Personalized Health Care: Science Provides Solutions

My interest in personalized health care began approximately a dozen years ago when as Chancellor for Health Affairs at Duke University, I realized that emerging sciences and technologies were creating medical capabilities never before known. Through the power of genomics, proteomics, metabolomics, systems biology, and bioinformatics, one could begin to predict an individual’s risk for diseases, define the exact mechanism of the disease and develop targeted therapies specifically for the patient. I was enamored with the power of science to provide better solutions than the current reactive approach of treating disease events long after chronic disease has begun. As I thought more about personalized health care, however, it became obvious that while solutions from research were important, they were not sufficient for the prevention and treatment of complex diseases which require addressing personal and societal issues as well. Moreover, scientific advances might be decades off, and we could use currently available tools now until better ones become available.

This past weekend I had a striking reminder of how powerful biomedical research can be in eliminating dreaded human diseases. I attended the Annual Joint Meeting of the American Society for Clinical Investigation (ASCI) and Association of American Physicians (AAP) in Chicago to present the Kober Medal to my close friend, Dr. Robert J. Lefkowitz, a giant in biomedical research who has contributed much to our current knowledge of how receptors work. Immediately following the presentation of his medal was the delivery of talks by Drs. Brian Drucker and Charles Sawyers, this year’s recipients of the Stanley J. Korsmeyer Award. Drs. Drucker and Sawyers received this award for their groundbreaking work in developing targeted therapies for the treatment of Chronic Myelogenous Leukemia (CML), a previous fatal disease that now has a 90% cure rate. Their work is but one example of the power of basic biological research leading to applications that entirely change the face of a disease and provides a prime example of its value in fostering the personalization of care.

CML had been a uniformly fatal disease with peak instances in people in their 40s. Research going back to 1960 identified a characteristic morphologic abnormality in the white blood cells of affected patients. This abnormality was shown to be due to the translocation of parts of two chromosomes resulting in a “Philadelphia chromosome” named as such because the discoverers were at the University of Pennsylvania in Philadelphia. Subsequent research identified the specific abnormality of this translocation as being the increased expression of a protein termed BCR-ABL, a tyrosine kinase involved in the development and progression of CML. The line of research identifying BCR-ABL as the cause of CML actually began in the earlier part of the 20th Century through the discovery that certain leukemias in mice were caused by viruses and one was associated with the over expression of BCR-ABL. This research accelerated rapidly in the last ten years to lead to a miraculous therapeutic triumph. Drs. Drucker and Sawyers became aware of a drug termed Imatinib (Gleevac) that specifically inhibited the BCR-ABL tyrosine kinase. In collaboration with scientists at Novartis, Drucker and Sawyers demonstrated the ability of Imatinib to inhibit the BCR-ABL enzyme in animals as well as in the cells of individuals with CML. In a subsequent series of brilliant experiments and clinical trials, Imatinib was shown to induce remission in patients with CML. Importantly, in the small percentage of individuals that relapsed after Imatinib treatment, they showed that the cause was a mutation in the BCR-ABL protein that rendered the drug unable to block its activity. Through the development of additional inhibitors of this tyrosine kinase, even more effective therapies were developed. Importantly, the field of cancer therapy is being revolutionized by research leading to the identification of the enzymes that are associated with the growth of different cancers. Treatment is already being targeted to each individual’s needs by using drugs specifically directed at their abnormality. I can think of no better example of personalized medicine as it relates to finding the right drug for the right individual.

The Korsmeyer Award and the purpose of the ASCI/AAP are to foster physician-led biomedical research and such research plays a fundamental role in the evolution of personalized health care. I think of advances in personalized health care as having a pull and a push. The pull comes from the needs of the individual to improve their health, minimize preventable diseases, and specifically target what they need to attain the best state of health. A push comes from the capabilities made available by science and biomedical research discoveries that provide tools to meet the needs of the individual. Biomedical research provides a more precise understanding of the molecular basis of diseases and the creation of targeted therapies. It is important that we understand this bi-directional dynamic of the pull and push. The needs of the individuals provide the market for the best capabilities to address them -- a pull. Science and technology provides specific capabilities to address them -- a push. In complex chronic diseases, solutions provided by science and technology cannot alone solve all the problems patients face, but they can play a vital part in the solution.

As we envision the development of better models of personalizing health care, we must never forget the vital role played by biomedical research in providing critical tools to address an individual’s specific health needs.

Health care reform and the deficit - it's about more than dollars and cents

As Congress hashes out the details of the budget deal made late last Friday night, my husband and I are hashing out some of our own financials from my son’s hospitalization six weeks ago. It’s quite timely, considering select lawmakers’ futile attempts to defund the Accountable Care Act during the appropriations process. I’m sure no one is surprised to read that five inpatient days at Duke Children’s are costly. To the tune of $17,255. Thankfully we have good insurance through my husband’s employer, because of that $17,000+, Blue Cross/Blue Shield “allowed” $3,265.  How’s that for collective buying power? An 81% discount!

Which brings me back to this whole federal budget/deficit turned health care debate. Again.

From the White House to members of Congress, most of the players are in agreement that, as Jay Carney said yesterday, “health care spending is a major driver of our deficit and debt problem.” And still, I have yet to hear a single member of Congress or the President talk about why costs are what they are and what they want to do about it. Lately politicians seem more concerned about making a statement for the 2012 elections – who funded Planned Parenthood, who wouldn't defund the ACA – than they are about making policy that addresses the issue of how much high quality health care really costs and what high quality care actually looks like. 

