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Big data, Genetics, Global Health, Infectious Disease, Research, Science

The benefit of mathematical models in medicine

The benefit of mathematical models in medicine

1024px-Free_range_chicken_flockTheoretical modeling sounds like it has, at best, a distant connection to the day-to-day concerns of medical professionals who care for or research the needs of patients. But when I spoke recently with Noah Rosenberg, PhD, a population geneticist at Stanford and editor of the scientific journal Theoretical Population Biology, he pointed out that modeling can offer distinct benefits to those in medical fields like epidemiology and genetics.

“We see a lot of occasions in public discussions of areas like the spread of epidemics, the demography of aging populations, and big data analysis in genomics where part of the backdrop arises from theoretical population biology work,” Rosenberg said. “We hope to spread the word that there is a place for the kinds of theoretical and mathematical insights that can contribute to those important topics.”

Rosenberg noted that papers in the journal often span the divide between mathematics and biology, but they have a few things in common. In an editorial he published last month in the journal, Rosenberg describes an ideal study for the journal – namely that first, “the mathematical work is motivated by a genuine problem in biology, and there’s a need for theory to resolve the problem,” he said. Secondly, the mathematical work is substantial enough that it uncovers new potential relationships or new explanations for a phenomenon, and lastly, that the advances contribute to our understanding of biology – though some of the best papers in the field can also have a big impact on the field of mathematics, too.

When I asked him to talk about what that would mean for studies that touch on health research, he pointed me to a couple of fascinating papers. One is a paper by Shai Carmi, PhD, and colleagues that explains a new way to look at shared DNA strands between people in order to understand their relatedness and the amount of overlap in their genomes. This has implications for how we think about “the way in which genes descend within families, including genes that may be related to a disease.” It’s one of the journal’s most downloaded papers, Rosenberg told me.

The second is a study by Maciej Boni, PhD, and colleagues that incorporates how decisions that poultry farmers in Southeast Asia make about market conditions might affect the spread of avian influenza in their flocks. When avian flu is identified in a region, poultry flocks are usually culled. It’s an interesting example of how human behavior can affect disease dynamics.

Rosenberg noted that the studies and models that are able to incorporate human behavioral patterns are among the most interesting that he sees. Nailing down how people’s decisions affect the course of an outbreak is notoriously difficult, but like the avian influenza paper demonstrates, mathematical models make it possible to explore the consequences of different assumptions about these decisions.

Rosenberg says that it’s even possible to make mathematical models of cultural practices (like deciding not to immunize your children) and how they spread among groups of people. One public laboratory this interaction is currently playing out in is the measles outbreak that got its start at Disneyland in December. The outbreak topped 100 cases nationwide, mostly among families that refuse to vaccinate their children. “It’s the intersection between human behavior and dynamics of disease,” he said. “Putting those together in a mathematical model to predict what might happen is the kind of work that appears in Theoretical Population Biology.”

Previously: Stanford physician Sanjay Basu on using data to prevent chronic disease in the developing world and Facebook app models how viruses spread through human interaction
Photo by Woodley Wonderworks

Big data, Events, Pediatrics, Pregnancy, Research, Stanford News

Stanford hosts inaugural Childx conference this spring

Stanford hosts inaugural Childx conference this spring

Chandler's 15 Month CheckupRegistration is now open for the first ever Childx conference, a TED-style conference focused on inspiring innovation in pediatric and maternal health. The conference will bring thought leaders from several disciplines to the Stanford campus April 2 and 3 for two days of conversation about how to harness many branches of medicine to solve the health problems of pregnancy, infancy and childhood.

“Pediatric medicine faces unique challenges,” said systems biology researcher Dennis Wall, PhD, who leads the conference’s scientific advisory board. “Most children are quite healthy, which can make it difficult to attract adequate research attention to severe pediatric diseases that affect relatively few children. At the same time, every child’s health status is influenced by a complex array of factors, which cause decades-long ripple effects as today’s children mature into tomorrow’s adults.”

