Leonard Fleck presents on cancer care at annual American Society for Bioethics and Humanities conference

Last month at the 23rd Annual Conference of the American Society for Bioethics and Humanities (ASBH), Center Professor Leonard Fleck, PhD, presented on “Precision Health, Ethical Ambiguity: How Much Cancer Can We Afford to Prevent?” as part of a session on health care allocation and cost. Dr. Fleck has provided a summary of his presentation below.

“Precision medicine” and “precision health” seem to complement one another. We want an effective targeted cancer therapy for our metastatic cancer, but would rationally prefer to prevent the emergence of a life-threatening cancer–the goal of precision health. In a recent book, The First Cell: And the Human Costs of Pursuing Cancer to the Last, Azra Raza, an oncologist, argues that we are wasting tens of billions of dollars annually on extraordinarily expensive cancer therapies that yield only marginal gains in life expectancy. Raza believes these resources (not resources from heart disease or anything else) should be redirected to destroying cancer in its earliest stages, those “first cells.”

A new liquid biopsy (GRAIL) can detect 50 different cancers in very early stages by examining cell-free DNA at a cost of $800. However, 200 million anxious U.S. adults would be candidates for this test annually at an aggregate cost of $160 billion. From the perspective of health care justice, who should pay for these tests? Who should be denied access to these tests at social expense? Should only individuals with a strong family history of cancer have a moral right to this test at social expense? That would cover only 10% of cancers diagnosed in any given year.

We might say individuals known to be at elevated risk for cancer should have these tests paid for as a social expense. That would include smokers and sun worshippers at risk for lung cancer and melanoma. Would non-smokers and responsible sunscreen appliers have just cause for a grievance, i.e., paying for the irresponsible?

Would justice or efficiency require foregoing $160 billion in metastatic cancer care to pay for this preventive effort? What would a “just enough” balancing of therapeutic objectives look like? The basic economic and ethical problem is that we would be paying $160 billion annually that we knew would yield negative results more than 99% of the time. This is not obviously either a wise or just use of social resources. Moreover, this situation calls attention to the “statistical lives vs. identifiable lives” problem.

The “statistical lives” are the lives we would hope to save from metastatic cancer with the liquid biopsy test. These are nameless and faceless lives, unlike the identifiable lives that are the patients with metastatic cancer who want access to the hyper-expensive targeted therapies that might extend their lives a few months, maybe an extra year or so. In contrast, the hope is that each statistical life saved would result in extra decades of life for that individual.

A key ethical question is whether statistical lives and identifiable lives in this situation are of equal moral weight. Or are the identifiable lives with metastatic cancer more “morally worthy” of social resources because they are suffering and near dying? Or, as Raza contends, are we ethically obligated to shift resources from metastatic cancer patients (who have been effectively treated up to this point) to preventive efforts associated with liquid biopsies hoping to save more lives and life years? How do you, my currently healthy readers, think we ought to decide?

Listen: Shared Decision-Making in Colorectal Cancer Screening

No Easy Answers in Bioethics Episode 20

This episode features guests Dr. Karen Kelly-Blake, Associate Professor in the Center for Ethics and Humanities in the Life Sciences, and Dr. Masahito Jimbo, Professor in the Department of Family Medicine at University of Michigan Medical School. Drs. Kelly-Blake and Jimbo discuss their NIH-funded study known by the acronym DATES—Decision Aid to Technologically Enhance Shared Decision Making—which addressed shared decision-making, decision aids, and patient-physician communication regarding colorectal cancer screening. The two researchers provide insight into the study and its results, also reflecting on what the process of shared decision-making means to them in the present day.

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This episode was produced and edited by Liz McDaniel in the Center for Ethics. Music: “While We Walk (2004)” by Antony Raijekov via Free Music Archive, licensed under a Attribution-NonCommercial-ShareAlike License. Full episode transcript available.

