Precision medicine is ‘personalized, problematic, and promising’

Precision medicine is ‘personalized, problematic, and promising’.
From the  10 July 2015 University of Pennsylvania news release

Since President Barack Obama’s State of the Union Address in January 2015, the nation has been talking about a revolution in patient care, known by many as precision medicine.

Of course, the country is used to hearing the president talk about health care, especially the Affordable Care Act. But when the White House starts launching $215 million initiatives to accelerate research—in this case, the Precision Medicine Initiative, according to a White House Press release—you can be sure it’s not just a passing fad.

First, what is precision medicine?

Precision medicine is about tailoring treatments to the patient’s genome and body function. The promise is that this detailed personal health data can determine what’s most effective for each individual, which can lead to better outcomes.

Most of precision medicine’s application currently focuses on cancer. Launched in 2013, Penn Medicine’s Center for Personalized Diagnostics (CPD) helps oncologists determine the best treatment for their cancer patients by looking at the cancer’s genome.

Here’s how precision medicine is being practiced at Penn:

1. A patient is diagnosed with cancer.
2. If the cancer involves a solid tumor—like breast, lung, or colon cancer—the tumor is surgically removed during a biopsy, and a chunk of the tissue is sent to Penn Medicine’s CPD. If the cancer involves blood or bone marrow—like leukemia—a sample of the blood or bone marrow is sent.
3. The CPD sequences a panel of genes that are known to be involved in cancer. This test examines DNA within the tumor, blood or bone marrow sample. The goal is to find DNA mutations that are driving the cancer.
4. A report on the mutations found is sent to the patient’s oncologist.
5. The oncologist determines if there are therapies or treatments available that work better than others—or not at all—on the patient’s particular type of cancer.

“We’re using precision medicine to give patients the right drugs, guided by the DNA sequence information from their cancer, so we’re not exposing them to potentially toxic effects,” explains David Roth, MD, PhD, director of the CPD. “This individualized therapy is better than treatment based on the ‘average patient.’”

Precision Medicine is being researched, translated and applied across Penn Medicine. Here,
experts from the Center for Personalized Diagnostics share four predictions on how precision medicine will change how cancer is treated in future generations.

1. Cancer will be diagnosed earlier.

Jennifer Morrissette, PhD, clinical director of the CPD:

“There are different stages of tumors. The earlier you catch the tumor, the more likely you are to survive it. My theory is that this century will be the century of diagnostics. We will be diagnosing people’s cancers earlier and earlier.

“That way, we are not dealing with advanced metastatic tumors that have acquired so many different changes that they’re hard to treat. We’ll be capturing tumors very early, in stage one; have a definitive surgery; follow the patient for a certain number of years to make sure that the cancer hasn’t spread; and then they’ll be cured.

“Some people put off seeing a physician because they don’t want chemo, but the longer they put it off, the more likely they are going to have metastatic disease.”

2. Cancer treatment will be based on each person’s health profile.

David Roth, MD, PhD, director of the CPD:

“[In the past,] doctors had been treating [the average patient] based upon results from a large study.

“The revolution in precision medicine is that now we have better tools to understand what’s going on with you as an individual. Instead of saying, ‘Okay, you have this particular cancer, and you have a 30 percent chance. So, go ahead and get this toxic therapy,’ we can be much more specific.

“If we were able to tell you that you have a five percent chance of responding to a chemotherapy based on the makeup of your tumor, would you still do it?”

3. Gene paneling will be used for diagnosis, not just treatment.

David Lieberman, MS, CGC (certified genetic counselor):

“We tend to see certain genes mutated in certain cancers. For example, there is a certain set of
genes [that are] typically mutated in lung cancer or another set in lymphoma.

“It is not always clear using historical methods what type of cancer a patient has. This makes treatment decisions challenging. Sequencing the tumor’s DNA on a panel of known cancer-related genes may help clarify the cancer’s origin and, in this way, assist the clinician in determining treatment or prognosis.”

$215 million: The amount the White House will invest in the Precision Medicine Initiative in 2016
Source: WhiteHouse.gov

4. More cancer patients will have a treatment team, rather than just an       oncologist.

Jennifer Morrissette PhD, clinical director of the CPD:

“It’s not going to be one physician making all the decisions. Cancer treatment has gotten much more complex. Because of the availability of multi-gene testing, you need a group of people with different types of expertise to make the best decision for a patient.

