Over at Wired Playbook, I wrote a piece about a group of researchers using ECG sensors, GPS, accelerometers, and a mobile phone to accurately monitor a patient with heart trouble, in real-time, during their prescribed exercise routine.

…[E]ven in this small pilot study, the device proved some worth: On two separate occasions, the researchers noted distinct abnormalities in a patient’s ECG and consulted with a cardiologist. While the cardiac events turned out to be benign, the fact that such subtleties could be picked up with remote monitoring holds much promise for the tech. Had a more serious medical emergency transpired, the researchers could have summoned an ambulance to the scene using the transmitted GPS data.

Though this was a small pilot study, the proof-of-concept research was a cool step forward for remote monitoring of health.

Read the entire article here.

Photo via Flickr / rwk

Worringham, C., Rojek, A., & Stewart, I. (2011). Development and Feasibility of a Smartphone, ECG and GPS Based System for Remotely Monitoring Exercise in Cardiac Rehabilitation PLoS ONE, 6 (2) DOI: 10.1371/journal.pone.0014669

My latest post for Wired Playbook reports on a new idea that two UK researchers have proposed for keeping tabs on which Olympic athletes are using performance-enhancing drugs.

Rather than having the athletes pee in a cup or get blood drawn just before competition, the researchers believe that searching for drug metabolites in the wastewater that flows from the Olympic village might be more effective, especially if used in conjunction with current screening methods.

As I wrote:

These studies indicate that fancy chemical analysis techniques can indeed detect drugs in wastewater, but claiming that some fraction of Olympic athletes uses PEDs, based on data showing traces of illegal substances in the sewer water? Well, that wouldn’t make Olympic officials blink. Unless researchers can hone in on who was using them, the idea simply won’t fly.

Katsoyiannis admits that while solid research supports their theoretical claim, the actual practice of monitoring wastewater in an Olympic Village to specifically target illicit drug use hasn’t been tested. But he plans to harness localization techniques developed during years of environmental research that could isolate the origin of certain organic pollutants that contaminate water supplies through rigorous sample collection and old-fashioned detective work.

I went “upstream” on this piece, and not just in the, er, wastewater vernacular sense. But upstream in that it’s reporting science at the beginning of the process, when the idea was just that, an idea. No data had been collected. No analysis completed.

Most science coverage waits until the end of the study to simply relay results. But in an effort to try new formats and techniques, I decided to cover the very early stages of discovery.

Read more…

Hats off to Misha Angrist over at Genome Boy for bringing this fascinating story about personal genomic experiments that ran in Nature Medicine to my attention.

Raymond McCauley and a small team of DIY-researchers wanted to know how effective different types of vitamins were for clearing “undesirable” amino acids from their bodies.   One of the supplements they investigated was a standard, over-the-counter vitamin B tablet.  But the other, was a more highly active B vitamin, called L-methylfolate.  McCauley’s genetic profile differed from the rest of his team in two particular SNPs (he was homozygous at both locations).

For four of the study participants, all of whom paid out of pocket to participate in the research, either type of vitamin supplement decreased homocysteine levels by almost a third, indicating that the vitamins were having the desired effect and leading to homocysteine getting converted into more benign amino acids. But for McCauley—the only person in the study who was homozygous at both SNPs tested—run-of-the-mill pills raised his homocysteine concentrations, and only the more active L-methylfolate seemed to aid his vitamin metabolism. After completing the experiment last month, McCauley changed his source of supplementary vitamin B to L-methylfolate.

When something’s wrong with the body, the innate immune system kicks into high gear, sending inflammatory molecules through the body, which help recruit macrophages – the cellular garbage collectors – to the scene. Recent publications show systemic inflammation goes hand-in-hand with cardiovascular disease (CVD) and atherosclerotic vessels. Researchers have been trying to pinpoint which inflammatory markers could potentially be used as biomarkers for CVD risk or progression. Current efforts have zeroed in on one marker in particular, the C-reactive protein, in the hopes of finding a way to assess a person’s risk for CVD both non-invasively and well before a cardiovascular event occurs.