About: No Easy Answers in Bioethics is a podcast series from the Center for Ethics and Humanities in the Life Sciences in the Michigan State University College of Human Medicine. Each month Center for Ethics faculty and their collaborators discuss their ongoing work and research across many areas of bioethics. Episodes are hosted by H-Net: Humanities and Social Sciences Online.

Listen: Ethics and Policy Issues of Targeted Cancer Therapies

No Easy Answers in Bioethics Episode 16

What kinds of challenges currently exist within precision medicine? This episode focuses specifically on targeted cancer therapies, featuring a discussion between Center Professor and Acting Director Dr. Len Fleck and College of Osteopathic Medicine student Stephanie Mackenzie. Dr. Fleck discusses ethics, economic, medical, and health policy issues related to these high-cost therapies. Additionally, he provides insight into how U.S. pricing models for these therapies compare with other countries.

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Health Care and Social Justice: Just Take Two Aspirin for Your Tumor If You Cannot Afford Your Cancer Care

This post is a part of our Bioethics in the News series

By Leonard Fleck, PhD

Dr. Stanley Goldfarb is the former Associate Dean of Curriculum at the University of Pennsylvania Perelman School of Medicine. In a recent Wall Street Journal opinion piece, “Take Two Aspirin and Call Me by My Pronouns,” he complained that curricula in medical schools “are increasingly focused on social justice rather than treating illness.” He goes on to say, “A new wave of educational specialists is increasingly influencing medical education. They emphasize ‘social justice’ that is related to health care only tangentially.” Really? Only tangentially?

Readers will recall Dr. Mona Hanna-Attisha, a pediatrician in Flint, Michigan. She had discovered elevated lead levels in many of her pediatric patients. She could have “stayed in her lane,” provided chelation therapy, hoped for the best, and gone home for dinner. If this is what we would have taught her during her medical education, we would have been complicit in suborning a major injustice.

Dr. Hanna-Attisha did the necessary background research, discovered that public officials had switched the source of Flint’s drinking water to save money, which, in turn, resulted in lead being leached into the drinking water. She brought her case to the media and vigorously advocated (successfully) for correcting this health hazard. She did this for the sake of the children in Flint, many not yet born. This was not tangential to her role as a physician; this was integral and essential. This was a matter of social justice. This was part of her medical education in the College of Human Medicine.

44680640861_952d805c95_c — Image description: Dr. Mona Hanna-Attisha is seated at a table smiling. Image source: University of Michigan School for Environment and Sustainability/Flickr

The practice of medicine today is suffused with social justice challenges. As we explain to our first-year medical students, the clinic is not an island of “pure caring,” isolated from the injustices that are pervasive in our health care system and governing policies. Those injustices frequently seep into clinical practice through the hands of physicians who, no doubt, see themselves as just and caring practitioners. This may sound like hyperbole, but I ask you to consider the evidence.

For the past forty years the dominant demand in health policy has been for health care cost containment. I will remind the reader that last year in the United States we spent $3.65 trillion on health care, roughly 18% of our GDP, compared to 11% of GDP in most European nations. If we ask who is responsible for spending more than 70% of those dollars, the short answer is that physicians in the clinic are the responsible agents. Physicians decide whether a patient needs surgery, which drugs to prescribe, what diagnostic tests are necessary, how much home care is needed, and so on. Consequently, if a focal point is needed for controlling health care costs, it will be physicians.

Note that cost control can be a matter of justice or injustice. In either case, physicians will have to be mindful of the justice-relevant consequences of their diagnostic or therapeutic choices. In the 1990s a number of managed care plans used “at risk” reimbursement to elicit more cost-conscious physician clinical behavior. In some cases, as much as 30% of a physician’s income could be “at risk” if they ordered too many tests. They could also earn 30% bonuses if they were especially stingy in their use of tests. Patients knew nothing of these arrangements. Income risks and opportunities such as those could readily shape physician behavior in ways that were less than just. Whether physician judgment in these circumstances would be corrupted would depend upon whether in their medical education they had had the opportunity to reflect upon such future challenges (as opposed to thoughtlessly accepting such practices as “this is the way medicine is practiced today.”)

