Friday, January 27, 2017


“Statistics teach absolutely nothing about the mode of action of medicine nor the mechanics of cure.” – Claude Bernard

Spurious Correlations, a term coined by Karl Pearson to describe the relationship between ratios and absolute measurements, is defined in Wikipedia: In statistics, a spurious relationship or spurious correlation is a mathematical relationship in which two or more events or variables are not causally related to each other (i.e. they are independent), yet it may be wrongly inferred that they are, due to either coincidence or the presence of a certain third, unseen factor (referred to as a "common response variable", "confounding factor", or "lurking variable").
Harvard Business Review cautions…

Little insight is gained from the accruing enormous research. To resolve ambiguity by using mathematical probability without a tincture of skepticism sterilizes the intellect and obfuscates the truth. While mathematical probability is a human invention to ease our understanding of the world of science. “Willful ignorance entails simplifying our understanding in order to quantify our uncertainty as mathematical probability.” -Herbert Weisberg

The scientific journals fill pages of mathematically derived studies to prove an intent, but do little to advance the cause of the physicians faced with the dilemma of treating disease.
Today quantification is the game in town. If you cannot quantify then it does not matter. Essentially the modern halls of medicine have relegated qualification of a disease process to the charred bin of history. A clinician once and still in some cases treats disease with the qualification of his or her earned and educated wisdom from experiential hindsight. The deluge of quantified guidelines inundating the landscape of medical IFTTT (If This Then That), which determines payment by the third-party insurers is circumventing the very essence of medical care of patients.

The illusion of certainty is compounded by the statistical geniuses who have little to do with medical facts or care and more to do with number manipulation to find the statistical significance. After having found the golden p-value of less than 0.05 deem the experiment, correlation, or a randomized control trial a landmark success. The quest to succeed supersedes intuition and judgment of the researcher. Today the desire for publication overrides all other questioning beasts of the mind. Studies are done for the sake of publishing and not for the sake of science of discovery itself.

No wonder the biotech giant Amgen reviewed 53 “Landmark studies” and found only 6 verifiable!

Validation data of drug target studies could only prove 14 of 67 projects.

If you look at the financial picture, the US government spends nearly $31 billion every year in science funding through NIH , which is given as research grants to academic scientists. Given the reproducibility rate of 11% (6 of 53) suggests that 89% or $28.74 Billion is being wasted. The obvious implications of such frivolous spending in healthcare costs are staggering when scaled to the entire medical industry.

Today scientific investigation considers human intuition and judgment as flawed and outmoded. Poisson once determined medical care through the lens of mathematical probability, is alive, well and wildly flourishing in the halls of scientific search. And few scientists straighten their spine to ask the question, “Can probability and statistics arbitrate the truth?”

Probability a subjective and ambiguous prospect, once an adjunct to reality has redefined itself as the objectified norm. The frequency of observable events as a hypothesis generating concept has now by the magic of quantification become “real” evidence as in medicine. The term “Risk” as one  might realize, in medicine is associated with causation, yet no precise term of the relationship between correlation and risk has a unified support, meanwhile, statistical fiat controls the issue of risk and harm. The anticipated “Harm” is exposed in this article from the Harvard Professors: The logic here relies on estimates based solely on assumptions. There are no hard facts except disparate data to prove their ideological point. So is that harm?

Calling into question the human subjectivity as a failing, quantified methods reign supreme today. Judgement, intuition, experiential reference subjugated to the quantified, computerized IFTTT norms. And the developed algorithms of best treatment are based on probability of response and the cost of the treatment. The hard truth willingly being ignored is the spark of intuition gained from the potential response of a single patient and the molecular truths that might lie beneath, rather than the quantified “logical” guideline based patient’s care. Even more dumbfounding is this concept at play in "scientific journals:"
Brenda J. Klement, Douglas F. Paulsen and Lawrence E. Wineski are authors of: Clinical Correlations as a Tool in Basic Science Medical Education Journal of Clinical correlation as a Tool in basic Science Medical Education. The article published in Journal of Medical Education and Curricular Development. In this article the authors propose the following; “Clinical correlations are tools to assist students in associating basic science concepts with a medical application or disease.”  One only needs to imagine the impact on the spongy brains that absorb these concepts and use them as the foundation for all future patient management in medicine.

