Sunday, July 2, 2017

Book Summary: Over-Diagnosis – Making People Sick In The Pursuit Of Health, by Dr. H Gilbert Welch

Imagine one morning you don’t feel right and go in WebMD (medical portal) to figure out what’s wrong, you browse around until you find the illness that catches your eye, Swine-Flu.

As you read through the list of symptoms you realize that you have all of them or in other words if you have all of the symptoms that you would have if you have Swine-Flu.  If we talk in term of probability, 95% of the people with swine-Flu have these symptoms. You began to freak-out and this is what happened to us most of the time. You search about any small symptom on the internet, you are sure to meet disaster. They will lead you to the any form of cancer or any dangerous disease. But this is not the truth sometimes, in fact, most of the times. Let us see how. If you know about Bayes Theorem, (a concept in probability. Don’t worry we are not dealing this in detail) you do further research and try to find out more facts to figure out the probability if you have swine flu or not. So, with little more googling you discover that the disease is extremely rare, only one in one hundred thousand (1/100000).Now, about the symptoms, like headache and runny nose, lots of people have those and google tell you one in a hundred (1/100). Putting everything into the place, now probability (using Bayesian theorem) of have Swine Flu is calculated as .00095, which is very-very small as compare to the probability we saw in first stance i.e. 95%. If we revisit the statement once again “…95% of the people with swine-Flu have these symptoms”, DOESN'T mean if you have these symptoms then 95% chances of you having Swine Flu.

In the book, Overdiagnosed: Making People Sick in the Pursuit of Health (Beacon Press), Welch and coauthors Lisa Schwartz and Steven Woloshin write about the hazards of looking too hard for illnesses in healthy people, including additional procedures that carry no benefit, but may cause harm, higher health care costs, and psychological detriments. “The biggest problem is that over diagnosis triggers over-treatment, and all of these treatments carry some harm,” says Dr. Welch.

There is an assumption that sooner is always better  but the hidden assumption states anything found early required intervention. OVER-DIAGNOSIS can be defined as the detection and treatment of an abnormality not destined to ever produce symptom or death.

This book is divided into twelve thorough chapters that do not only unveils the systematic conspiracy of the health care systems but also bursts the hypes created by popular media that promotes the fear of disease and perpetuates the myth that early and aggressive treatment is always better. Doctors have begun to leave no test undone, no abnormality overlooked. Profits are being made from screenings, medical procedure and pharmaceutical.

Chapter two; We change the Rules, highlights the clear traces of conspiracy at the institutional level. It shows how numbers get changed to give you diabetes, high cholesterol and osteoporosis. The author provides the end-to-end research to prove that over-diagnosis or early detection doesn’t help the population at large but only instills the fear of being died with the disease. Let us see how-
Who is diabetic? Before 19997, if you had fasting sugar over 140, then you had diabetes. But in 1997 the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus redefines the disorder. Now if you have fasting blood sugar over 126, you have diabetes. So everyone between 126 and 140 used to be normal but now has diabetes. That little change turned over 1.6 million people into patients.

Is that a problem? Maybe, or May not be. Because the rule has been changed, doctors now have to treat more patients for diabetes. That MAY mean that they have lowered the chances of diabetic complications for some of these new patients. But because these people have milder diabetes, they are at relatively at low risk of these complications to begin with. The author has proved through the research that people with mild abnormal blood sugar have less to gain from treatment. If patients are not getting benefited from the early diagnosis then who is?

These changes substantially increased the market for treatment and the money to be made from them. There are widespread concerns about the independence of the experts who set the cutoffs for all the conditions (whether it is diabetes, hypertension, osteoporosis or any other disease). The head of the diabetes cutoff panel was a paid consultant to Aventis Pharmaceuticals, Bristo-Myers Squibb, Eli Litty, GlaxoSmithKline, Novartis, Merck and Pfizer – all of which make diabetes drugs. Nine of the eleven authors of recent high blood pressure guidelines had some kind of financial ties – as paid consultant, paid speaker, or grant – to drug companies that made high blood pressure drugs. Similarly, eight of the nine experts who lowered the cholesterol cutoff were paid consultants to drug companies making cholesterol drugs.

With over-diagnosis, a few may be helped but a lot more will be over treated and some of them will be harmed. The conventional ethos of medical is to focus of potential benefits for the few and to downplay the rest. Dr. Welch proved via randomized trials that the treatment on ‘new’ patients (with mild abnormality) does not improve the chances of not getting better. However, over diagnosis will increases the chances of plethora of other diseases.

In the graph on the left (fig. 1a), the rise in cancer diagnosis is accompanied by a rise in the feared outcome of cancer -  death. This suggests that the new diagnoses are destined to be meaningful and that this is a true increase in the underlying amount of cancer that matters.

But in the graph on the right, the rise in cancer diagnoses is not accompanied by a rise in cancer death. This suggest that while there is more diagnosis, there is no change in the underlying amount of cancer that matters.

Over-Diagnosis can also be understood as an attempt to look harder to find the abnormalities without any symptoms. This has been seen in cases of prostate cancer, breast cancer and other abnormalities which required scanning. Fear has taken place of understanding the disease. The simple rule of thumb that can be deduced from the findings of the author is that -  diagnosis is important but it should follow the symptoms not the other way around.

Author cautions in the end that it’s tempting to conclude that the solution is simply to avoid doctors. But that would be the wrong conclusion. Medical care offers ill patients a great care. The question is about when you are well. How hard doctors look for things to be wrong?

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