Putting physician income at risk to control costs related to patient care is crude and obvious. More problematic are the subtle and invisible ways in which physicians control costs justly or unjustly. For example, a patient demands an MRI to rule out brain cancer when a physician is medically certain these are tension headaches. But the physician authorizes the MRI because “insurance will pay.”

If thousands of physicians are indifferent to authorizing such unnecessary care, then the costs of health insurance to employers increase. For employers at the economic margins, that cost increase may mean dropping health insurance as a benefit, thereby adding those employees to the ranks of the uninsured. From the perspective of any individual physician, this is a very remote, invisible consequence of their decisions that creates an injustice. Medical students need to know this to practice medicine justly.

Other employers will change insurance coverage to reduce their costs. They will require their employees to accept insurance with $5000 front-end deductibles. Financially less well-off workers will deny themselves that unnecessary MRI (no injustice there), but they will also deny themselves medically necessary diagnostic procedures (sometimes with deadly consequences) by not even walking into a physician’s office. Why, physicians might ask, should they as physicians be responsible for those bad decisions by patients; there was nothing to diagnose in the examining room. But maybe there was something to diagnose in society? This is sounding a bit more like the situation in Flint. Non-physicians made cost control decisions but counted on physicians to see such decisions as “merely tangential” to the practice of medicine, nothing that should concern them.

Precision medicine has generated more than 90 FDA approved genetically-targeted cancer drugs with annual costs of more than $100,000. These drugs are used with patients with metastatic disease. The vast majority of these patients will gain no more than extra months of life from these drugs, not extra years (though clever media campaigns create a very different impression). For most workers, their health plan will require a 20-30% co-pay for these drugs, which is unaffordable for most workers. Financially well-off managers and executives will be able to afford those co-pays, which means that workers who could not afford the co-pays will have contributed through their premiums to subsidizing that other 70-80% for the well-off. Is that fair? Is that just?

Should physicians caring for these patients silently acquiesce to these insurance arrangements as “too tangential” to medical practice, too far removed from the clinic? Should we, as teachers of future physicians, also silently acquiesce so that more curricular time can be allocated to understanding the mechanisms of action of the next 90 FDA approved targeted cancer therapies? WWHAD: What Would Dr. Hanna-Attisha Do?

Leonard M. Fleck, PhD, is Acting Director and Professor in the Center for Ethics and Humanities in the Life Sciences and Professor in the Department of Philosophy at Michigan State University.

Join the discussion! Your comments and responses to this commentary are welcomed. The author will respond to all comments made by Thursday, October 24, 2019. With your participation, we hope to create discussions rich with insights from diverse perspectives.

You must provide your name and email address to leave a comment. Your email address will not be made public.

More Bioethics in the News from Dr. Fleck: Medicare For All: This Is Going to Hurt; Greed Is God: The Divine Right to Avaricious Drug Pricing; Gene Editing: God’s Will or God’s Won’t

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Dr. Fleck presents at Centre for Cancer Biomarkers Symposium in Norway

Leonard Fleck photo Center Professor Dr. Len Fleck recently traveled to Bergen, Norway to present a keynote address at the 6th Annual Centre for Cancer Biomarkers (CCBIO) Symposium. Dr. Fleck’s presentation, “Just Caring Challenges: Visible Biomarkers and Invisible Rationing,” addressed some of the critical ethical issues related to the use of biomarkers in cancer research and clinical care.

Dr. Fleck addressed two main problems in his lecture. First, the ragged edge problem. One of the primary purposes of finding biomarkers is to determine whether a cancer drug is likely to be effective for a particular metastatic cancer patient. However, rarely will a biomarker yield a simple answer. Most often, the biomarker will be expressed along a continuum. If a drug were very inexpensive and side effects tolerable, it would be easy to say that the ethically right choice would be to respect patient autonomy. But these drugs all cost more than $100,000 for a course of treatment. Consequently, if a drug has a 20% chance of having a beneficial effect, there is a conflict between considerations of justice and respect for patient autonomy. Invisible rationing (just not offering the drug to the patient) can bypass this conflict, but invisible rationing is ethically problematic so far as justice is concerned.

