of the body, and some show up on bone or connective tissue. Virtually in every instance cancer researchers have found that the differences have been far more pronounced than the similarities. For decades, efforts to find the one thing common among all of these tumors, in order to find a single, broad potential cure, has basically come up empty. This helps explain why progress on treating cancer has been so aggravatingly slow, and why drugs for breast cancer don't necessarily help a patient with lymphoma. On March 26, the Proceedings of the National Academy of Sciences (PNAS) published an article (some images from which are below) based on tissue cultures and experiments on mice that exploits one broad similarity between many types of tumors, which could potentially lead to a rather simple, single therapy that thus far shows no signs of unacceptable toxicity in the mice. Sounds great, right? So how does this work, what happens next, and how unprecedented is this?

Just look at what happens when you target CD47

Ultimately, drugs are molecules, and when they work, it's because there's a target that fits the unique shape and characteristics of the drug. Some early chemotherapeutic drugs, such as vincristine or vinblastine worked because they bonded to the ends of molecules that formed the components of a tiny skeletal framework which holds together virtually every cell in our bodies. Unable to support themselves, new cells across the board did not grow and divide, but since cancer cells grow faster than normal cells, they were the ones more affected. Hair and blood cells also grow rapidly, leading to the most familiar side affects of chemotherapy, hair loss and extreme fatigue. So while these drugs may have led to remission for some patients, it is never without excruciating side affects. The therapy described in PNAS takes a very different approach, where the target is a protein embedded on the surface of cells called CD47, which when expressed, prevents macrophages in the immune system from engulfing and destroying the cells. It does this by binding to a different protein expressed on the surface of the immune cell that happens to fit it quite well. When CD47 is bound to the protein on the macrophage, a signal is sent not to eat whatever cell it's attached to. It's an amazingly elegant system, and fatefully, according to the study, cancer cells happen to express a lot more CD47 than normal cells. The researchers used an antibody for CD47, yet another protein which could bind it in place of the protein on the surface of the macrophage. This prevents the signal that says "don't eat me," and allows the immune cell to do its normal function of destroying something it doesn't recognize. Previous studies had established that this antibody helps shrink leukemia, lymphoma, and bladder cancer in mice, so the PNAS study expanded upon this to look at ovarian, breast, and colon cancers, as well as glioblastoma. It effectively inhibited growth for each, sometimes outright eliminating smaller tumors. Larger tumors, the authors note, would likely still need surgical removal prior to antibody therapy. There's no question now, this needs to be tested in actual human patients.

The next step will be to organize what's called a phase I trial, which enrolls some brave (or desperately poor) individuals, perhaps up to 100, to help determine whether the drug is even safe enough to find out whether it works, and what dose can be tolerated. Often, for simplicity's sake, phase I is combined with phase II trials involving ideally a couple hundred more individuals, which appears to be the intention with the antibody therapy. Phase II trials answer the question "can it work?", with the assumption going in that it doesn't. For a refresher on how the future trial data will be analyzed, see my previous post on basic statistics. Should this phase II trial pan out, meaning sufficient biological activity is observed without unacceptable risks, and there's obviously no guarantee that this will happen, a new, more robust trial will be designed. Phase III trials answer the question everyone wants to know: does it work? The ideal phase III trial involves several thousand patients, which probably wouldn't be too difficult to find when the drug could save their life. In this stage, the new therapy would be compared to the best current therapy rather than placebos, because a placebo isn't a treatment, and would be unbelievably unethical to give to a cancer patient. Take a look at this page from the National Cancer Institute for more information specific to how cancer trials operate.

Oftentimes, unfortunately, the process isn't as smooth as I outlined. Trials are increasingly outsourced outside of the US or Europe, where regulations and ethical frameworks are not nearly as strong, and of course, a few thousand patients in a randomized control trial can't catch every potential adverse effect. And then there's the question of who funds and how they manage these trials, but I'm not going there. For every thousand poor critiques of Big Pharma you can find on the Internet, there's only one Ben Goldacre who does it right. I recommend Bad Pharma if you want to really know more about where this could all go completely off the rails.

