Document:Viral Load Internet Hell
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"You Bet Your Life"
23 October 2006
For the past 20 plus years, like most other hospital based physicians working inside mainstream medicine, I accepted the HIV/AIDS hypothesis without question. The idea that HIV infected and killed T cells and therefore wiped out the immune system causing opportunistic infection was accepted by everyone else, so I had no reason to question it. My major concern was avoiding a needle puncture from a patient whose HIV status was unknown. In retrospect, I admit I was vaguely aware of questions, but I didn’t know what those questions were or who posed them.
A few months ago, while surfing the internet for news, I came across a Google video entitled, ”HIV/AIDS, Fact or Fraud?”, containing interviews with Dr. Peter Duesberg and Dr. Charles Thomas. The information seemed credible and sparked my curiosity, so I ordered the book, Inventing the Aids Virus by Peter Duesberg, as well as books by Farber, Bialy and Lauritsen, and emailed Dr. Duesberg for more information. He quickly replied with a collection of more recent articles along with a sample of his appealing sense of humor. After weighing the arguments and style of the proponents of the two sides, I came away impressed with what seemed the higher moral and ethical standards of the AIDS rethinkers – their obviously much higher scientific standards, and their inescapable common sense credibility.
It was only then that it occurred to me after working inside multiple hospitals since the beginning of the "epidemic", I did not know of a single co-worker who had contracted AIDS, a supposedly contagious disease. I do, however, have personal knowledge of co-workers contracting real infectious diseases such as hepatitis and tuberculosis from exposure to patients. In addition, as a radiologist, I routinely saw the admission chest X-rays and admitting diagnosis on many patients. There was no massive epidemic, or even mini one, of sick people carrying the diagnosis of AIDS.
Which brings me to the point of my descent, that began after I read the Sept 27 JAMA 2006 article by Rodríguez et al showing essentially no correlation between CD4 cell count and HIV viral load – indicating that unchecked virus replication is not killing the CD4 cells. On the same day, I posted this information at the misc.health.aids newsgroup and quickly realized that I had entered the proverbial snake pit.
My posted message was almost a direct quote from the JAMA authors: “The noncorrelation in the Figure 3 (click on the miniature to the left) scattergram on page 1504 is the finding which indicates that HIV plasma RNA level (HIV viral load) is not a reliable predictor of CD4 cell loss in HIV infection and challenges the concept that the magnitude of viral replication is the main determinant of the speed of CD4 cell loss at the individual level.”
I promptly received a reply from a Nick Bennett, who turns out to be an MD/PhD from Cambridge (UK), currently a pediatric infectious disease resident trainee in NY, and a self appointed guardian of the HIV/AIDS hypothesis. He explained to me in a condescending and extremely arrogant manner that, "No, I am mistaken, the JAMA article actually confirms a correlation between CD4 cell count and HIV viral load. There is indeed a linear trend in Figure 3, because the R2 Coefficient of Correlation is not zero.”
This absurdity revealed the lie behind the credentials, as clearly the man knows nothing about linear regression analysis. The Figure 3 R2 is actually 0.04, which for statistical purposes is just slightly above zero. R2 values range from zero to 1.0, with 1.0 indicating a straight line and zero indicating a random pattern of dots very much like Figure 3.
Bennett continued his post by questioning my training and background and ability to read and interpret the medical literature:
I find it astonishing that you somehow think yourself better qualified to analyse the results of a paper than the authors themselves or indeed anyone else with specialist qualifications in the relevant field. Where's your research background in HIV (or even microbiology in general)? Why should I trust what you say versus what every microbiologist/epidemiologist/clinician and researcher I've ever met tells me about how to analyse a paper and judge and interpret the evidence? I would say you had no relevant experience upon which to base your views and are incapable of correctly interpreting scientific evidence in context!
I barely controlled myself in reply: “The JAMA, as you know, Dr. Bennett, is the Journal of the American Medical Association and is written specifically for the members of that organization. I have been a member of the American Medical Association and have been reading JAMA since 1976, which is probably before you were born. I was certainly reading it when you were still in knickers, my youthful but arrogant correspondent. I've had thirty years of experience reading and interpreting this journal. How many years have you had?” (I neglected to mention my own publication in 1983).
Bennett must have gone back to read his math book, because he finally agreed an R2 of 0.04 indicates non-correlation, and excuses his ignorance of linear regression analysis by telling me in his PhD thesis research he used PCR and did Western blots. He nonetheless continues in the same self-important manner, and then, with his new found mastery of linear regression, calculates his own R2 value, which does not appear anywhere in the paper, from the data in the paper's Fig. 1 (click on the miniature to the right). This turns out to be a much more acceptable 0.9351. It is also in total error. If we assume Bennett's PhD is not a completely fraudulent document, this is either an intentional deception designed to fool the few gullible who are persuaded that this man is some kind of authority, or yet another example of the Orwellian Doublethink characteristic of the AIDS church. Bennett’s Oct 6 blog posts his deceptive graph with the sham R2 value of 0.9351.
The real explanation for the straight line shown in this figure is provided by a real mathematician, Darin Brown, in his discussion of the Rodríguez et al. paper that appeared on YBYL on Oct. 9.
But the most plausible explanation to me is that Figure 1 [JAMA Sept 27] is just a mathematical artifact. If you take a cloud of data points that are essentially random (no correlation) and you break them into 5 subgroups by magnitude of the predictor variable and choose the median outcome of the response variable for each subgroup, this will have the effect of obscuring the lack of correlation. It's the statistical equivalent of squinting your eyes so you can't see any details anymore.
I sometimes jokingly tell my sons how I know when things are getting serious: They hand you the blindfold and the cigarette. For your own sake, Nick, don't wait that long.
© 2006 by Jeffrey Dach
Originally published at "You Bet Your Life"