Secondly, recent liquid biopsies can identify eight common cancers at a very early stage–in the form of circulating cancer cells in the blood–at a cost of $500. However, the critical question would need to be raised: How often would 170 million adults (all anxious about cancer) in the U.S. have a just claim to access that test? Every six months? Every year? Note that each such offering of that test to that population would cost $85 billion. Would that represent either a just or prudent use of health care resources?

The CCBIO symposium was well-attended by an international mix of junior and senior researchers and scholars. Dr. Fleck had the opportunity to meet with many European researchers to discuss their respective work in the field of cancer research.

Dr. Fleck also gave a public lecture at the University of Bergen’s Centre for the Study of the Sciences and the Humanities, titled “Precision Medicine, Ethical Ambiguity: Rough Justice, Ragged Edges.” Dr. Fleck addressed precision medicine as it currently exists, in particular the costly FDA-approved targeted cancer therapies. Treatments for patients with metastatic cancers, which are not curative, can cost $100,000 to $475,000 per treatment course. For example, 30% of patients who are candidates for CAR T-cell immunotherapy will not gain more than an extra year of life. As things are now, we do not know before the fact who those patients might be. But one goal of biomarker research is to identify before the fact who those marginal responders most likely will be, so that we could save money by denying those patients access to this therapy. As a citizen of a just and caring society, would you endorse the research to accomplish that result? Why or why not? This is what Dr. Fleck calls “rough justice.”

Can Big Data and AI Improve End-of-Life Care?

This post is a part of our Bioethics in the News series

By Tom Tomlinson, PhD

A recently reported study claims to more accurately predict how much longer patients will live. Researchers at Stanford University assigned a neural network computer the task of training itself to develop an artificial intelligence model that would predict if a patient would die within 3-12 months of any given date. The computer trained on the EMR records of 177,011 Stanford patients, 12,587 of whom had a recorded date of death. The model was validated and tested on another 44,273 patient records. You can find the wonky details here.

The model can predict with 90% accuracy whether a patient will die within the window.

Now this is a lot better than individual physicians typically do. It’s not just that such predictions are fraught with uncertainty, given how many complex, interacting factors are at work that only a computer can handle. If uncertainty were the only factor, one would expect physicians’ prognostic errors to be randomly distributed. But they are not. Clinicians overwhelmingly err on the optimistic side, so the pessimists among them turn out to be right more often.

The study takes accurately predicting death to be a straightforwardly useful thing. It gives patients, families and clinicians more reliable, trustworthy information that is of momentous significance, better informing critical questions. Will I be around for my birthday? Is it time to get palliative or hospice care involved?

The study’s authors are particularly hopeful that the use of this model will prompt more timely use of palliative care services, and discourage overuse of chemotherapy, hospitalization, and admission to intensive care units in the last months of life—all well-documented problems in the care of terminally ill people, especially those dying of cancer. So this is a potentially very significant use of “big data” AI research methods to address major challenges in end-of-life care.

But making real progress toward these goals will take a lot more than this model can deliver.

36302888621_ad3b5fc2e1_h — Image description: A graphic on a blue gradient background shows the silhouette of an individual in the foreground containing colorful computer motherboard graphics. In the background are silhouettes of twelve more individuals standing in a line and containing black and white computer motherboard graphics. Image source: Maziani Sabudin/Flickr Creative Commons.

The first question is how it could inform decisions about what to do next. The limitation here is that the model uses events from my medical history occurring prior to the time it’s asked to predict my survival. Perhaps the decision I’m facing is whether to go for another round of chemotherapy for metastatic cancer; or whether instead to enter a Phase 3 clinical trial for a new therapeutic agent. The question (one might think) is what each option will add to my life expectancy.

Now if the training database had some number of patients who took that particular chemotherapy option, then that factor would have somehow been accounted for when the computer built the model. Assuming the model reliably predicted the mortality of those earlier patients, all we’d need to do is add that factor to my medical record as a hypothetical, run the model again, and see whether the prognosis changed.

