HIV/AIDS Skepticism

Pointing to evidence that HIV is not the necessary and sufficient cause of AIDS

“HIV” tests are self-fulfilling prophecies

Posted by Henry Bauer on 2009/05/10

I’ve become accustomed (though not inured) to the fact that what’s publicly disseminated about HIV/AIDS by official agencies and white-coat-credentialed gurus is vastly different from what the research literature has to say.

Rarely if ever do the media mention that a positive “HIV”-test may not signify active infection by a pathogenic immune-system-destroying retrovirus. The research-level literature tells an entirely different story, however; it states accurately that no “positive” “HIV”-test — antibody, antigen, or nucleic-acid (“viral load”) — diagnoses active infection.

The unwary layman would be — or should be — further shocked upon discovering that “HIV” tests are to an alarming degree self-fulfilling prophecies. The fundamental reason for this is that there is no gold standard for any of these tests; there is not even a universal standard for what counts as “positive” on any given test. “HIV” tests are not yes-no, all-or-nothing, positive-or-negative.

The material cited below comes from “Laboratory detection of human retroviral infection” by Stanley H. Weiss and Elliott P. Cowan, Chapter 8 in AIDS and Other Manifestations of HIV Infection, ed. Gary P. Wormser, 4th ed. (2004). Weiss has worked in this field since the beginning, having published since 1984, including with Gallo. At least* 38 of the 429 cited sources in this chapter are co-authored by Weiss. He can surely be accepted as being as knowledgeable, as authoritative about this, as anyone could be.
[* “at least”: The convention adopted in this volume, common in the medical-science literature, is to give only the first 6 names of co-authors and then “et al.”, so Weiss may be co-author on more than 38].

There are “variations in testing approaches . . . [with] patients, persons believed at risk, and screening of blood donors” (p. 147). A given technical result will be interpreted as “positive” or “negative” or “indeterminate” depending on who is being tested:
“A pre-test probability assessment is required whenever test results are to be meaningfully interpreted” (p. 149; emphasis in original); “An essential part of the testing process takes place even before testing is done; that is, the estimation of the probability of infection (the ‘pre-test’ probability). This is necessary in order to interpret a test result appropriately, whatever the purpose — whether it is clinical, counseling or research — and can dramatically impact the predictive value after testing (or ‘post-test’ probability) (p. 159; emphases added).

In other words, “HIV” tests don’t distinguish with certainty between presence and absence of “HIV” antibodies or of “HIV” antigens or “HIV” RNA or pro-viral DNA. Part of the reason is that lack of a gold standard. With antibody tests, another part is that “the precise spectrum of component antibodies remains undetermined” (p. 155); and a further part — sufficient in and of itself — is that the most commonly used first test, ELISA, involves the measurement of the intensity of a color, which can be anything from transparent to opaque. The possible variations in that range are infinite, there are no discrete steps. Therefore there has to be chosen an arbitrary “cut-off”: a decision has to be made that opaqueness above a certain degree shall be regarded as “positive”. An analogous uncertainty with the Western Blot is the need to decide which protein bands and how many of them shall be regarded as a positive; different laboratories and different countries have adopted different opinions on this score (summary at p. 93 in The Origin, Persistence and Failings of HIV/AIDS Theory).

Every “test” report should therefore be presented in terms of a probability, not “positive” or “negative” (or “positive”, “negative”, or “indeterminate”). Every individual receiving a test report should be counseled on this score; yet innumerable anecdotes indicate that, instead, most people are told that they are “positive” or “negative”. Perhaps this constitutes medical malpractice?

A little table on p. 149 underscores the uncertainty: In low-risk populations (prevalence of “HIV” 0.1%), a “positive” “HIV”-test-result has only about 1 chance in 6 of being a “true” positive as opposed to a false positive; similarly, where the prevalence is 99.9%, a negative test-result has only about 1 chance in 6 of truly being negative.