“In addition to the team directing care for the appropriate approach—whether it’s surgery, radiation, chemotherapy, pain management—now there is also the genetic component.

“[The team’s] able to sit in a room with people from the lab who can talk about what the result means, have the oncologist tell them about the patient and then get the clinical geneticist’s notion that there may be an inherited predisposition. Then, they walk out with a consolidated treatment plan for that patient.”

The future of medicine

For more than 250 years, advancements like “precision medicine” have been the hallmark of Penn Medicine. As the first school of medicine in the United States, it has been and continues to be a place where the future of medicine and the future leaders in medicine are being developed.

[Reblog] Will Getting More Granular Help Doctors Make Better Decisions?

From the 8 February 2015 post at The Health Care Blog

Will Getting More Granular Help Doctors Make Better Decisions?

Excerpt (longish post)

But, there are many things that data will never do well.  For certain things, physician heuristics may lead to better decisions than any predictive model.

Heuristics are shortcuts, based on experience and training that allow doctors to solve problems quickly.  They are pattern maps that physicians are trained to recognize. But, heuristics have a reputation for leading to imperfect answers: Wikipedia notes that heuristics lead to solutions that “(are) not guaranteed to be optimal, but good enough for a given set of goals…. (they) ease the cognitive load of making a decision.”  Humans use them because we simply can’t process information in sequential binary fashion the way computers do.

It would be a mistake to call heuristics a sad substitute for big data.  Some cognitive scientists have made the argument, and I think they’re right, that heuristics aren’t simply a shortcut for coming to good-enough answers. For the right kinds of problems, heuristically generated answers are often better than the those generated by computers.

How can this be?

I often think of the following cartoon in Randall Munroe’s superb recent book, What If? Serious Scientific Answers to Absurd Hypothetical Questions.  In trying to compare human and computer thinking, he rightly notes that each excels at different things.  In this cartoon, for example, humans can quickly determine what they thought happened.  Most people can tell you that the kid knocked over the vase and the cat is checking it out, without going through millions of alternate scenarios.  Monroe notes that most computers would struggle to quickly come to the same conclusion.

So, from the perspective of an emergency doctor, here are the three leading problems with the applied use of complex analytics in the clinical setting:

• 1. The garbage in, garbage out problem.  In short, humans regularly obfuscate their medical stories and misattribute causality. You need humans to guide the patient narrative and ignore red herrings.

• 2. If we want to be able to diagnose, screen and manage an ER full of runny-nosed kids with fevers, we simply can’t afford the time it takes for computers to sequentially process millions of data points. The challenge is at one simple and nuanced: allowing 99% of uncomplicated colds to go home while catching the one case of meningitis. It’s not something that a computer does well: it’s a question of balancing sensitivity (finding all true cases of meningitis among a sea of colds) and specificity (excluding meningitis correctly) and doctors seem to do better than computers when hundreds of cases need to be seen a day.

• 3. There is a problem with excess information, where too much data actually opacifies the answer you’re looking for. Statisticians call this “overfitting” the data. What they mean is that as you add more and more data points to an equation or regression model, the variability of random error around each point gets factored in as well, creating “noise”. The more variables, the more noise.

The paradox is that ignoring information often leads to simpler and ultimately better decisions.

…

Related articles

• It takes more than great algorithms to make personalization work
• Sanjay Bakshi: Daniel Kahneman vs Gary Klein

[Reblog] What happens to medicine when it has no heroes?

What happens to medicine when it has no heroes?.

From the 4th December 2013 KevinMD article  by A COUNTRY DOCTOR, MD |

A few years ago, a medical journal piece about electronic medical records with built-in decision support announced that the days of super-physicians and master diagnosticians were over.

Being a doctor isn’t very glamorous anymore, and being a good one seems rather obsolete with so many guidelines and protocols telling us what to do.

A hundred years ago, William Osler, a practicing physician, had single-handedly written the leading textbook of medicine, reformed medical education, helped create and chaired Johns Hopkins and become the chair of medicine at Oxford.

Today, it is virtually necessary to be a researcher to teach at a university, let alone chair a medical school. The only other way to advance in medicine is to go into administration. Leaders in medicine are not chosen for their mastery of clinical practice, but for their managerial or business acumen.

The culture of clinical excellence has few heroes in our time. Pharmaceutical companies sometimes speak of “thought leaders” on the local level, which is more often than not only their way of building momentum for their drug sales through promoting early adoption of new medicines. Doctors today practice on a level playing field, where we are considered interchangeable providers in large organizations and insurance networks. Media doctors don’t earn their position based on clinical mastery, but rather their communication and self promotion skills.