But is there something about the chemotherapy being offered that is different than the regimens on which the computer trained? Then the model will not be able to assess the significance of that difference for the patient’s survival. Obviously, this limitation will be even more radical for the experimental treatment option. So in the individual case, the model’s helpfulness in making prospective treatment decisions could be quite limited. It would have to be supplemented, or even supplanted, by old-fashioned clinical judgment, or alternative algorithmic prognostic tools.

This may be one reason the study authors imagine a different use: identify patients with 3-12 months life expectancy and refer them for a palliative care consultation. The idea is to push against the tendency already noted for physicians to wait too long in making palliative care or hospice referrals. Assuming the model is running all the time in the background, it could trigger an alert to the attending physician, or even an automatic palliative care referral for all those the model flagged.

Now, in my ethics consultation experience, getting an appropriate palliative care or hospice referral only one month preceding death would be a stunning accomplishment, let alone three months prior. But the key word here is “appropriate,” since the need for palliative care is not dictated by life-expectancy alone, but more importantly, by symptoms. Not every patient with a projected life expectancy between 3 and 12 months will be suffering from symptoms requiring palliative care expertise to manage. Automatic referrals requiring palliative care evaluations could overwhelm thinly-staffed palliative care services, drawing time and resources away from patients in greater need.

Part of the problem here is the imprecision of the model, and the effects this may have on patient and provider acceptance of the results. A 90% chance of death within 3-12 months sounds ominous, but it leaves plenty of wiggle-room for unrealistic optimism: lots of patients will be confident that they are going to fall at the further end of that range, or that they will be among the 10% of cases the model got wrong altogether. And it’s not just patients who will be so affected. Their treating physicians will also be reluctant to conclude that there is nothing left to do, and that everything they did to the patient before has been in vain. Patients aren’t the only ones prone to denial.

And the nature of the AI-driven prognosis will make it more difficult to respond to patient skepticism with an explanation anyone can understand. As the authors point out, all we really know is that the model can predict within some range of probability. We don’t know why or how it’s done so. The best we can do is remove a feature of interest from the data (e.g., time since diagnosis), rerun the model, and see what effect it has on the probability for the patient’s prognosis. But the model offers no reasons to explain why there was a change, or why it was of any particular magnitude. The workings of Artificial Intelligence, in other words, are not always intelligible. Acceptable explanations will still be left to the clinician and their patient.

Tom Tomlinson, PhD, is Director and Professor in the Center for Ethics and Humanities in the Life Sciences, College of Human Medicine, and Professor in the Department of Philosophy at Michigan State University.

Join the discussion! Your comments and responses to this commentary are welcomed. The author will respond to all comments made by Thursday, March 8, 2018. With your participation, we hope to create discussions rich with insights from diverse perspectives.

You must provide your name and email address to leave a comment. Your email address will not be made public.

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Dr. Fleck presents at Great Lakes Biorepository Research Network annual scientific meeting

Leonard Fleck photo Center Professor Len Fleck, PhD, was a keynote speaker at the Great Lakes Biorepository Research Network (GLBRN) Annual Scientific Meeting, held at Beaumont Hospital-Royal Oak Campus on November 3. The title of Dr. Fleck’s presentation was “Precision Medicine, Ethical Ambiguity,” summarized below.

What is precision medicine? A short answer would be getting beyond “one size fits all” drug therapy, with all the side effects and misfits that implies (e.g. traditional chemotherapy). Instead, medicine would stratify patients with a specific disease, such as some cancer, into subgroups so that therapy could be tailored to the specific genetic features of their cancer. The overall goal is to maximize the beneficial effects of an available therapy for a specific patient, minimize debilitating or dangerous side effects, and save money for the health care system. How could there be ethical problems with goals such as that?

The most significant problem relates to health care justice, the fair distribution of access to the fruits of precision medicine. The basic problem is that these targeted cancer therapies are extraordinarily expensive. More than 70 of these cancer drugs have been approved by the FDA since 2000.