Case in point: Does a 5-day pediatric inpatient stay at one of the premier academic medical institutions in the country cost $17K or $3K? And if Duke University Health System can provide said care for $3K to some, then why don’t they charge everyone $3K? I’m fairly certain health systems like Duke's aren’t actually earning profits from the patients who cannot afford health insurance, let alone a $17K bill.  In fact, I’m sure they’re actually losing more money than the “cost” of the services they provided by the time they hire creditors and bug these folks until they declare bankruptcy and not pay their bills anyway.

And I haven’t even begun to talk about what quality health care is or the idea that, if we invested in systems and technologies that support personalized prevention, we might actually make real headway in reducing how much we as individuals  – and we as taxpayers via federal health insurance programs like Medicare, Medicaid, and SCHIP – pay for health care. This will become even more of a reality as our nation becomes unhealthier and rates of obesity and associated diseases rise in children and young adults. If folks are worried how Medicare is going to handle the Baby Boomers, they haven't seen anything yet. Wait until today's youth turn 65.

I’m all for getting the deficit under control. But when it comes to health care, we can’t continue to piecemeal solutions together without addressing the larger systemic issues: personalized chronic disease prediction and prevention beginning in childhood, coordinated care across time and providers, cost containment through quality initiatives, and of course, overhaul and transparency of pricing structures. When members of Congress stay late into Friday evening to debate and negotiate these issues, then we’ll know they’re onto something worth fighting over.

In Physicians we Trust

An article on a new physician trust measure in the recent issue of Annals of Family Medicine sparked some interesting commentary from Jessie Gruman. She challenged the idea of whether this was a measure of physician “trust” or good old-fashioned doctor-say patient-do. Using her personal experience with cancer, she explains her concerns about the article’s criteria being used to evaluate her doctor’s level of trust in her.

This is an interesting example of semantics, which is something we’ve been discussing here at the Center. Just as we ask the question, “How are we defining personalized medicine?” The same question applies here. “How are we defining physician trust?” Taken out of context, the Thom et al. Physician “Trust” measure sounds exactly as Jessie Gruman describes it – at best a paternalistic, non-participatory approach. But it’s important to remember the context in which the measure was used – HIV-positive patients on opiods for chronic, non-cancer related pain. Not cancer patients. These are two very dissimilar patient populations with significant differences in the social and cultural factors influencing their health behaviors and decisions. A scale designed for HIV-positive patients with chronic pain doesn’t make sense in an oncology setting and was never proposed by the authors.

That being said, I understand Gruman's gut reaction. The title of the Thom et al. article is misleading. Instead of “Physician Trust in the Patient,” the article title could have been: “Physician Trust in the HIV-positive Chronic Pain Patient” or “Physician Assessment of Abuse Potential in Chronic Pain of HIV-positive Patients.” And the issue of patient engagement remains. Despite the challenges these providers and patients are facing – namely, risk for drug abuse and addiction – these patients still need health care where they are involved in the process. Then a question like “How confident are you that the patient will follow the treatment plan you recommend?” might read something like: “How confident are you that you and your patient can develop a treatment plan together that the patient will follow?” It’s a subtle shift, but it brings the patient into the process of his/her care. It also attends to some of Gruman’s concerns. If nothing else, this is a perfect example where being clear in our terminology makes all the difference in how we interpret, understand, and utilize scientific information. We’ve still got a ways to go.

P4 Medicine – How do we get from current practice to future progress?

In the current issue of Nature Reviews in Clinical Oncology, Stephen Friend and Leroy Hood – the man who first described predictive, personalized, preventive, and participatory medicine as “P4 medicine” emphasize that clinical trials of the future will need to be designed so they fully capitalize on P4 medicine. Specifically with the advent of high-throughput genomic medicine, Friend and Hood note that science is experiencing a paradigm shift: what we once thought were single diseases, are in reality multiple distinct molecularly defined disease states. The natural extension is that trials previously needing 10,000 patients to show a benefit will now need tens of thousands of patients to have adequate statistical power to detect the same level of benefit. Even in large academic medical centers, the authors note, it will be difficult or even impossible to rapidly accrue proportionally small patient subsets in which personalized interventions can be feasibly explored and tested. The authors suggest the use of patient driven networks to obtain the patient numbers needed for these trials.

We at the center typically think about patient-physician interaction and patient empowerment, activation, or participation when we talk about the “participatory” P of P4 medicine. Friend and Hood extend the definition of participatory to include efforts by patients to enroll themselves in networks whose goal it is to provide access to clinical trials that would otherwise be beyond the reach of single, brick and mortar institutions. Given the authors’ backgrounds, they are understandably preoccupied with the genetics and molecular aspects of such trials, but their concept still applies to models of personalized medicine that may not involve molecular data.

Even for purely non-genomic based disease models, we are beginning to appreciate the importance of individual variation in response to therapy. We already have the tools to perform personalized, risk-based prevention and treatment for many disease states using family history, biochemical markers, and patient preference. For prospective health care to reach its maximum potential in the future, we will need to develop new models that allow iterative improvements in personalization and intervention outside of current models of clinical trials. Much in the way that the physiology-based practice of medicine of the 21st century came to embrace evidence based medicine (EBM), personalized medicine will likely require some analogous, personalized equivalent to maximize its full potential . One possibility is patient driven networks as proposed by Friend and Hood. Another is novel statistical modeling that would allow us to personalize interpretation of conventional clinical trials.