The conference, developed and sponsored by Stanford’s Child Health Research Institute, has five themes:

  • Definitive stem cell and gene therapy for child health
  • The arc of fetal, developmental/cognitive, and adult health
  • Accelerating child and maternal health innovation
  • Precision medicine for rare and historically untreatable childhood disease
  • The health ecosystem and the impact of social, economic, political, environmental, and cultural issues on children’s health and well-being

Featured guests include Martin Andrews, who leads Glaxo Smith Kline‘s rare diseases team; Nadia Rosenthal, PhD, founding director of the Australian Regenerative Medicine Institute; Harvard’s Matthew Gillman, MD, an expert on early-life prevention of chronic disease; Sheena Josselyn, PhD, a neuroscientist at the University of Toronto and the Hospital for Sick Children who studies molecular processes behind learning and memory; and Donald Schwarz, MD, the director of the Robert Wood Johnson Foundation, as well as a large cast of Stanford stars from several areas of pediatric medicine.

“Pediatric medicine needs to turn its focus more to creating advanced, technology-enabled solutions that will increase our ability to detect, monitor and treat child health,” Wall said. “No pediatric conference to-date has combined these key themes of precision healthcare with the most pressing challenges and opportunities in child and maternal health. The inaugural Childx will be the first conference to do so.”

The conference will welcome maternal and child health researchers, clinicians, investors, industry experts and interested community members. Early bird registration is open through February 28.

Big data, NIH, Research, Videos

Fly through the inside of a mouse lung

Fly through the inside of a mouse lung

Take a 50-second ride through the inside of an adult mouse lung in this video created by Rex Moats, PhD, scientific director at Children’s Hospital Los Angeles. A post published today on the NIH Director’s Blog describes the animation and points out that the video is a prime example of how scientists are using big data to make biomedical research more accessible to the public:

We begin at the top in the main pipeline, called the bronchus, just below the trachea and wind through a system of increasingly narrow tubes. As you zoom through the airways, take note of the cilia (seen as goldish streaks); these tiny, hair-like structures move dust, germs, and mucus from smaller air passages to larger ones. Our quick trip concludes with a look into the alveoli — the air sacs where oxygen is delivered to red blood cells and carbon dioxide is removed and exhaled.

… [Moats] created this virtual bronchoscopy from micro-computed tomography scans, which use X-rays to create a 3D image. The work demonstrates the power of converting Big Data (in this case, several billion data points) into an animation that makes the complex anatomy of a mammalian lung accessible to everyone.

Speaking of the power of big data, the Big Data in Biomedicine conference returns to Stanford May 20-22. For more information about the program or to register visit the conference website.

Previously: Big data = big finds: Clinical trial for deadly lung cancer launched by Stanford study and Peering deeply – and quite literally – into the intact brain: A video fly-through

Big data, Clinical Trials, FDA, NIH, Research, Science

Transparency in clinical trials: The importance of getting the whole picture

Transparency in clinical trials: The importance of getting the whole picture

New rules for clinical trials Scope blog 2015.02.02Last week, the Journal of the American Medical Association ran a Viewpoint article from Francis Collins, MD, PhD, director of the National Institutes of Health and Kathy Hudson, PhD, deputy director of NIH, about the U.S. Health and Human Services’s plans to beef up transparency of clinical trials of FDA-regulated drugs and devices.

As they write, the rate of results-sharing for clinical trials is fairly dismal. Some of the reasons for this go beyond researchers; for example, it’s extremely difficult to get negative results published in scientific journals. Collins and Hudson point out that another avenue exists for sharing summary results: NIH’s ClinicalTrials.gov website. But even there, less than one-third of researchers had shared results within four years of the end of their studies. Collins and Hudson are critical of this lapse in data sharing:

Without access to complete information about a particular scientific question, including negative or inconclusive data, duplicative studies may be initiated that unnecessarily put patients at risk or expose them to interventions that are known to be ineffective for specific uses. If multiple related studies are conducted but only positive results are reported, publication bias can distort the evidence base. Incomplete knowledge can then be incorporated into clinical guidelines and patient care. However, one of the greatest harms from nondisclosure of results may be the erosion of the trust accorded to researchers by trial participants and, when public funds are used, by taxpayers.