Cost: $70,000–$200,000+ for a course of treatment.
- One form of combination therapy is priced at $86,000 per month.
- Kymriah for Acute Lymphocytic Leukemia (ALL) is priced at $475,000 for a one-time treatment.
None of these drugs is curative.
Median gains in life expectancy for patients is measurable in weeks or months for the most part.
Several hundred more such drugs are in the pipeline.
Fojo and Grady have pointed out that these drugs yield incremental cost-effectiveness ratios (ICERs) of several hundred thousand dollars to more than a million dollars per Quality-Adjusted Life Year (QALY).

Imatinib (Gleevec) was approved in 2001 for the treatment of Chronic Myelogenous Leukemia (CML). It is extraordinarily effective for the 70% of these patients who have survived at least ten years beyond diagnosis. It was priced at $36,000 per year in 2001, and must be taken indefinitely. In 2016 imatinib was priced at $146,000, even though nothing at all changed with regard to the drug itself. Another drug, Iclusig, was priced at $120,000 for a year in 2015. In 2016 the price was raised to $200,000. We will pass over in stunned silence at the obvious ethical issues here.

As a society that seeks to be just and caring in meeting health care needs we struggle to identify the ethical norms that should govern access to these targeted cancer therapies. Keep in mind that these drugs are for metastatic cancer, almost always a terminal diagnosis. Consequently, we often appeal to inchoate (and problematic) ethical intuitions. We appeal to the “rule of rescue,” “last chance therapies,” “the pricelessness of human life,” and the “visibility of desperate patients,” all of which seem to generate an ethical obligation to fund access to these targeted therapies. Unfortunately, that obligation runs out of ethical steam once insurance runs out. In health care, our sense of obligation has evolved to select for money.

Some sad conclusions: (1) No moral theories or “compelling” moral arguments are going to yield clearly satisfactory ethical resolution to these allocation/ priority-setting challenges. Not just cancer counts (ethically speaking). (2) Ultimately, given limited resources (money) for meeting unlimited health care needs we will have to rely upon fair and legitimate processes of rational democratic deliberation constrained by relevant clinical evidence and broadly endorsed considered judgments of health care justice. (3) For the foreseeable future, precision medicine will remain infected with clinical uncertainty, ethical ambiguity, disingenuous politicking, and byzantine economic accounting (not to mention pharmaceutical philandering).

Just Caring: Health Reform, Cost Control, and the Fate of Children with Life-Altering Illnesses

Leonard Fleck photo Center Professor Dr. Leonard Fleck recently gave a keynote address at the 2017 Pediatric Bioethics Day at Norton Children’s Hospital in Louisville, KY, held on September 20.

Titled “Just Caring: Health Reform, Cost Control, and the Fate of Children with Life-Altering Illnesses,” Dr. Fleck’s talk started out with a short string of cases related to children with life-altering illnesses. He brought up the Jimmy Kimmel case (recently born infant with hypoplastic left heart syndrome), in part because a very explicit connection was made with the House-approved repeal of the Affordable Care Act (ACA). He also brought up childhood cancer cases, some capable of being effectively addressed by contemporary medicine, others not capable of being effectively addressed but raising ethics issues related to cost/health care justice as well as unnecessary harms related to aggressive treatment.

Dr. Fleck painted a statistical picture of the very large problem of escalating health care costs in the U.S., primarily as background for better understanding the “big picture” behind the problem of health care justice. He introduced seven different conceptions of justice, which are all part of our everyday understanding of how resources ought to be distributed fairly. The basic question we are seeking to answer would be this: What are the just claims to limited health care resources for children who have a broad range of expensive health care needs, the outcomes of which might vary considerably and have significant uncertainty attached to them?

Dr. Fleck reviewed a few elements of the ACA that were directly relevant to the fate of children with life-altering illnesses. For example, what effect has Medicaid expansion had on these children in the different states? Or what effect has the pre-existing condition clause of the ACA had on children with life-altering illnesses (forbidding insurance companies from discriminating against such children, either as children or future possible adults)?