What happens to medicine when it has no heroes? Who defends the ideals of a profession that is becoming commoditized? What keeps new physicians striving for clinical excellence with only numerical quality metrics and policy adherence as yardsticks? How are the deeper qualities of doctoring preserved for new generations of doctors, and how are they kept in focus with all the distractions of today’s health care environment — because people still worry and suffer; they are more than bodies with diseases or abnormal test results.

Every day, doctors on the front lines treat two dozen fellow human beings with every imaginable condition. How do we carry on, with only our own ideals as beacons in the fog, if we are left to ourself to defend our higher purpose, without champions, mentors, or heroes?

“A Country Doctor” is a family physician who blogs at A Country Doctor Writes:.

Related articles

• Bringing emotions back into medicine (kevinmd.com)
• [Reblog] In Medicine, More May Not Be Better (jflahiff.wordpress.com)
• “Relationship Is Everything” MED Grads Told (bu.edu)

The High Cost of Not Listening to Patients.

This article reminds me of my days as a medical librarian.
If I did not carefully listen to a patron (customer) or ask the right questions, I gave the person the wrong information!

Minutes spent in listening and asking focused questions often saved an hour (or more!) of fruitless searching.

So, when I talk with a health care practitioner, I am mindful to give as much relevant information as possible to so the proper diagnosis and treatment can be given!

It is also necessary that we all do whatever we can so that health care practitioners are given the time they need to listen to patients.
Ultimately this will result in lower health care costs overall.

 

From the 18 January 2013 post at The Health Care Blog

Before we can understand the high cost of not listening, we need to examine in detail the diagnostic process. I am limiting my discussion to patients with chronic or recurring symptoms lasting several months. I am not discussing acute illnesses. They fall into completely different category.

At the front line of medical care, at the first contact between a patient and a doctor, the patient describes physical symptom. Whatever the real underlying cause, a physical symptom is the required ticket to see a physician. The physician, on first contact, has no idea what the underlying nature of the patient’s chronic complaint really is.  At the risk of oversimplifying, there are five broad categories of the causes for complaints.

These are:

1. There is a definable medical disease in one or more organs.

2. There is no definable medical disease but the patient is in contact with an unknown toxic substance causing the symptom (inhaled, ingested, or from skin contact).

3. The patient is in a stressful or toxic relationship at home or work producing physical symptoms or even a definable medical disease. (“What the mind cannot process is relegated to the body.” Dr. William Mundy, psychiatrist, personal communication. )

4. The patient or a companion is inflicting harm. Here, there are several categories:…

 

…

5. There is no definable medical disease but the patient has assumed a chronic illness role in life with multiple symptoms (i.e. hypochondriasis).

Psychosomatic Illness

6. There is a sixth category; patients with psychosomatic disorders. Time and space does not permit a full discussion of this important and very common set of disorders. I suspect they represent more than fifty percent of patients seeking primary medical care. The book“The Divided Mind” explains and defines these disorders and the successful treatment applied to thousands of patients at NYU by Dr. Sorno and his colleagues. At present the medical profession denies the existence of this category. The epidemic emergence of pain clinics comes from lack of knowledge about psychosomatic disorders and their proper treatment.

Of course, the patient can have any of these, and also be suffering from a definable medical disease.

But my experience in primary care over the past 55 years — combined with studies in the medical literature —suggest that between 30 and 40 percent of first contact  primary care visits are stress related or are psychological in nature (#3 and #6  in above list).

It should be obvious that the only way to sort out these causes of symptoms requires very careful listening to the narrative of the patient’s life. Some of these causes can be determined only by listening…..

 

Read the entire article here

[Article Summary] 1 In 3 Americans Uses Internet To Help With Diagnoses



From the 15th January 2013 article at Medical News Today

A nationwide survey ***of US adults finds that 1 in 3 of Americans say they have used the internet to help them diagnose a medical condition, either for themselves or someone else. But, when asked who they turned to for help with a serious health issue, either online or offline, the majority said they turned to a doctor or other health professional…

…when these “online diagnosers” were asked who they turned to for information, care or support the last time they had a serious health problem, either online or offline:

• 70% said they got it from a health professional,
• 60% turned to family and friends, and
• 24% said they got it from others with the same condition.

