Too much of a good thing?
This is another of those “Early Reviewer” books from LibraryThing.com … which has recently been connecting me with a number of books in related areas. Unfortunately, a lot of these
have only been so-so (well, let me drop the caveat in here that most
of the books that I end up getting through LTER aren't exactly items that I went looking
for, but clicked on them on the monthly request list because they “sounded interesting enough”, so going in on these I'm rarely in a “can't wait to read it” mode, and not particularly predisposed to an enthusiastic reaction). While this was, indeed, interesting enough
it also only netted three
of my little bookmarks, meaning that there wasn't a whole lot “jumping off the page” for me to reference. Of course, this is a somewhat unfair way to preface my review of Dr. H. Gilbert Welch's Less Medicine, More Health: 7 Assumptions That Drive Too Much Medical Care
Those of you who follow these reviews over on my main blog will realize, I've been through a lot
of “medical care” over the last half year or so, and thereby the material here should be pretty much “on target” for me … but somehow this wasn't necessarily the case. The author is a medical doctor who is both a professor at the School of Medicine at Dartmouth, and an internist with the V.A. (most of his stories in the book come from that work). His main area of research has been in the area of cancer screening, and has published books about that, as well as a controversial study in 2012 that indicated that the wide-spread use of mammography was having no appreciable effect of breast cancer death rates. This book essentially is an expansion of the focus of his previous titles, Overdiagnosed
and Should I Get Tested For Cancer?
, moving into general cultural assumptions about medical care.
Since I don't have a lot of bookmarks here to build a narrative with, I think it might be useful to just run through what these “7 Assumptions” are, and then go into some detail on those:
Assumption #1: All Risks Can Be Lowered
Assumption #2: It's Always Better To Fix The Problem
Assumption #3: Sooner Is Always Better
Assumption #4: It Never Hurts To Get More Information
Assumption #5: Action Is Always Better Than Inaction
Assumption #6: Newer Is Always Better
Assumption #7: It's All About Avoiding Death
Now, presented with that list of propositions, I suspect that most folks would be in agreement all the way down the list … which is, I assume, why Welch wrote this book, as, point-for-point, he presents arguments against each. He actually pairs a “disturbing truth” with each assumption in the chapter headings, and these go:
D.T. #1: Risks can't always be lowered – and trying creates risks of its own.
D.T. #2: Trying to eliminate a problem can be more dangerous than managing one.
D.T. #3: Early diagnosis can needlessly turn people into patients.
D.T. #4: Data overload can scare patients and distract your doctor from what's important.
D.T. #5: Action is not reliably the “right” choice.
D.T. #6: New interventions are typically not well tested and often being judged ineffective (even harmful).
D.T. #7: A fixation on preventing death diminishes life.
All of my little bookmarks are from the middle of the book – in Assumptions #2-4 – so I'm going to let those “disturbing truths” stand on their own as an indication of what's covered in the other chapters, and zoom in to the bits that caught my fancy while reading this.
The most memorable
part of this for me was from the third chapter … where Welch splits different types of cancer out into different “critters” … each with a different progression. I was trying to figure a way of communicating this to you briefly, but I'm going to have to break down and type out a few paragraphs to get you what's the essence of this (sorry about that!):
Let's start with the benefit of cancer screening. It's an important benefit: avoiding a cancer death. At the same time, it's equally important to acknowledge that screening doesn't avoid most cancer deaths. People who are regularly screened still can die from the cancer being screened for. Every randomized trial of screening has shown this. It's not the patient's fault. It's not the doctor's fault. It's not the screening test's fault. Instead it reflects the dynamics of cancer.
When I was in medical school, I was taught that anything labeled “cancer” would inexorably progress. Once a cell had the DNA derangement of cancer, it was only a matter of time until the cancer spread throughout the body. And it was only a matter of time until it killed the patient.
But we now recognize the world of cancer is much more diverse. At one extreme, autopsies have shown that many of us have small cancers that never bother us during life – particularly cancers of the prostate, breast, and thyroid gland. At the other extreme, screening programs have shown that early cancer detection doesn't help everyone; many go on to die from cancer despite early detection. These observations bring us to a new conceptual model of cancer – and to turtles, rabbits, and birds.
It's a barnyard pen of cancers. The goal is not to let any of the animals escape the pen to become deadly. But the turtles aren't going anywhere anyway. They are the indolent, nonlethal cancers. The rabbits are ready to hop out at any time. They are the potentially lethal cancers, cancers that might be stopped by early treatment. Then there are the birds. Quite simply: they are already gone. They are the most aggressive cancers, the ones that have already spread by the time they are detectable, the ones that are beyond cure.