Even these seemingly precise statements of probability mask further uncertainties, or a circularity in reasoning: after all, the purported prevalence in any actual population can only have been determined on the basis of some sort of “HIV” tests. Still, the significant import is clear enough and independent of numbers. Someone in a low-risk group will be given the benefit of the doubt whenever at all possible. On the other hand, a person regarded as at high risk — a gay man, an African-American, a drug abuser — is likely to be told that he is “HIV-positive”, because a negative or indeterminate test result based on an arbitrary cut-off point is likely to be ignored, or repeated testing will be done in expectation of eventually getting a “positive”: “in persons in whom HIV infection is strongly suspected, additional testing may be necessary even if the initial screening test is negative” (p. 154). “When the prior probability is high (as for persons at high risk from hyper-endemic regions or high risk groups), the positive predictive value of a reactive or strongly reactive EIA is extremely high . . . . Although a confirmatory assay, such as a WB, may give an ‘indeterminate’ result based on simple application of some generic criteria . . . , the use of alternative interpretive criteria or additional tests can often be utilized to confirm the diagnostic impression” (p. 160).

As I said, “HIV” tests have the characteristics of self-fulfilling prophecies. If the physician believes you’re in a high-risk group, indeterminate tests and failure of confirmatory tests shouldn’t dissuade him from looking for ways to pronounce you “HIV-positive”.

Weiss & Cowan give an actual example: “a patient in the U.S. with clinical AIDS who had multiple negative HIV-1 screening tests” [the most sensitive kind!]. Because the person had come from West Africa where there’s a lot of HIV-2, testing was done for that. “In the U.S., HIV screening now routinely includes HIV-2”. The pertinent references come from the late 1980s, before the realization in the early 1990s that so many AIDS patients are indeed “HIV”-negative that a new disease had to be invented, “idiopathic CD4-T-cell lymphopenia”, which might equally and validly be called “non-HIV AIDS”.

The concluding sentences of this review article are commendably cautionary, and one might wish that every practicing clinician, AIDS specialists in particular, would take them to heart:
“The context within which any test is used is of critical importance to its interpretation. No test, per se, should be the basis for diagnosis on its own, but rather a test is merely an aid in correct diagnosis. The practitioner must use test results in the context of a clinical picture to reach an    accurate diagnosis” (p. 172).

Since the late 1990s, though, the Centers for Disease Control and Prevention have classed as “AIDS” any person who is “HIV-positive” and has a CD4 count below 200, even in absence of any “clinical picture” (since there need be no manifest illness). About two-thirds of those now being told they have “AIDS” fall into this category, and so, according to Weiss & Cowan, should not have been so diagnosed. Of course, if “clinical picture” includes that a healthy person is gay or African-American, and therefore in a high-risk group, that apparently “justifies” a positive diagnosis.

As I’ve said, “HIV” tests constitute a self-fulfilling prophecy; a dreadfully self-fulfilling prophecy.

44 Responses to ““HIV” tests are self-fulfilling prophecies”

  1. onecleverkid said

    Fascinating and very well written. Thanks.
    I cannot believe this actually. How many lives have been ruined needlessly? A positive diagnoses is a death sentence and yet it is given out haphazardly. It might as well be a wild guess. I have read news stories about people in African villages being buried alive by family members for being “positive.” And we all know, it was probably a positive Rapid test, no less. Who’s responsible for this? How did we arrive here?

    • Henry Bauer said

      onecleverkid:
      “Who’s responsible for this? How did we arrive here?”
      The responsibility is widespread and diffuse. We arrived here through a long succession of poor decisions and unfortunate mistakes.
      Part III of The Origin, Persistence and Failings of HIV/AIDS Theory describes some of that, beginning with the “observation” that the first AIDS cases were “young, previously healthy, gay men”; they weren’t young, they weren’t previously healthy, and what mattered was excessive use of drugs, not gay sex.
      For the detailed story of mistakes on the purely scientific side, read John Crewdson, “Science Fictions”.

