Make Evidence-Based Medicine Great Again!

Cristina Roure
 

“Make Evidence-Based Medicine Great Again!” is the provocative title of a conference that Dr. Domenico Pagano delivered at the 56th Congress of the American Society for Cardio-thoracic Surgery, calling for the need to restore professionalism, integrity, and trust in data and evidence in medicine. The conference is long, it lasts 55 minutes, but Pagano makes a brilliant presentation on the increasing manipulation that has led us to the swamp in which evidence-based medicine (EBM) currently inhabits.

Risk-based medicine, a hieroglyph full of traps

Jordi Varela
Editor

 

Gerd Gigerenzer, Director of the Harding Center for Risk Literacy at the Max Plank Institute for Human Development in Berlin, was featured in this blog in 2016 following the publication of "Risk Savvy. How to make good decisions." Gigerenzer's crusade against risk manipulation and its consequences are consistent and tenacious, and that's why we should use more of his materials to help overcome the traps of malicious numbers if we want to practice proportionate medicine to address the real risks to peoples health. The following video which was edited in February 2020 by the Gigerenzer factory,  turns out to be essential in differentiating between absolute risk and relative risk.

When the overdiagnosis is politicized

Rudy Giuliani, the Republican mayor of New York, on that fateful September 11, at an election meeting said: "I had prostate cancer 5 or 6 years ago and I thank God to be an American citizen because here the probability of survival at five years for this cancer is 82%, while in the UK, due to socialized medicine, this value is only 44%." We must clarify that in the US, PSA screening is widespread while in the UK it’s not so. According to Gerd Gigerenzer (I have extracted this case from his book "Risk Savvy"); Giuliani’s words conceal a big mistake, because in reality, although it seems a contradiction, mortality from prostate cancer in the two countries is practically the same. So how is it possible that the survival rates are so different? To explain it, Gigerenzer describes two biases that encourage the intentional error of the conservative politician:

Risk savvy according to Gerd Gigerenzer

Gerd Gigerenzer, Director of Harding Center for Risk Literacy at the Max Planck Institute for Human Development in Berlin, has published "Risk Savvy. How to make good decisions" (Penguin 2014). It’s a book that addresses the difficulties of making decisions in uncertain environments and the need to know how to communicate risks in an understandable way. According to the author, according to his own experience, 80% of doctors do not understand the meaning of a positive result in a diagnostic test and, following this line, in an Australian study, from the 50 doctors surveyed, only 13 responded that they understood the concept of "positive predictive value" (which is the probability of having a disease if a specific test is positive), but only one of them finally was able to explain it properly. In a post on this blog, "Too much mammography or the mirage of screenings", Cristina Roure said that a woman's risk of breast cancer after showing a suspicious lesion on a screening mammogram is 10%, when most doctors believed to be 90%. After this introduction, we can understand why we ought to consider Gigerenzer’ book as essential in medical practice in a world of probabilities.

Could the cancer numbers be better explained?

Cristina Roure explained in a post in her blog series "Pantone", an experience that Gerd Gigerenzer, Director of the Max Planck Institute for Human Development in Berlin, wrote in the book "How to know when numbers deceive you", where more than half of the surveyed gynaecologists did not estimate, after seeing published scientific data, what was the probability to have cancer of an asymptomatic woman’s with a positive screening mammogram. In fact the error of most of the colleagues was monumental: they said it was 90% when in fact it was 10%.

In a recent post, I commented on the book of Peter Ubel "Critical Decisions", in which the author showed what the emotional force of numbers was, both for patients and for the doctors. In this certainly worrying line, I want to give you a shred of hope. There are ways to show the numbers in order to reduce the reigning confusion. Many experts are warning us to flee percentages, the ineffable pies and the relative risks, and we have to get used to talking to patients of real numbers, pictograms with people and absolute risks. To make myself understood, I include a couple of graphics from the Harding Center for Risk Literacy, a centre which is in the orbit of Gigerenzer and Max Planck. The first is a pictogram on the evaluation of prevention programs for prostate cancer based on PSA controls and anal touch of the gland.

Knowledge chain sanitation, a difficult undertaking

By Cristina Roure 

In one of my posts  from "Pantone" series, August 17, I was talking of the need for crystal clear knowledge sources so we can make appropriate decisions, but the point is that our sources are contaminated by a number of biases that permeate the decisions we make as citizens, as patients, as health professionals or managers, and this leads to over diagnosis and overtreatment. Faced with these biases, Gerd Gigerenzer and Muir Gray, in the book "Better Doctors, Better Patients, Better Decisions" propose some sanitization measures, to which I have allowed myself to add some homemade ones:

1. How to make research more relevant to patients

a) Regulatory agencies, such as the FDA or the EMA, should require studies demonstrating the superiority of the new drugs compared to the best treatments available, not placebo.
b) Independent sponsors should promote research on simple, beneficial and patient relevant treatments and practices that do not involve the use of drugs or technology, practices that for this reason lack sponsorship (exercise, healthy diets or checklists to improve clinical safety).
c) I would add that the so called Patient Reported Outcomes should be included in clinical trials, which unlike conventionally employed variables, report on the effectiveness of treatment perceived by the patient.

Crystal clear knowledge for decision making

By Cristina Roure 

Excellent health care is one in which patients, professionals and managers apply the best available knowledge in decision making. Only well-informed agents can take the most appropriate decisions for an effective, safe and efficient health system. We often think that the big problem of the system is the lack of money, and only devoting more resources will solve the problems, but lack of knowledge is much more worrying than it may seem at first glance.

Sir Muir Gray, Chief Knowledge Officer of the National Health Service (NHS), uses an analogy that I find very spot on: "It takes knowledge as crystal clear as the water we drink if we want to take the right decisions." But the current reality is very different because we drink from contaminated sources of knowledge.

"Too much mamography" or the mirage of screenings

By Cristina Roure @crouren

The BMJ recently published the results of a randomized Canadian study which shows that annual mammography in asymptomatic women under 60 does not bring any advantage in reducing mortality from breast cancer compared with physical examination without mammography and, instead, it leads to more than 20% over diagnosis. The article is accompanied by an editorial entitled "Too much mamography" which suggests the need to rethink the breast screening policies as it has done with PSA screening in the case of prostate cancer.

It can be somewhat counterintuitive to think that a test that can detect cancer early and therefore provide the opportunity to treat it early, does not reduce mortality, but often not only the citizens but also the professionals have difficulty interpreting the benefits and risks of screenings and to communicate them clearly to patients when making the decision to participate or not in the program. Gerd Gigerenzer, Director of the Max Planck Institute for Human Development in Berlin explains it very well in his book Calculated Risks. How to know when numbers deceive you¹.