Preliminary evidence has shown that in the normal population, the higher the C-reactive protein level, the higher the risk for CVD. But what exactly is a normal population? These days, a full serving of heart disease often comes with a heaping side of Type II diabetes, rheumatoid arthritis, or chronic kidney disease, creating a so-called “co-morbidity” of chronic diseases. Not surprisingly, these secondary disease states also affect the levels of C-reactive protein in the blood. So when a patient has more than one chronic condition, how useful is measuring the C-reactive protein level in predicting CVD risk?

A new study published this week in PLoS One by a group at Kings College, London, took a look at people with rheumatoid arthritis (RA), an inflammatory joint condition that also coincides with remarkably elevated C-reactive protein levels. According to the authors, along with swollen joints, sufferers of rheumatoid arthritis are also twice as likely to have a heart attack.

The researchers looked at three subclinical measures of CVD: flow mediated dilation (measures endothelial cell function), intima-medial thickness (measures arterial wall thickness), and pulse wave velocity (measures large artery stiffness), in people with RA and healthy control subjects. The RA group was further subdivided into three tiers according to how much C-reactive protein was circulating in the patient’s blood during a baseline reading.

If C-reactive protein was in fact causing CVD in rheumatoid arthritis patients, the subclinical CVD measures should incrementally change as the level of C-reactive protein increases. However, the researchers found that two of the subclinical measures didn’t change at all as the level of C-reactive protein increased in those with rheumatoid arthritis. The third subclinical measure – the flow mediated dilation value, which measures how responsive endothelial cells are – actually improved as C-reactive protein levels rose, suggesting that the protein may offer a protective function in a chronic state of inflammation.

I’m always scouring scientific papers looking for the next great thing in biomarkers. After all, if a simple blood test can tell us who’s at risk for certain diseases, we could make great strides in diagnosis and treatment of affected people. But I think this paper shows that biomarker readings are not so straightforward. In the complicated web of chronic disease we’re now spinning, we need to better understand how cardiovascular disease biomarkers – particularly inflammatory markers — change when people have more than one chronic medical condition.

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0010242#pone-0010242-t001

Obesity (determined by BMI) and blood glucose levels are by far the best predictors of whether a person will develop diabetes. Yet doctors are always on high alert for new biomarkers that may be more sensitive indicators of which patients will develop diabetes in the near future.

The idea of using biomarkers to predict diabetes is not entirely new. Glycated hemoglobin (HbA1C) values are now routinely being monitored to screen for at-risk patients. However, a new study in PLoS One shows that several new biomarkers in the blood may further our understanding of exactly who’s at risk for diabetes, and increase our knowledge of the etiology of the disease.

Veikko Salomaa and colleagues from the Department of Chronic Disease Prevention at the National Institute for Health and Welfare in Helsinki, Finland, tested nearly 13,000 people and found almost 600 cases of diabetes during routine follow-up exams.

According to the study, low levels of adiponectin, and high levels of apoB, C-reactive protein (CRP), and insulin, increase the chance that a woman will develop diabetes. When these factors were measured, proper diabetes prediction increased by 14% compared to when doctors only use classic risk factors, such as BMI and blood glucose levels, to predict disease.

The biomarkers that best predicted diabetes in men were low adiponectin, and high levels of CRP, interleukin-1 receptor antagonist, and ferritin. Accounting for these biomarkers led to a 25% increase in correct diabetes detection in the cohort.

read the study here.

In Chapter 6 of The Decision Tree, “Screening for Everything”, Thomas talks about the human papilloma virus (HPV), the virus that causes cervical cancer. Traditionally, doctors detected HPV by looking for irregular cells in the pap smear. But now, a cheap ($5) test can detect and analyze the DNA of the virus, determining if it is the high- or low-risk type, which can determine the likelihood of a patient developing cervical cancer.

One problem remains: you still have to get women into the clinic to be tested. However, a new study in the British Medical Journal shows that home testing is not only a reality, but it may actually boost compliance rates. Roughly 28% of women using the home testing kit, which consisted of a simple cervicovaginal lavage, effectively screened themselves, while only about 17% of women required to go into the doctor’s office for screening showed up.