    • Edward Kamau said

      onecleverkid:

      Would you happen to have a source for:
      ‘news stories about people in African villages being buried alive by family members for being “positive.”’

      I’d just like to find out when and where.

      thanks

      emk

  2. Vincenzo Crupi said

    Dear Henry,

    I think that the following reference is quite relevant to this post:

    http://library.mpib-berlin.mpg.de/ft/gg/GG_AIDS_1998.pdf

    These are cognitive psychologists studying human reasoning under risk and uncertainty. They have a very nice field study concerning the use and understanding of HIV-testing. There is no HIV-skepticism. However, the basic probabilistic mathematics of the tests’ predictive value is neatly displayed. And their empirical results are startling.

  3. This is an issue I have spent a lot of time thinking about.

    I’m probably going to attract a lot of wrath when I say that, purely from a mathematical standpoint, there’s nothing wrong with using the characteristics of a patient to “interpret” a diagnostic test result. It’s a routine application of Bayes’ Theorem. In other words, from a mathematical standpoint, there’s nothing wrong with “giving the benefit of the doubt” to someone from a “low-risk group” and “not giving the benefit of the doubt” to someone from a “high-risk group”.

    I can hear Michael and Liam going into fits already. But let me make exactly clear what I’m saying.

    First, I’m assuming a well-defined gold standard is in place, and that we are using a diagnostic test in lieu of that gold standard. Second, when I say “low-risk group”, I simply mean a population with low prevalence (relative to the gold standard). Similarly, when I say “high-risk group”, I simply mean a population with high prevalence (relative to the gold standard). Finally, and most importantly, when I say “interpret”, I mean “assign a posterior probability [of the gold standard] to”. Under these assumptions, whether someone is a member of a low-risk or high-risk group [in mathematical jargon, their “prior probability”] most certainly will affect the interpretation of the diagnostic test. This is just a mathematical fact.

    Now, there are a lot of mistakes in the world of “HIV testing”, but there is only one that really matters. And that is the lack of a gold standard.

    First, a list of mistakes that definitely don’t matter:

    1. Many things “cross-react” with HIV tests, causing them to register positive.
    2. The ELISA test depends on a cut-off value.
    3. The Western Blot test isn’t standardized.
    4. The Western Blot test isn’t reproducible.
    5. The proteins used in the Western Blot test have never been shown to originate from HIV particles.
    6. Lots of people have high viral load with negative antibody test results, or vice versa.

    Why don’t these matter? The orthodoxy has answers to all these points, which they regularly trot out, and which are entirely valid, provided a gold standard exists.

    1. So you have a lot of false positives. We just need better tests to eliminate them.
    2. So what? It’s not a gold standard. Fiddling with cut-off values in order to balance specificity vs. sensitivity in certain situations is a common practice in diagnostic testing.
    3. So what? It’s not a gold standard. People are free to invent whatever diagnostic tests they want. The fact that Australia defines a positive WB differently than the US is no problem.
    4. So what? It’s not a gold standard. While it would certainly be preferable if it had higher specificity and sensitivity relative to itself, nothing is perfect. Even true gold standards aren’t 100% reproducible in practice.
    5. So what? The origin of the proteins is completely irrelevant. (Ironically, they conveniently “forget” this fact, if they ever understood it in the first place, when they say the tests are “more specific” because of the origin of the proteins.)
    6. So what? Two diagnostic tests may disagree. And viral load shouldn’t be used to diagnose anyway. (Again, ironically “forgotten” when a member of a high-risk group repeatedly tests negative.)

    I could go on further. But as you can see, we go round and round the mulberry bush many times like this with them.

    The problem stems from the fact that clinicians only have a vague sense of the meaning of the words “gold standard”, “sensitivity”, “specificity”, and so on. For example, the Wikipedia article on “gold standard” states:

    As new diagnostic methods become available, the “gold standard” test may change over time. For instance, for the diagnosis of aortic dissection, the “gold standard” test used to be the aortogram, which had a sensitivity as low as 83% and a specificity as low as 87%. Since the advancements of magnetic resonance imaging, the magnetic resonance angiogram (MRA) has become the new “gold standard” test for aortic dissection, with a sensitivity of 95% and a specificity of 92%. Before widespread acceptance of any new test, the former test retains its status as the “gold standard.”