The new rules make the expectations to report some summary details about clinical trials, including adverse events, explicit. Although NIH has always encouraged sharing of summary results, the rules haven’t always been explicit. Now that there will be detailed guidance, the penalty for not complying will be harsher:

Thus, with the implementation of clearer requirements, augmented support materials and resources, and facilitated reporting, the NIH expects that investigators and sponsoring organizations will have the necessary tools to provide accurate, complete, and timely trial results submissions. However, for grantees who are subject to the amendments act and fail to comply after sufficient notification, the law is clear that NIH and other federal funders of clinical trials must then withhold further funding for the grant and any future grant to the grantee. In addition, the timely reporting of clinical trials will be taken into consideration during review of subsequent applications for funding.

The proposed changes to the regulations are currently in the public comment period, which will end in a few weeks, on February 19. After a review of the comments (and possible revisions), a final rule will likely be issued in a few months time. Once the rule goes into effect, it will be interesting to watch how this changes the research process for new NIH and FDA-regulated studies.

Previously: Shake up research rewards to improve accuracy, says Stanford’s John IoannidisRe-analyses of clinical trial results rare, but necessary, say Stanford researchersHow important is it to publish negative results?Researchers call for “democratization” of clinical trials data and A critical look at the difficulty of publishing “negative” results
Photo by U.S. Department of Defense

Big data, Cardiovascular Medicine, Chronic Disease, Research, Stanford News

Big data used to help identify patients at risk of deadly high-cholesterol disorder

Big data used to help identify patients at risk of deadly high-cholesterol disorder

Familial hypercholesterolemia is not exactly a catchy name. But Stanford cardiologist Josh Knowles, MD, is determined to make it easier to remember. This little known, high-cholesterol disease is a silent killer. If you don’t know you have it, it can strike suddenly – and years before most people ever start worrying about heart attacks.

Knowles and fellow researchers at Stanford have launched a new research project aimed at identifying people at-risk of having FH. Using “big data” research methods and software that “teaches” a computer how to recognize patterns, researchers plan to comb through electronic medical records at Stanford hospitals and, if successful, pinpoint those who might have the disease and not know it.

In a story I wrote on the new project, Knowles described how this innovative technology could potentially be used to transform health care:

Machine learning, in which computer algorithms learn to recognize patterns within data, is widely used by Internet businesses such as Amazon and Netflix to improve customer experience, get information about trends, identify likes and dislikes and target advertisements. These techniques have not been widely applied in medicine, but we believe that they offer the potential to transform health care, particularly with the increased reliance on electronic health records.

Using these methods to help identify patients with FH is a good place to start, Knowles said, since there are currently few systematic approaches to finding people with FH, and many doctors are unfamiliar with the disease. As he told me:

This disorder certainly leads to premature death in thousands of Americans each year … Less than 10 percent of cases are diagnosed, leaving an estimated 600,000 to 1 million people undiagnosed. If found early enough and treated aggressively with statin-based regimens, people can live longer, healthier lives.

The project is part of a larger initiative called FIND FH (Flag, Identify, Network, Deliver), a collaborative effort involving Stanford Medicine, Amgen Inc., and the nonprofit Familial Hypercholesterolemia Foundation to use innovative technologies to identify individuals with the disorder who are undiagnosed, untreated, or undertreated.

Previously: Registration for Big Data in Biomedicine conference now open, Hope for patients with familial hypercholesterolemia and Born with high cholesterol
Photo by Dwight Eschliman

Big data, In the News, Patient Care, Pediatrics, Stanford News

Examining the potential of big data to transform health care

Examining the potential of big data to transform health care

Updated 1-6-15: The piece also aired this week on NPR’s All Things Considered.

***

9-29-14: Back in 2011, rheumatologist Jennifer Frankovich, MD, and colleagues at Lucile Packard Children’s Hospital Stanford used aggregate patient data from electronic medical records in making a difficult and quick decision in the care of a 13-year-old girl with a rare disease.