Screening can only help with the rabbits. The turtles don't need help; the birds can't be helped. The turtles create the problem of overdiagnosis …, the birds create the problem of limited benefit.
The author goes into a lot of data about these various groups, but one particularly caught my eye – it was a 30-year study of 50,000 patients looking at a specific cancer. Half these subjects were systematically screened for this cancer, and half were not. At the end of 30 years, most had died. Of the screened group, 2% died of the cancer, while the non-screened group had a 3% death rate of that cancer – a 33% reduction. That's great, right? Well, it depends. The mortality rate for both groups was “exactly the same”
year-in-year-out, with the rate at the end of 30 years being 71% in both groups – “Screening didn't help people live longer. Not even a little bit.”
… pretty sobering if one's hoping that having that test is going to improve your longevity.
The next thing I want to bring to your attention is from the second chapter … the one about “fixing the problem”. Welch backgrounds this with a discussion about the “two broad categories of medical research” evidence-based (randomized trials), and observational. He notes that EBR has been mocked by some, inviting researchers such as Welch to review the effectiveness of parachutes by using randomized controlled trials. He counters this with a look at how, indeed, some trials are not ideal, including:
One of the pharmaceutical industry's favorite strategies is to study the effect of a drug on the few patients who have severe disease, find some benefit, and then hope that doctors extrapolate the benefit to many patients with a less severe forms of the disease. It's a cleaver strategy: it's like testing parachutes on the few people who jump out of airplanes and then selling them as protection against falls to the many people who walk downstairs. Severely ill patients always stand to benefit more from intervention than those who are less severely ill … Yet the harms of intervention are roughly equivalent in the two groups. So the net effect of intervention regularly looks better in the severely ill.
The last thing I have marked to bring up is from the information chapter, which has a central story regarding a critique of the opening of an “Information Age” exhibit at the Smithsonian, that Welsh had kept handy for decades:
Data, information, useful knowledge, wisdom … that's a good vocabulary. Good enough for me to keep the article around for a quarter century. I might tweak the definitions a bit for clinical medicine. Data would be the measure of lung impedence. They would only become information if they reliably told us about the likelihood that the patient would develop a clinical problem (shortness of breath) – a problem that might lead to a hospitalization. The information would become useful knowledge only if we had a course of action that reliably lowered that likelihood. Wisdom requires balancing the benefits and harms of that action – and knowing how the patient values the carious outcomes – to arrive at a decision about what to do.
Just because you have data doesn't mean you have information. Having information doesn't mean you have useful knowledge. And wisdom – well, that's a whole new ball game.
The central question of this chapter is whether obtaining more clinical data on individuals with medial problems reliably leads to useful knowledge. The short answer is: no. The natural follow-up question is whether there is any reason – other than cost – not to obtain more clinical data. The short answer is: yes. More clinical data not only can create anxiety for patients, they can also initiate cascades that lead to unneeded medical care.
While the author is, obviously, “flying in the face of” the “common knowledge” about medicine, he's hardly “against it” like the anti-vaxxers and other neo-Luddites out there … but he is saying it's become way too easy for even basic medical care to cascade
into complicated, intrusive, expensive, and potentially unneeded
care. And, of course, the way our (U.S.) medical system is set up – nobody gets paid
for letting a condition simply “run its course” as the body heals itself (or doesn't), so there are systemic financial pressures to act on things that might have better outcomes with inaction
There is a lot of info in Less Medicine, More Health
, with the author describing numerous studies, etc. supporting his assorted points. And, as noted above, he's not averse to admitting the other side has supporting material as well, so it's a much more “balanced” look than one might expect for something going so jarringly against the “assumptions” of modern medical care. He personalizes this with a lot of stories from his own clinical work (mainly in the V.A.), illustrating points with what had happened to various patients he'd encountered. The book, however, doesn't have much of a “story arc”, as it is a detailed look into these relatively thorny issues, so it's hardly “a beach read” (for most folks, at least), but given the universal applicability of medical care, this might have some interest even to the fiction readers out there.
This is brand new (just hitting the shelves a week or so back at this writing), so it should be at least available
via your local brick-and-mortar book vendor, but the on-line big boys have it at about 20% off of cover, and, oddly, some of the new/used guys have it new
for about half off (plus shipping). While interesting, and applicable to everybody still breathing, I don't think I can call this an “all and sundry” recommendation, as you really
have to be into this stuff to get the most out of reading it.