While doubt and ambiguity grow uncertainty, quantified statistical inference deems to reduce doubt by applying certainty where certainty does not exist. Whereas real experimentation means a chance meeting error in the face, quantified inference on the other hand, suggests a sterilized, clean and objectified certainty. We are awash with "incremental advancements" that ebb and flow but real breakthroughs in medicine are few and far between. This exalted form of science of statistical "purity" has caused a slew of retractions in its wake. The retractions come in bigger and bigger waves, some by authors, others by peer complaints, and still others by the journals themselves. Most of these “high impact” articles have been cited in other literature and by other scientists as well. The scale of damage to the real advancement of science and medicine continues at unprecedented pace. Copied below are a few recent retractions;

The human mind has the uncanny ability to use logic, experience, outcomes, experimental design, minority opinion and other perspectives to grow their intuition map. From there the seeds of truth grow. The mechanized, automated, statistically quantified world of today leads to the unnatural and uncomfortable way of a flawed linear thinking. Today’s “Evidence,” as proclaimed by the statistical manipulators, remains a soft flowing sea of sand, moved by the vagaries of the winds of numerical information and/or misinformation. Panaceas abound in the form of “Coffee,” “Antioxidants,” “Vitamins” to name a few that were dismissed after being regaled in laity publications, the NEWS print and digital media. Coffee was correlated to cause cancer and then it was not.

Here are a few booms and busts related to faulty science.

Coffee causes cancer…
1.     Stocks P. (1970) Cancer mortality in relation to national consumption of cigarettes, solid fuel, tea, and coffee. Br J Cancer, 24:215–225
2.     IARC, (1991) ‘Monographs on the Evaluation of Carcinogenic Risks to Humans: Coffee, Tea, Mate, Methylxanthines and Methylglyoxal. Volume 51

Coffee does not cause cancer…
"After thoroughly reviewing more than 1,000 studies in humans and animals, the Working Group found that there was inadequate evidence for the carcinogenicity of coffee drinking overall."

Antioxidants and Cancer…
Initially Antioxidants were supposed to prevent cancer, later it was suggested that it might promote it!
Cochrane Review of the benefits of Antioxidants finds there is 1.03 higher risk of cancer with it’s use:
And studies in mice show; Antioxidants accelerate tumors in mice
Meanwhile Vitamin D still remains the science writer’s current favorite who present both sides of the benefit and risk arguments with zeal of their intent.
Current Conclusions: We found no evidence to support antioxidant supplements for primary or secondary prevention. Beta-carotene and vitamin E seem to increase mortality, and so may higher doses of vitamin A. Antioxidant supplements need to be considered as medicinal products and should undergo sufficient evaluation before marketing.

It is wise to remember Galton’s “Correlation Coefficient;” a numerical measure of the degree of relationship between two quantities, once heralded and later quantified by Karl Pearson as a measure of “partial causality,” since 1890 and through time, has been transformed by the manipulation of “quantified metrics” into “absolute causality.” This arbitrary measure of conjecture has now become fact du jour. The evidence in medical science is supposed to be based on “causation” and not using statistical generalizations via mathematical probability. At best this new "science" gives us partial causality and lends to harm for all.

Sunday, January 22, 2017


– A short story of RISK

“Fear of harm ought to be proportional not merely to the gravity of the harm, but also to the probability of the event.” 

A certain atmospheric hue cries out to my memories of a long gone past as does a certain smell of a parched earth fed with fresh rain drops. And now it seems that words are pulling at the skein of new-found knowledge and old wisdom in medical care.

Before we get into the weeds, let me direct you to this very well crafted dialogue between a physician Dr. Saurabh Jha and an economist Dr. Mark V. Pauly that I happened to feed on.
This wonderful piece brings with it wisdom from thoughtful minds. Someone who has seen, experienced and then nuanced the human economic behavior into digestible components.

I plan to focus squarely on two concepts outlined in this wonderful dialogue; Community Risk and Individual Risk. Although these are heady concepts that fill an insurer’s mind and an economist’s well-spring of financial models, they also dwell largely into the domain of behavioral economics as coined by Kahneman and Tversky. Essentially, how people make their choices. What Mark Pauly, PhD has nicely captured the consequences of such actions. And learning from these concepts, he pulls the trigger on his own ideas for the future. However, I will leave his ideas of how to advance the insurer model in the future for another time.

We start with Dr. Mark Pauly's statement; “we transfer our angst about the uncertainty of our future, the dice which plays with our lives, to insurers who are in the business of rolling the dice.” And that is the very fount of insuring or transferring risk (known, projected or unknown hazards) for a certain sum of money, called a “premium.” He then moves to the issue of information asymmetry; “The sellers of health insurance can roughly risk rate the buyers by asking questions about their health, recent visits to doctors, family history and tobacco and alcohol use.” Simply, the Insurers can mitigate their financial risk by gathering data on an individual before insuring. Yet information asymmetry abounds when insuring a large cohort, as Peter Bernstein states in his book “Against the Gods,” “The information you have is not the information you want. The information you want is not the information you need. The information you need is not the information you can obtain. The information you can obtain costs more than you want to pay.” And since numbers have no soul, they can be manipulated to our whims and needs, the known risk takes on the “unknown character.