Dr. Fleck then critically examined the American Health Care Act as passed in the House, and then the Senate counterpart of that bill. He addressed what he saw as the key injustices in those bills, the biggest being that it would achieve cost control largely through practices that were forms of invisible rationing (something he has written about extensively). Likewise, Dr. Fleck assessed the implications of the contraction of Medicaid for children with life-altering illnesses. This included the corruption of protections for pre-existing conditions and the inadequacy of state-based “high risk” pools allegedly as adequate protection of the health care rights and needs of such children.

Finally, Dr. Fleck discussed precision medicine in relation to cancer in children, keeping in mind the very high cost of these targeted therapies and the limited (marginal) success that has largely been true, especially in relation to solid cancers. There has been a lot of half-truths and hyperbole in this regard. There are in fact many extremely costly drugs for children with a range of life-threatening problems: some very effective, some not. Dr. Fleck used examples such as hemophilia (especially Factor VIII resistant), Gaucher, cystic fibrosis, Pompe, Fabry, Duchenne, etc. In this connection Dr. Fleck wanted to tease out the ethical challenges: If we cannot afford or justify doing EVERYTHING medically possible for all these children, then how should priorities be justifiably set? What should be the role of rational democratic deliberation in addressing these justice-relevant issues? Is bedside rationing ever morally justifiable in these circumstances? If so, how would we distinguish just bedside rationing from unjust bedside rationing decisions?

Chapter from Dr. Fleck published in ‘Cancer Biomarkers: Ethics, Economics and Society’

Leonard Fleck photo A chapter from Center Professor Dr. Leonard Fleck has been published in the book Cancer Biomarkers: Ethics, Economics and Society, published by Megaloceros Press. Dr. Fleck’s chapter is titled “Just Caring: Precision Medicine, Cancer Biomarkers and Ethical Ambiguity.” The book is edited by Anne Blanchard and Roger Strand.

From the Amazon description:

Cancer care is undergoing a shift from a ‘one-size-fits all’ approach to more personalised medicine. One way of personalising cancer treatments is through biomarkers: molecules or biochemical changes found in the patient’s tissues and body fluids. This book reflects upon the promise of cancer biomarkers and asks questions such as: How may the complexity of cancer biology impede the robustness of biomarkers in the clinic? How should one draw the line between the various sub-groups of patients for personalised treatment? How can one evaluate the cost-effectiveness and fairness of personalised cancer treatments? By bringing together authors from the fields of science and technology studies, medical ethics and philosophy, health economics and oncology, the book aims to give a critical yet accessible overview of some of the key social, ethical and economic issues that surround cancer biomarkers. “The book should be required reading for oncologists, medical students, graduate students and especially for those who make policy decisions regarding the use and reimbursement of cancer biomarkers.” – Bruce Zetter, Charles Nowiszewski Professor of Cancer Biology in the Department of Surgery, Harvard Medical School

Correlates of Patient Intent and Preference on Colorectal Cancer Screening

Karen Kelly-Blake photo Center Assistant Professor Dr. Karen Kelly-Blake is a co-author of an article in the April 2017 issue of the American Journal of Preventive Medicine. The article, “Correlates of Patient Intent and Preference on Colorectal Cancer Screening,” is co-authored by Masahito Jimbo, MD, PhD, MPH, Ananda Sen, PhD, Melissa A. Plegue, MA, Sarah T. Hawley, PhD, MPH, Karen Kelly-Blake, PhD, Mary Rapai, MA, Minling Zhang, BS, Yuhong Zhang, BS, and Mack T. Ruffin IV, MD, MPH.

From 2012 to 2014, a total of 570 adults aged 50–75 years were recruited from 15 primary care practices in Metro Detroit for a trial on decision aids for colorectal cancer screening. The article discusses the results of that trial. The full article text is available on the ScienceDirect website (MSU Library or other institutional access may be required to view this article).

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