Today on San Francisco’s KQED, Frankovich discusses the unusual case and the potential of big data to transform the practice of medicine. Stanford systems-medicine chief Atul Butte, MD, PhD, also weighed in on the topic in the segment by saying, “The idea here is [that] the scientific method itself is growing obsolete.” More from the piece:

Big data is more than medical records and environmental data, Butte says. It could (or already does) include the results of every clinical trial that’s ever been done, every lab test, Google search, tweet. The data from your fitBit.

Eventually, the challenge won’t be finding the data, it’ll be figuring out how to organize it all. “I think the computational side of this is, let’s try to connect everything to everything,” Butte says.

Frankovich agrees with Butte, noting that developing systems to accurately interpret genetic, medical or other health metrics is key if such practices are going to become the standard model of care.

Previously: How efforts to mine electronic health records influence clinical care, NIH Director: “Big Data should inspire us”, Chief technology officer of the United States to speak at Big Data in Biomedicine conference and A new view of patient data: Using electronic medical records to guide treatment

Big data, Events, Stanford News

Registration for Big Data in Biomedicine conference now open

Registration for Big Data in Biomedicine conference now open

big_data

Last spring, in a blog post on a study from Stanford systems-medicine chief Atul Butte, MD, PhD, National Institutes of Health Director Francis Collins, MD, PhD, noted that “we are at a point in history where big data should not intimidate, but inspire us.”

The theme of how large-scale data analysis and technology can inspire ways to improve disease prevention, diagnosis and treatment will take center stage at Stanford this spring for the annual Big Data in Biomedicine conference.  The event, which is co-sponsored by Stanford and Oxford University, will be held May 20-22 at the School of Medicine’s Li Ka Shing Center for Learning & Knowledge. Registration is now open on the website.

More than 40 speakers will participate in the conference, including Margaret Hamburg, MD, commissioner of the U.S. Food and Drug Administration; Nobel laureate and Stanford professor Michael Levitt, PhD; Peter Norvig, PhD, director of Research at Google; and 23andMe founder Anne Wojcicki. The three-day event will also include a technical showcase where attendees can browse displays and demos highlighting public and private companies’ innovations related to big data.

For those interested in viewing the keynotes and panel discussions from the 2014 conference, the videos are available to watch online.

Previously: Big Data approach identifies new stent drug that could help prevent heart attacks, Examining the potential of big data to transform health care, Stanford’s Big Data in Biomedicine chronicled in tweets, photos and videos and Videos of big data in biomedicine keynotes and panel discussions now available online
Photo, of 2014 conference speaker Colin Mahony, by Saul Bromberger

Big data, Cancer, Cardiovascular Medicine, Fertility, Men's Health, Research, Stanford News

Male infertility can be warning of hypertension, Stanford study finds

Male infertility can be warning of hypertension, Stanford study finds

sperm graffitiA study of more than 9,000 men with fertility problems links poor semen quality to a higher chance of having hypertension and other health conditions. The findings suggest that more-comprehensive examinations of men undergoing treatment for infertility would be a smart idea.

About a quarter of the adults in the United States (and in the entire world) have hypertension, or high blood pressure. Although it’s the most important preventable risk factor for premature death worldwide, hypertension often goes undiagnosed.

In a study published today in Fertility and Sterility, Stanford urologist Mike Eisenberg, MD, PhD, and his colleagues analyzed the medical records of 9,387 men, mostly between 30 and 50 years old, who had provided semen samples in the course of being evaluated at Stanford to determine the cause of their infertility. The researchers found a substantial link between poor semen quality and specific diseases of the circulatory system, notably hypertension, vascular disease and heart disease.

“To the best of my knowledge, there’s never been a study showing this association before,” Eisenberg told me when I interviewed him for a press release about the findings. “There are a lot of men who have hypertension, so understanding that correlation is of huge interest to us.”

In the past few years, Eisenberg has used similar big data techniques to discover links between male infertility and cancer and heightened overall mortality, as well as between childlessness and death rates in married heterosexual men.

Eisenberg sums it all up and proposes a way forward in the release:

Infertility is a warning: Problems with reproduction may mean problems with overall health … That visit to a fertility clinic represents a big opportunity to improve their treatment for other conditions, which we now suspect could actually help resolve the infertility they came in for in the first place.