The HPV DNA test is primarily looking for the high-risk virus serotype, and the authors of this study claim that home screening kits have the same sensitivity as the doctor’s protocol when specifically looking for the aggressive virus.

Special thanks to Lindsay Crouse for bringing this to my attention. In her email to me, she brilliantly summed up the significance of home HPV testing:

While screening has been tremendously successful in Western countries at reducing cervical cancer cases and deaths, the obstacle of reaching all women through screening remains. Currently, if a woman is to be screened for cervical cancer, she must visit a health care provider for a gynecological exam. If she is unable or reluctant to do that, whether due to transportation, cost, or comfort issues, she is less likely to get screened at all, and is consequently at increased risk for developing cervical cancer. More than half of such cancers are typically diagnosed in women who do not get screened regularly.

We’ve all heard the mantra: keep LDL levels – the “bad” cholesterol – down, and the “good” HDL cholesterol up. But thanks in part to the ubiquity of statins, such as Lipitor, which allow us to simply pop a pill to limit LDL production in the body, we’ve recently adopted tunnel vision when thinking about managing cholesterol. LDL levels are all we seem to care about now, as we strive for lower and lower numbers at each visit to the doctor’s office.

However, I think we’re missing the bigger picture by focusing solely on LDL. First, it’s made us reliant on medication to solve a problem that can many times be addressed with changes in diet and exercise regimes. Once someone starts Lipitor treatment, they’ll be taking it for life, and if LDL levels don’t quite get as low as they should, it’s all too easy to solve the problem by increasing the dose. When patients first begin Lipitor treatment, physicians typically prescribe the lowest possible amount, 10mg. However, dosing can go as high as 80mg, which begs the question: Do higher doses of the drug really improve outcomes?

Read more…

[this is a post I did for TheHealthcareBlog, crossposted here]

Want to know the future of medicine and healthcare in one sentence?

For my money, it goes like this: The real opportunity in healthcare is to combine our personal data with the huge amount of general biomedical and public health research, in order to create customized information that’s specific to our person and our circumstance. We need relevance, and the right information at the right time will help us make better choices for prevention, helping us stay healthier longer, it’ll help us navigate diagnosis, letting us select screening tests that are useful and not unnecessarily fearful, and it’ll let us make better decisions on care and treatment – when we’re trying to choose among various treatments to find our way back to health.

It’s in the last category – care and treatment – that I wrote a recent post at the Huffington Post about one man’s story with prostate cancer. Tom Neville got a diagnosis and then had to struggle to find information to help him make sense of what to do. Ultimately, he chose surgery, but the difficulty of the choice led him to create Soar Biodynamics, a company that offers decision-making support for men assessing their prostate health.

You can read his story here and learn more about his tool here, but for the purposes of this post I wanted to consider the kind of decision-making tool he created. It’s called a nomogram, and it’s one of my favorite discoveries in researching The Decision Tree.

A nomogram is basically a calculator – a way to assess our risk or outcome for a particular condition. A nomogram starts with an interface where a few telling datapoints can be entered, and then turns to an algorithm that crunch those numbers together with broader data about the condition. The result is a statistical prediction – the prediction can concern the outcome of the disease, or it can be a recommendation for particular treatment (a medical nomogram is not to be confused with mathematical nomograms, which are tools for calculating geometrical something or others).

The Framingham Risk Calculator, which calculates your risk of heart disease, is a kind of nomogram. Memorial Sloan-Kettering Cancer Center, the research institute and hospital in New York City, has developed almost a dozen nomograms for a range of cancer conditions. There are tools for predicting the spread of breast cancer, a tool for assessing lung cancer risk among smokers, a tool for predicting the prognosis after colon cancer surgery, and more. Dr. Pierre Karakiewicz at the University of Ottawa has developed nomogram.org, which offers prediction calculators on four different types of cancer. Nomograms are one of the best examples of Decision Tree thinking, the sorts of tools that are easy for patients and doctors alike to use and understand—particularly when they’re available online and free of charge. They’re brilliant and auspicious because the turn research around so that it faces the patient: An individual can interrogate medical science for how it applies to his specific circumstances, rather than having to navigate through stacks of research papers and findings for some wisp of relevance.