    How can something be a new “gold standard” test for aortic dissection, with only 95% sensitivity and 92% specificity? Where on earth did the numbers 95% and 92% come from? I’m not an expert on cardiology, but obviously, they were obtained by comparing results using MRA with something really definitive, like say, actually opening up a patient and seeing a torn aortic wall. The numbers must have come from somewhere. There are no sources given for this particular example, but the mindset is what’s important.

    The Wikipedia article contains the following sidesteps:

    “A hypothetical ideal “gold standard” test has a sensitivity, or statistical power, of 100% (it identifies all individuals with a disease process; it does not have any false-negative results) and a specificity of 100% (it does not falsely identify someone with a condition that does not have the condition; it does not have any false-positive results). In practice, there are no ideal “gold standard” tests.

    Because tests can be incorrect (either a false-negative or a false-positive result), results should be interpreted in the context of the history, physical findings, and other test results in the individual that is being tested. It is within this context that the sensitivity and specificity of the “gold standard” test is determined.

    Quite often the “gold standard” test is not the test performed in a particular individual. In fact, many “gold standard” tests are not performed in the clinical practice of medicine at all. This is because the “gold standard” test may be difficult to perform or may be impossible to perform on a living person (i.e. the test is performed as part of an autopsy), or may take too long for the results of the test to be available to be clinically useful.

    This passage exemplifies the fact that clinicians conflate “gold standard”, “reference test”, and “diagnostic test”. When they say “gold standard”, they really mean, “best available diagnostic test that is practical to apply”. They also use “gold standard” a lot when they mean “reference test”. (“Reference test” simply means the placement of a test against a diagnostic test in the binary testing scheme. For example, Suppose X is an impractical gold standard, and Y is a very accurate practical diagnostic for X. Then Y may be so accurate that to test a new test Z against X, you test it against Y instead of X. Here, Y is a reference test but not a gold standard.)

    But the most telling phrase is “a hypothetical ideal ‘gold standard'”. To my mind, this phrase is nonsense. By its very nature, a “gold standard” is a decision procedure which can actually be implemented to produce a binary result (yes/no). The only way a “gold standard” can be “hypothetical” or “ideal” is if it represents some figurative, imaginative, or ill-formed impression of a pathological state in the mind of the clinician. This is confirmed by an anonymous comment on the discussion page of the Wikipedia article:

    To me it seems there is no contradiction [saying a “gold standard” has less than 100% sens/spec]. The second paragraph tells of what a gold standard should aspire to be, and states that in clinical medicine there are no such ideal gold standards; the imperfect (but still very good) tests are referred to as gold standards. [Emphasis mine]

    When it comes to aortic dissections and the like, this fuzzy thought, this idea of having an “ideal” or “hypothetical” fantasy disease state, has little ramifications, since torn aortic walls actually do exist, and so on. The problem with HIV testing is that clinicians have a mental impression of a disease state that has no correspondence to anything in reality. And then they devise lots of diagnostic tests for it.

    Only by hammering them on the lack of gold standard, over and over again, mercilessly, relentlessly, can the fog be cleared.