The argument posed by Mark Pauly take us into the mind of the insured and the insurer. Whereas the insurer’s aim is to gain from the collective premium and reduced outlay, the insured has a different purpose in mind; he or she wants a ROI on the premiums when need arises. To that end the insurer tries to aggregate the insured to minimize the risk to self. In the healthcare market that translates to having a large pool of low-risk individuals mixed in with a small pool of high risk individuals. The unused premiums go to pay for the high-risk cohort and any surplus is the Net income for the insurer. But Dr. Pauly makes a case for the flight of the low risk individuals who may not want to subsidize the high-risk ones and thus adverse selection ensues when more high-risk individuals asking for insurance essentially force the insurer to leave the game of risk. Once again here is the wisdom of Peter Bernstein words, “Game theory says that the true source of uncertainty lies in the intentions of others,” and that “This is the essence of risk aversion—that is, how far we are willing to go in making decisions that may provoke others to make decisions that will have adverse consequences for us.” The high-risk individuals' need forcing a high premium on the low-risk individuals force the latter to leave the market place.

What is perhaps more informative is the idea of “Community Risk” which is embedded in the current Affordable Care Act that forces this concept. And Dr. Pauly goes on to state, “We found that when insurers changed to community rating, while the probability that the high-risk were covered increased, it was overwhelmed by the probability that the low-risk, the healthy, didn’t buy insurance.” It would appear the low-risk individuals realized their personal financial risk in the “one-size-fits-all” model and as Peter Bernstein states elegantly, “life is a collection of similarities rather than identities; no single observation is a perfect example of generality.” The model of community risk of insuring the community under a similar actuarial risk drives out the low-risk individuals, creates adverse selection and ultimately the insurers from the market-place.  

We cannot therefore intellectualize our needs to the degree that we cannot find any satiation of our desires. Wild gyrations of reality exist in the imperfections of the outliers as noted by the author Nassim Taleb in his book “The Black Swan.” Therefore, information asymmetry will always exist even within the elegance of mathematical probability models. The consummate model of individual risk still reigns supreme. One size per individual. Or as Kierkegaard states, “The central point about being human is that the unit “1” is the highest; “1000” counts less.” And he goes on to say something more ominous, “Aristocrats take it for granted that a lot of people will always go to waste. But they keep silent about it; they live sheltered lives pretending that all these many, many people simply do not exist.”

If you are not too tired of reading this, let me show you a corollary of the ACA insurer model to  the ACA's forced model of how medicine needs to be practiced. Community Risk as advocated in the Affordable Care Act is akin to Population Medicine as advocated by the ivory towers in our prestigious universities. One size fits all concepts of care are being enforced in the act to minimize cost outlays for high-risk individuals. Age, Performance characteristics, Shared Decision Making, Choosing Wisely, Less is More are concepts evolved through a groupthink model of Community Risk. Prestigious organizations, proclaimed journals edited by the political winds and television “experts” abound sizing up the medical care and suggesting that the United States is wasting resources. And it is! But not in the way they seem to suggest. Their concept of wastage is in patient care. Unfortunately, that is a short-sighted and easy target they focus on so that the populace can identify with ease. Digging deeper into the realm of cost, one finds at a minimum 30-40% of the healthcare costs are steeped in the over-indulgence in regulatory and administrative fiats that govern the healthcare dollar and have nothing to do with medical care of the patient. Sweet benevolence couched in rhetoric is bursting with consequences as Shakespeare said, “as in the sweetest bud the eating cancer dwells.”

Personalized Medicine is being bandied about in Research Circles but it is out of reach for an individual of average means because of the astronomical costs of these selective treatments. The insurers balk at absorbing such risk, since the adverse selection prevents enough of the low-risk premiums to mitigate such needs. Perhaps a larger pool of individual rated risks and the current governmental subsidies for those not well to do, can defray the cost for access to better health? If good medical care is the desired outcome then perhaps that should be considered for all, provided the financial risks for both the patient and the insurer is mitigated with large pools of low, average and high-risk insured.

“May you live in interesting times,” a curse in the Chinese language is upon us. We face an interesting complex of thoughts and ideas steeped in the elixir of ideology. Somewhere in the mix is the solution. The enduring concept of individual risk and thus individual care remains paramount in healthcare. One size has never fit All. It never will. We might follow the foresight of our ancestors in the Latin phrase that graces the One Cent coin, “e Pluribus Unum.” Espousing belief in certainty by the policy wonks is akin to looking at the face of wrath.

“Vast ills have followed a belief in certainty.”