Tumors go bye-bye

That's a long, long road that takes up to a decade, and potentially billions of dollars spent before this potential drug could ever reach the general cancer patient. Given this, it's not really too surprising how much pharmaceutical companies spend on advertising once they beat the odds and get a new drug approved by the FDA. And that's all the more hopeful part of the CD47 story. Thousands of chemicals have been shown to kill cancer cells in vitro, and just a cursory search of the national registry of clinical trials for RCTs involving antibody therapy for cancer alone brings up nearly 1100 results in various stages, from withdrawn, suspended, or currently recruiting patients.  This is just a tiny sampling of all clinical trials on cancer therapies, that all got to where they were because they were once so promising in test tubes and animal models. So when you read about this study in the media, it's natural to hope we've finally found a major breakthrough. Maybe we really have. The odds are certainly long, and hopefully this post will help you understand that there's perfectly legitimate reasons why. If it doesn't pan out, it's not gonna be because a trillion dollar industry held it down, it's gonna be because of unacceptable toxicity, or because the effectiveness simply doesn't translate to us, or because it's not significantly better than current treatments. I can't possibly conceive of a worldview where drug companies wouldn't want to get this to people ASAP.

4/25/2013 - UPDATE: I had heard about the FDA's recent Breakthrough Designation, which is intended to expedite the long process of getting drugs to patients with serious conditions, but it didn't come to mind for this post. A melanoma drug received breakthrough designation yesterday, after very preliminary trials showed a marked response in patients. Stay tuned to see if the CD47 antibody therapy joins the ranks.

Allow Me to Curate the State of BPA Research For You

After reading two interesting articles on bisphenol A (BPA) in the past few weeks, I decided to spend a little time the other day looking through reviews and analyses to get my own sense of where the research stands. There's a pretty staggering amount of research out there with a variety of designs, which makes the conclusion all that much more frustrating: We don't really know what the deal with BPA is. That being said, it's probably time to rethink the approach to what to do about it.

BPA is considered an endocrine disruptor, meaning that its structure is very similar to a hormone, in this case estradiol. It's so similar, in fact, that hormone receptors for estradiol can be tricked by BPA into a response as if estradiol were bound to it, affecting potentially a number of biological activities. Observational studies have linked BPA to a variety of negative health impacts, especially obesity, neurological damage, cancer, and recently asthma. Considering that virtually everyone is exposed to BPA due to its widespread use in making plastic bottles, can linings, paper receipts, and epoxy resins, these associations naturally should be cause for some concern, particularly in how it may affect infants and children. There is considerable debate on precisely how much concern there should be, probably more than is reflected in most media accounts. The way scientists approach this is quite at odds with the type of information the public needs, which was put eloquently by Richard Sharpe, a researcher in the UK who takes a pretty skeptical stance on BPA's harmful effects.

What is never stressed enough is that scientists work at “the borders of ignorance” – what is in front of us is unknown and we try to find our way forward by making hypotheses based on what is known. This means that we are wrong most of the time, and because of this scientists have to be very cautious about interpretations that are based on our projected ideas about what is on front of us. What decision-makers, politicians and the public want is unequivocal guidance, not uncertainty. So this creates a dilemma for scientists. 

So far this is beautiful. Absolutely crucial to keep in mind. Sharpe continues:

Those who are more prepared to throw caution to the winds and make unequivocal statements are more likely to be heard, whereas a more cautious scientist saying “we’re not sure” will not be taken notice of. 

I honestly don't know whether this is the case with BPA or not. The uncertainties are many, and the value of the observational studies showing all these associations is controversial. There are a number of criteria that correlative studies must meet in order to determine whether that correlation actually equals causation, summarized from the link above.

Hill's Criteria applied to a chiropractic term "subluxation", which refers to an abnormality in the spine that supposedly causes a number of diseases. Subluxation is undetectable by X-ray, but nevertheless is considered treatable by some chiropractors through realignment.