When the survey asked online diagnosers if the information they found online had led them to think they needed to see a doctor, 46% said yes, while 38% said they could take care of it themselves and 11% said it was a case of both or something in between.

Read the entire article here

Related articles

• Internet Is First Stop for Many Ill People, Study Finds (mashable.com)
• 1 in 3 adults search online for medical diagnosis (cbc.ca)
• ‘Doctor Google’ Isn’t Replacing Actual Doctors Any Time Soon (betabeat.com)

***The full Pew Internet report Health Online 2013 may be found here

Vinod Khosla: Technology Will Replace 80 Percent of Docs

An astonishing proposal.

Yes, computer algorithms are great tools, but they are just that, tools. These tools are only as good as the data and algorithms they include. Our understanding of diseases and diagnosing is not static. Hence these tools will always be imperfect.
Furthermore, I do not believe the workings of the human body can be reduced to algorithms. Individuals are more than the sum of their parts. The relationship between diseases/conditions and wellness is a bit more nuanced than “solving” a problem. Case in point is the relationship of microbes in the gut and how they affect our immune system.

This article so far has drawn 60 comments..many very worth the time of reading.

From the 31 August 2012 post at The Health Care Blog

 I recently viewed health care through the lenses of a technology entrepreneur by attending the Health Innovation Summit hosted by Rock Health in San Francisco. As a practicing primary care doctor, I was inspired to hear from Andy Grove, former CEO of Intel, listen to Thomas Goetz, executive editor of Wired magazine, and Dr. Tom Lee, founder of One Medical Group as well as ePocrates.

Not surprising, the most fascinating person, was the keynote speaker, Vinod Khosla, co-founder of Sun Microsystems as well as a partner in a couple venture capital firms.

“Health care is like witchcraft and just based on tradition.”

Entrepreneurs need to develop technology that would stop doctors from practicing like “voodoo doctors” and be more like scientists.

Health care must be more data driven and about wellness, not sick care.

Eighty percent of doctors could be replaced by machines.

Khosla assured the audience that being part of the health care system was a burden and disadvantage.  To disrupt health care, entrepreneurs do not need to be part of the system or status quo. He cited the example of CEO Jack Dorsey of Square (a wireless payment system allowing anyone to accept credit cards rather than setup a more costly corporate account with Visa / MasterCard) who reflected in a Wired magazine article that the ability to disrupt the electronic payment system which had stymied others for years was because of the 250 employees at Square, only 5 ever worked in that industry.

Khosla believed that patients would be better off getting diagnosed by a machine than by doctors. Creating such a system was a simple problem to solve. Google’s development of a driverless smart car was “two orders of magnitude more complex” than providing the right diagnosis. A good machine learning system not only would be cheaper, more accurate and objective, but also effectively replace 80 percent of doctors simply by being better than the average doctor. To do so, the level of machine expertise would need to be in the 80th percentile of doctors’ expertise.

Is it possible technology entrepreneurs can disrupt health care? He challenged any doctor in the room to counter his points.

Silence.

Was it because everyone agreed? Were the doctors in the room simply stunned? Was there a doctor in the house? And where did he get that 80 percent statistic?…

Related articles

• Why I Disagree With Vinod Khosla About Digital Health — And Hope He Succeeds Brilliantly(Forbes)

• Vinod Khosla says technology will replace 80 percent of doctors – sparks indignation (venturebeat.com)
• Tech VC: Machines can learn up to 80 percent of what doctors do, replace healthcare voodoo (medcitynews.com)
• Vinod Khosla: Technology Will Replace 80 Percent of Docs (thehealthcareblog.com)
• Topol says machines will be vital to healthcare transformation, new doc-patient partnership (medcitynews.com)
• Sun daddy: ‘Machines will replace 80 per cent of doctors’ (go.theregister.com)
• Vinod Khosla: Maintain the Silicon Valley Vision (iamvictorio.us)

Better medicine, brought to you by big data through new types of data analysis

 

A good overview of how improved data analysis and presentation is improving health care delivery.

I especially liked the slideshare presentation found below in Related Articles.
The 42 slides in Big data – a brief overview outlines what big data is, its sources and processes, how it is analyzed, current “players”,examples, market analysis, future, and opportunities.

From the 15 July 2012 blog post at Gigaom

Slowly but surely, health care is becoming a killer app for big data. Whether it’s Hadoop, machine learning, natural-language processing or some other technique, folks in the worlds of medicine and hospital administration understand that new types of data analysis are the key to helping them take their fields to the next level.