    In my view your proof that HIV exists depends on your belief in a nexus between a series of non-specific phenomena (particles, reverse transcription, antigen/antibody reactions and PCR). I contend this does not constitute proof any more than claiming a cigarette smoking patient with weight loss, fever, sweats and coughing up blood has to be suffering from a hitherto unknown and undiscovered variety of lung cancer. I further argue that the epidemiological data, far from “proving” these data are due to the effects of a unique retrovirus, do exactly the opposite. Indeed, as I suggested in my introduction, these data prompt an urgent reappraisal of how and why such non-specific data have been interpreted as proving the existence of HIV. The mistake that has been made is the assumption that finding antibodies that react with culture proteins proves (a) the proteins are constituents of a retrovirus; (b) the antibodies specifically react with these proteins; (c) isolation of a virus. That this is not the case follows from an appreciation of basic science and was, for retrovirologists, the lesson of the HL23V era. It is uncanny that, by changing a few dates, nouns and adjectives in the papers of the HL23V era, it is possible to arrive in the HIV era. — Val Turner, email to Robin Weiss, 1999

    • Gos said

      Darin wrote: “This is an issue I have spent a lot of time thinking about. I’m probably going to attract a lot of wrath when I say that, purely from a mathematical standpoint, there’s nothing wrong with using the characteristics of a patient to ‘interpret’ a diagnostic test result. It’s a routine application of Bayes’ Theorem.”

      No wrath here, Darin, but you will get some encouragement from me to do a lot more thinking about this.

      This may be an acceptED standard, but it’s not an acceptABLE standard, from the standpoint of Bayesian mathematics. In fact, it’s actually reversed logic.

      This is because a higher seroprevalence DOES NOT eliminate false positives, it merely increases the number of true positives. If you are familiar with Bayesian mathematics (as you seem to be) then you can demonstrate this for yourself simply by running the Bayesian formula on two hypothetical groups — one with seroprevalence of say 5%, and another with a seroprevalence of 0.1%. Use whatever sensitivity and specificity figures you want, but use the same sensitivity and specificity for both groups. What you’ll find is that you have only 5% fewer false positives for the group with higher seroprevalence, but 50X more true positives.

      It must be remembered that seroprevalence doesn’t affect the specificity of the test, it merely affects the proportion of true positives to false positives. That’s all. If you use a test with 99% specificity to test 1000 HIV-negatives from a low-risk group, you’ll get 10 false positives. If you use the same test to test 1000 HIV-negatives from a high risk group, you’ll get the same 10 false positives.

      This sort of reverse logic is very similar to the logic I once used when I was a teenager. I’d been molested at the age of 12, and I later read articles that said that X% of pedophiles were molested as children (I don’t remember the exact percentage but I do remember that it was more than half.) When I read these articles, I nearly committed suicide because I thought I was going to grow up to be a pedophile. Later, I learned that pedophiles actually represent an extremely small fraction of the total number of adults who were molested as children. So in effect, by reading the statistics backwards, I’d come to a fallacious and erroneous conclusion that my chances of becoming a pedophile were very high when in fact they were statistically quite low.

      There are several other points that you have made which are similarly fallacious:

      “1. Many things “cross-react” with HIV tests, causing them to register positive.”

      As Ron White says about hurricanes, “It’s not THAT the wind is a’blowin’; it’s WHAT the wind is a’blowin’.”

      With HIV tests, it’s not THAT so many things cause cross-reactions, it’s WHAT causes cross-reactions that you have to worry about. If you’ll check out a list of the 5 or 6 dozen factors which have been shown to cause false positives on HIV tests, you’ll find that they break down fairly neatly into three categories: 1) “Risk factors” and related factors. [Examples: Receptive anal sex, blood/tissue transfusions, pregnancy in multiparous women, hemophilia]; 2) Infectious diseases unrelated to HIV, but which might be mistaken for AIDS-indicator diseases [Examples: Candidiasis, viral infections, leprosy, tuberculosis, mycobacterium avium, flu, malaria, upper respiratory tract infection, Q-fever with associated hepatitis]; 3) Non-infectious autoimmune diseases which might be mistaken for AIDS, and antibodies which correlate to autoimmune disease [Examples: Systemic lupus erythematosus, hypergammaglobulinemia, rheumatoid arthritis, scleroderma, elevated antinuclear antibody titers].

      Earlier, I pointed out that seroprevalence in a given group doesn’t affect the specificity of the test. However, factors such as the ones listed above do actually lower the specificity of the test. Which means that HIV tests are less specific in persons who have “HIV risks” and persons who have diseases which might be mistaken for AIDS.