Previously: Poor semen quality linked to heightened mortality rate in men, Men with kids are at lower risk of dying from cardiovascular disease than their childless counterparts and Low sperm count can mean increased cancer risk
Photo by Grace Hebert

Big data, Cancer, Health Disparities, Imaging, Public Health, Women's Health

A new way of reaching women who need mammograms

A new way of reaching women who need mammograms

black Woman_receives_mammogramI’ve taken cancer screenings for granted since I’m one of those fortunate enough to have health insurance, and it didn’t occur to me that many uninsured women were going without regular mammograms to screen for breast cancer. A story today on Kaiser Health News mentions this fact and highlights a partnership that Chicago public-health officials have forged with a company named Civis. The private company includes staffers that helped with the Obama campaign’s get-out-the-vote efforts, and then moved on to help find people eligible to enroll for health insurance through the Affordable Health Care Act. The company used its expertise to identify women who were in the right age group (over 40) and were uninsured in Chicago’s South Side area; those women then were then sent fliers about free screenings available to them.

The article describes some other cities using similar “big data” efforts for public-health purposes:

This project represents a distinctive step in public health outreach, said Jonathan Weiner, professor and director of the Johns Hopkins Center for Population Health IT in Baltimore. But Chicago is not the only city investigating how population data can be used in health programs, he added, citing New York City, Baltimore and San Diego as other examples.

“It’s a growing trend that some of the techniques first developed for commercial applications are now spinning off for health applications,” he said. So far, he said, “these techniques have not been as widely applied for social good and public health,” but that appears to be changing.

The early signs say that the new effort in Chicago, which started earlier this year, is working. One hospital saw a big jump in the number of free mammograms, from 10 a month to 31, though the full impact may not be understood for a few months. It’s not “a silver bullet” as one expert cited in the story notes, but it’s a much more precise tool than most public-health outreach programs have had access to until now.

Previously: Screening could slash number of breast cancer casesDespite genetic advances, detection still key in breast cancerStudy questions effects of breast cancer screenings on survival rates and New mammogram guidelines echo ones developed by physicians group
Photo by National Cancer Institute

Big data, Cardiovascular Medicine, Chronic Disease, Research, Science, Stanford News, Videos

Big data approach identifies new stent drug that could help prevent heart attacks

Big data approach identifies new stent drug that could help prevent heart attacks

Ziad Ali, MD, PhD, was a cardiovascular fellow at Stanford with a rather unique skill when a 6-year study published today online in The Journal of Clinical Investigation first began.

The multi-talented physician-scientist – who is now associate director of translational medicine at Columbia University Medical Center – had figured out a way to put tiny little stents into mice with clogged arteries as a PhD student.

The skill would become key as he and colleagues set out to find a better pharmaceutical for the drug-eluting stents that are used in combination with angioplasty to treat coronary artery disease. In order to prevent stent disease, the often serious medical problem caused by stents themselves, chemotherapy drugs were added to bare metal stents. But these drug-eluting stents have their own problems: The drugs work like “hitting a pin with a sledgehemmer,” as Ali describes it, often damaging the lining of the arteries which can lead to heart attacks. As a result, patients are required to take blood thinners for up to a year after the procedure to prevent clots.

“A lot of our patient population is on the elderly side with bad hips or diabetes,” Ali told me. “Once you get a drug-coated stent, you can’t have surgery for a year. And if you stop the blood thinners for any reason, you’re at risk of a stent clotting off. And that actually causes a heart attack. Stent thrombosis has a high mortality rate.”

By using a “big data” computational approach, learning about the genetic pathways involved in coronary artery disease, then testing the new theories on mice models in the lab, researchers were able to pinpoint a potential new treatment for patients: Crizotinib, a pharmaceutical approved by the FDA for treatment in certain cases of lung cancer.

“This could have major clinical impact,” Euan Ashley, MD, PhD, senior author of the study, who discusses the work alongside Ali in the video above, said.

Previously: Euan Ashley discusses harnessing big data to drive innovation for a healthier world, New computing center at Stanford supports big data, Trial results promising for new anti-clotting drug and A call to use the “tsunami of biomedical data” to preserve life and enhance health
Photo in featured entry box by Mark Tuschman

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