Over-Diagnosed, by Welch et al, is an interesting tale. At first I approached this with some concern as if it was just another one of those trend setting books by some physicians seeking to push the latest idea. After a few pages I was hooked and saw that Welch was in my opinion spot on. Yes there is too much diagnosis. As anyone who is in the medical area knows one of the most costly machines ever invented was the CAT scan. I recall that the second such machine went into Mass General I believe in 72 or 73, and was immediately put to use in determining if a stroke was a block or a bleed. In those days this was a real issue and the CAT scan allowed for a rapid and accurate determination and helped save lives. Then its use expanded. Today with a CAT scan as Welch states we can find things that we never ever suspected, and then what?
Chapters 1 and 2 set the scene for what the authors intend to present. Namely that there are lots of over diagnosis out there and for lots of reasons. Part of the author’s presentation is that we have defined more disease. Take the example of Diabetes, it was fasting blood sugar of 140 and now we start treatment at 100! The reality is we should really look at the average over some period of time, using say HbA1c which is a metric measuring average blood sugar over 60-90 days. It is a good measure but still not perfect. We also should remember that HbA1c follows BMI, namely the fatter you are, the greater the chance of having Type 2 Diabetes, and then of course all the sequelae. The authors give a good overview of this idea.
Chapter 3 is the one which details the issue of if you look you shall find. I have seen many examples of this. Take a 70 year old woman, goes to her local physician with what may described as a vague tightness in her abdomen. Off to the CAT scan. Then we see shading in the right ovary, then off to the OBGYN, then ultrasounds, looks like a cyst, and the CA 125 is low, so the scans are repeated, and CA125 redone, remains low, but he insists on a recent mammogram, which gets done with some questions, then for an ultrasound and follow up, then they find a nodule on thyroid, but it was there before, and then Endocrinologist fortunately had old records, ten years earlier and at that point everyone stopped and she went home told not to wear that tight belt anymore! How much did that cost! Welch has many tales like this. Then there are the ones he misses, what I have seen as a small industry, the Lyme Disease group, where they are getting gamma globulin transfusions at hundreds of thousands of dollars, adding to costs with questionable results. Thus Welch is understating the problem, but he is spot on!
Chapter 4 is the lynchpin chapter for several reasons. It is the prostate cancer chapter and here I may differ with the authors but not by much. The rule of thumb is that 50% of men in their 50s have prostate cancer, PCa, 60% in their 60s, 70% in their 70s and so on. This is a really rough rule of thumb but the author makes the point that most PCa is indolent, slow growing and not the cause of death. The problem is we do not know how to differentiate between slow and fast growing so we tend to deal with all of them assuming the worst. In addition the author on p 59 discusses the American and European Trials and he discusses their conclusions. If one were to look deeper into the trials one would see major defects. The American used a fixed 4.0 PSA over the 10 year period even though the number was shown during that period to require substantial age related adjustments. Thus the problem with the American Trial was that they asked the wrong question. The asked did a PSA of 4.0 show significant reduction in mortality? The proper question should have been; what level of PSA at what age brackets shows a significant reduction in mortality. The European Trial was defective in that measurements were also at 4.0 but the time between was considerable or not at all. Thus I would argue with the author that these results have merit. The other problem with PSAs is that they lead to biopsies which have some morbidity. But frequently we see HGPIN, which has been assumed a precursor to PCa but we also see HGPIN and then its total regression. Why? Genetics, immunological, a result of the first biopsy, or perhaps there was a PCa stem cell and they got it the first biopsy. Or a million other things. Notwithstanding the authors phrase the issues quite well.
Chapter 5 looks at several other cancers and screening. I will focus on one, melanoma. In the late 60s when we saw a melanoma we were ready to amputate a limb if that was where it was located. That generally was because it was detected late in the stage. However today with increased sensitivity to one of the deadliest cancers known, we can detect it earlier. On p 68 the authors show a curve which shows incidence and mortality versus time. Mortality is almost constant whereas incidence is increased. In the prior chapter on PCa the argument made is that we can now determine PCa at much lower levels and at levels where mortality is not changed. That is we are detecting non-lethal PCa. The author tries to make the same nexus here, not exactly, because he readily recognizes the deadly nature of melanoma, but to the casual reader it may look that way. There is a true increase in the incidence of melanoma due to lifestyles, excessive ultraviolet exposure, and the good news is mortality is slowly decreasing. That I believe is a point needing better clarity.
Chapter 9 is well done and hits a significant fact. Genetics which is expressed in your DNA is interesting but only in a small set of diseases is it the causative factor per se. Take obesity and diabetes, not discussed in detail by the author, but of significant interest since its costs are currently well over $250 Billion per year in current 2011 medical costs. There is the desire on the part of many to find the genes which cause this. Obesity is in almost all cases a disease where the patient violates a law of nature, input less output equals net accumulation, they just consume too much. Type 2 Diabetes in more than a majority of cases is driven by obesity and its related inflammatory state. The attempt to blame genes may be fruitless. The same goes regarding say cancer. Vogelstein in a now classic demonstration showed twenty years ago that colon cancer was the result of 4 genetic hits. What caused the hits was unknown but they were almost always the same and always in the same sequence. Recent work on PCa has attempted to do the same there but it appears that PCa is a multi-hit cancer but sometime they are not the same set of hits, genes for PTEN, Akt, c-Myc etc are all affected but in a yet to be determined manner.
Chapters 10 and 11 speak towards facts and systems. The authors does a superb job here as well. Simply, it discusses the issues related to gathering data and looking at it systematically. This is more than just having electronic medical records and the like.
The conclusion is well done. What would have been useful especially since the author states he was trained as an economist, would be some detailed discussion regarding what costs could be saved by the recommendations he makes. That would be a major contribution to the overall discussion. The new health law for Medicare patients will be issuing multiple Comparative Clinical Effectiveness guidelines and these, albeit a potential rationing mechanism, may also be a potential cost increaser. It would be very useful if the author could put dollars to his recommendations. He has set out a well structure framework for that, it would be a great follow up.
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