In 2008, the Natural Resources Defense Council petitioned the FDA to ban BPA largely on the basis of all these correlative studies. The FDA responded that after years of review, these criteria had essentially not been fully met, and did not ban the substance, specifically on the basis of criteria 5, 7, and 9. One of the criticisms of the FDA response is that some evidence suggests even very low doses may have strong effects, and that a typical dose-response curve that rises steadily as the dose increases until it ultimately plateaus does not reflect how BPA works. Rather, BPA may have sort of an inverted U-shaped dose-response curve referred to as hormesis, in which high levels actually don't have an effect at all, or perhaps even the opposite effect.

Dose-response curve of hormesis (Source)

Some studies used to support the petition relied on non-oral BPA exposure, which the FDA considered insufficient, as exposure from the skin misses some of the metabolic processes that quickly turn BPA into an inactive form called BPA-monoglucuronide. The only real exposure we'd really need to be concerned about is oral, since that's how we're predominantly exposed, and there's enough difference between how BPA acts orally vs. subcutaneously to doubt the significance of studies using the latter method.

Additional studies used by the NRDC were based upon experiments performed on isolated tissue samples, which bring up a similar concern, as well as being essentially limited to describing a potential mechanism for the chemical's effects and what sort of tissue it would ultimately effect. Another study showing an association with cardiovascular problems was cross-sectional, which takes a single measurement of exposure at one point in time and looks at whether the higher levels of exposure are associated with a disease. As I've mentioned before, this study design is limited to generating hypotheses, and are definitely not considered suitable for determining causation.

So we have a number of epidemiological associations, experimental data on tissue samples, plus some experimental data on primates, and rodents, all pointing to some negative health effects, sometimes even at small doses. Couldn't these all add up to more than the sum of their parts? Sure, there's really 2 major ways to validate that claim. One way, which the FDA apparently thinks highly of, is to use the data from other mammals and tissue samples to develop a mathematical model, which can be used to predict the effects found in humans. Another would be to approach the problem along the lines of, "given the data that shows such and such effect at this level in animals and tissue, we can assume that the probability of this translating to humans in real world exposure is X." Nobody has seemed to try this yet, and the level of subjectivity involved in determining that X makes some researchers uncomfortable. Recently, a researcher named Justin Teeguarden developed a model to predict the levels that should be typically found in humans, and presented his findings (yet to go through peer review) at the annual meeting of the American Association for the Advancement of Science. His research determined that the levels causing effects in animals and tissues are not plausibly found in humans.

Biologists and epidemiologists who have worked on the studies showing the harmful effects question the validity of the assumptions that went into his model, as well as the lack of predictive power in what the levels he suggest exist in humans actually does at either acute or chronic exposure. Tom Philpott at Mother Jones suggests that Teegaurden's past ties to the plastics industry makes his research suspect, a sentiment I don't entirely share, but is not completely irrelevant.

So what do we make of all of this? I think this is a perfect scenario for an ideological fight where two sides dig in immediately and reach a stalemate. Studies with inherent limitations get disseminated to the public as being probably more suggestive than they really are, feeding premature alarm, while industry unjustifiably dismisses the risk. If you read the FDA's response to NRDC, it appears to me that you're just not going to get far calling for an outright ban on a substance like BPA unless you have a good amount of longitudinal data plus experimental data on mammals using the same type of exposure as would be expected in humans. Is that the best way to go? If not, how can it be improved upon?

Perhaps the NRDC's petition might have been more effective if it were honest about the limitations of the studies supporting their argument and the uncertainties that exist (like the dose-response curve of BPA). In addition to calling for a ban of BPA using the precautionary principle, there should also be a focus on safer alternatives. In other words, don't just point to a problem, especially when it's not totally cut and dried, but demonstrate a workable solution, and pursue it with the same energy that's been used up trying to prove something that may not be provable, at least any time soon.

If there's a lesson time and time again from these sorts of things, there's little in the world that's purely black and white. I love exploring the shades of gray, but I can't expect everyone to. However I'd at least love for people to respect that they're out there, and that this is where reality tends to dwell.