Here are some of the interesting use cases we’ve written about over the past year or so, and a few others I’ve just come across recently. If you have a cool one — or a suggestion for a new use of big data within the healthcare space — share it in the comments:

Genomics. This is the epitomic case for big data and health care. Genome sequencing isgetting cheaper by the day and produces mountains of data. Companies such asDNAnexus, Bina Technologies, Appistry and NextBio want to make analyzing that data to discover cures for diseases faster, easier and cheaper than ever using lots cutting-edge algorithms and lots of cloud computing cores.

BI[definition of business intelligence] for doctors. Doctors and staff at Seattle Children’s Hospital are using Tableau to analyze and visualize terabytes of data dispersed across the institution’s servers and databases. Not only does visualizing the data help reduce medical errors and help the hospital plan trials but, as of this time last year, its focus on data had saved the hospital $3 million on supply chain costs….

..Semantic search. Imagine you’re a doctor trying to learn about a new patient or figure out who among your patients might benenfit from a new technique. But patient records have been scattered throughout departments, vary in format and, perhaps worst of all, all use the ontologies of the department that created the record. A startup called Apixio is trying to fix this by centralizing records in the cloud and applying semantic analysis to uncover everything doctors need, regardless who wrote it…

..Getting ahead of disease. It’s always good if you figure out how to diagnose diseases early without expensive tests, and that’s just what Seton Healthcare was able to dothanks to its big data efforts…

and more!

Related articles

• Better medicine, brought to you by big data [GigaOM] (gigaom.com)
• Intel and NextBio seek Big Data upgrades in genomics (fiercebiotechit.com)
• Big Changes Are Ahead For The Health Care Industry, Courtesy Of Big Data (fastcompany.com)

• Big data – a brief overview (slideshare.net) [a slide presentation, 42 slides]

• Oracle adopts the popular R language for the enterprise and big data. (oracle.com)
• Presentation: Scalability Challenges in Big Data Science (architects.dzone.com)
• Salesforce intros Radian6 Insights for social big data (zdnet.com)
• Big Data Modeling – Part I – Defining “Big Data” and “Data Modeling” (infocus.emc.com)
• NextBio and Intel Announce Collaboration to Optimize Use of Hadoop Stack And Move Forward With Big Data Technologies in Genomics (ducknetweb.blogspot.com)
• A Beautiful Friendship: Big Data and Social Media (blogs.sap.com)
• Stanford rides Big Data wave in medical research (fiercebiotechit.com)
• Big Data? Big Deal! (clean-clouds.com)

Resist the urge to label everything a disease

Patients. PARAGUAY (Photo credit: Community Eye Health)

From the 7 July 2011 post at KevinMD.com

Every patient is the only patient.
– Arthur Berarducci

Each person in need brings to us a unique set of qualities that require unique responses.
– Don Berwick

Disease-ify: To generalize and then classify a unique person’s health complaint in order to match them with an effective remedy that ends to encounter; often done out of convenience, expedience, or for profit.

Unique is a funny word. Every time I come across it, I am reminded of my high school English teacher’s admonition that qualifying the word–very unique, kind of unique–is inappropriate. Things are either unique, one of a kind, or not.

 

Although Dr. Berwick did not have my English teacher, I think he would agree that each patient’s presentation is unique in this sense; it is one of a kind. Even the most mundane complaint is buried in a rich social and genetic context that simply cannot be reduced to a chief complaint.

As a moral enterprise, medicine seeks to serve patient interests, and few interests supersede the need to be treated as the unique identities that we are. …

More Being Prescribed Psychiatric Medications With No Diagnosis

From the 4 August Medical News Today article

59.5% of antidepressant prescriptions were made with no diagnosis in 1996, in 2007 the figure rose to 72.7%, researchers reported in Health Affairs. Antidepressant drugs are today the third most commonly prescribed class of drugs in the USA.

Nearly 8.9% of the American population had at least one antidepressant prescription during any given month during the period 2005-2008.

A good proportion of this growth in antidepressant prescription has been by non-specialist providers whose patients were not diagnosed by a psychiatrist.

Read the entire article

Related articles

• Prescriptions for antidepressants increasing among individuals with no psychiatric diagnosis (medicalxpress.com)
• More Antidepressants Prescribed by Non-Psychiatrists (psychcentral.com)
• Antidepressants Overprescribed in Primary Care (psychcentral.com)