Nomograms are especially powerful when they’re combined with a screening test, because they help people understand what to make of the test and point to what to do with the result. They immediately customize the clinical data, be they nanograms-per-milliliter figures or spots on mammograms. Nomograms let patients ignore the inscrutable repository of jargon that is medical research in favor of something personal, something real, and something to go on. They allow us to make sense of a screening test’s result, and allow us to take some measure of meaning from it.

The University of Texas at San Antonio, for instance, has developed a prostate risk calculator that lets a man enter his PSA level along with his age, race, family history, and a couple of other metrics and churns out his risk of developing prostate cancer. Importantly, the calculator also calculates the risk of a high-grade cancer, accounting for the fact that not all prostate cancers are lethal. The value of such a tool, says Ian M. Thompson, professor and chairman of the department of urology at the University of Texas Health Science Center at San Antonio, who developed the calculator, is that it turns the PSA figure from one isolated data point into one of many inputs. “We need to build in characteristics about the person, their age, their race, their family history,” says Dr. Thompson. “It’s not just what one test tells us.”

Nomograms, of course, are no substitute for a doctor’s definitive assessment and treatment (or better yet, more than one doctor). And they are only as good as the data that goes into them; if they’re not kept up to date on the latest information and research, they can lead people astray. But especially for conditions where we have some agency – where we can take actions today that can enhance our tomorrow – they are a terrific tool.

The catch with nomograms is that they must be developed one disease at a time, which means they don’t scale up so well. Each one takes a great deal of work and expertise. But if I had millions of dollars for philanthropy, I’d spread it around to smart researchers across a lot of fields where nomograms could help people assess their risk for disease and potentially take actions today. It would be money well spent.

Calculator image via Flickr by Ian Ruotsala

The most impressive tool for clinical decision-making presented at the Health 2.0 conference was a program that allowed docs to share medical images over the Internet, developed by MyPACS.net.  Any DICOM image (e.g. CT scan, MRI, etc) can be uploaded and shared through their website.

Say, for example, that a patient comes to the hospital with abdominal pains.  After undergoing a CT scan, the radiologist determines that there is a mass located in the abdominal cavity, but is not quite sure what it is.  Traditionally, the radiologist would either compare the patient’s CT to scans in the hospital archive, or spend hours searching through the limited information in medical journals.  With MyPACS.net, doctors can upload and share hundreds or thousands of images, instantaneously.  It’s like Facebook photos or Flickr for physicians.

Not only would this system help a small-town hospital that has limited DICOM image archives, but it also eliminates the 6-10 month lag in publication of images in medical journals.

A quick note that my latest story for Wired, on the emerging science of early detection of cancer, is now on stands (and online).

The story focuses on the Canary Foundation, a Silicon Valley-based nonprofit that’s funding an innovative approach to cancer research: strictly focusing on developing two-step tests that will spot various cancers in their earliest stages, when the odds of successful treatment are highest.

My effort here was to explore how early detection – which sounds obvious on its face; of course we should find cancer early – in practice creates a series of riddles and/or paradoxes. For instance, when you’re looking for something floating in the bloodstream (a molecular signal of early cancer), how can you be sure it’s present in high enough volumes early enough to be worthwhile as a test? Or: What if a test is great at spotting cancers that, paradoxically, may not actually be lethal, and thus may not merit immediate treatment? What I find admirable about the Canary Foundation approach is that they don’t look at finding a protein or a DNA signal as the be-all/end-all of a valid test – it’s just the beginning the a statistical parsing that may or may not result in something clinically useful.

If it’s not obvious, the connection to the decision tree thesis is this: Finding disease early, when treatment choices are various and have more promise of success, is a far better position to be in than waiting for symptoms and late-stage treatments. My hunch is we’re going to be moving towards more and more screening tests for more and more conditions. The challenge will be striking a balance between good tests that and the expense of too much screening and too many false signals.

Oh, and a shout-out to Wired’s design department, helmed by Scott Dadich, which always does an ace job turning some rather sober writing on my part into something alluring and cover-worthy.