      As a result, your claim earlier that it’s mathematically sound to use patient characteristics to determine posterior PPV of a positive test is actually reversed. Because so many “HIV risks” and diseases unrelated to HIV can cause false positives, it would actually be mathematically sound to reduce our estimate of the PPV of a positive test in such cases, since lowered specificity will naturally tend to have a much greater impact on the PPV of a positive test than higher seroprevalence.

      “2. The ELISA test depends on a cut-off value.”

      I think you have failed to grasp the true significance of a test which detects “HIV antibodies” in everybody, regardless of HIV status. (For more info, look up “Everybody Reacts Positive on the ELISA Test for HIV” by Roberto Giraldo, Continuum, Midwinter 1998/9) As Dr. Giraldo points out, the fact that the serum must be diluted to a 400:1 ratio means that in fact we are looking at an extremely slight variance in the amount of “HIV antibodies” found in “HIV-positives” and “HIV-negatives”. So not only does each and every HIV-negative human being on the planet have “HIV antibodies”, but HIV-positives only have the slightest bit more “HIV antibodies” than HIV-negatives.

      This fact, by itself, proves conclusively before the layman or professional that these “HIV antibodies” couldn’t possibly be HIV antibodies or HIV-negatives wouldn’t have them, much less would they have virtually the same amount as HIV-positives (only very slightly less).

      So it’s not THAT the ELISA (and incidentally all 10 bands of the Western Blot as well) has a cutoff, but it’s WHY it has a cutoff. And given what I said earlier about the factors that cause false positives, it’s not hard to see that the factors which cause false positives are capable of making that slight difference in antibody levels that make the difference between a negative and a false-positive result, which in turn means that those in “risk groups” and those who have preexisting disease have the greatest likelihood of testing false positive.

      In addition to completely obliterating any argument that these are “HIV antibodies”, this argument has the added benefit of explaining away any and all correlation that an orthodox advocate might claim between HIV seropositivity, risk groups, and AIDS.

      “3. The Western Blot test isn’t standardized.”

      I’d say that it’s pretty significant that you can test positive in one country and have the same test read in another country and be negative. Do viruses jump off at international borders? Do you check them at customs? No? Then a test which has any validity should give the same result, regardless of what country you have the thing read in.

      “4. The Western Blot test isn’t reproducible.”

      According to Wikipedia: “Reproducibility is one of the main principles of the scientific method, and refers to the ability of a test or experiment to be accurately reproduced, or replicated, by someone else working independently.”[emphasis mine]

      It’s really quite simple: Nothing which is non-reproducible is scientific. Ever. Period. It doesn’t matter whether you’re talking about cold fusion or Hwang-Woo Suk’s claim of human cloning. If it isn’t reproducible, it isn’t science. I don’t make these rules, I just observe them.

      “Now, there are a lot of mistakes in the world of “HIV testing”, but there is only one that really matters. And that is the lack of a gold standard … Why don’t [other arguments] matter? The orthodoxy has answers to all these points, which they regularly trot out…”

      If you really think that the orthodoxy doesn’t have standard, cut-and-paste answers to the “gold standard” question, then you haven’t spent nearly enough time debating with the orthodoxy. They love nothing more than to be challenged with the “gold standard” argument, because it gives them the opportunity to trot out pictures of what they allege are HIV particles, and studies like Jackson et al (Journal of Clinical Microbiology, Jan 1990), to prove that HIV can be “cultured” in 100% of AIDS patients and asymptomatic HIV-positives, and not at all in seronegatives. I would suggest that you read Jackson et al very closely if you’ve never seen it before, or you’re gonna get clobbered one day when an orthodox advocate blindsides you with it. If you need a link or you need help debunking Jackson, I’ll be more than happy to help.

      Of course, there are counters to their arguments against your “gold standard” argument, but some of these counters seem downright petty to the uneducated observer, so unless you’re having this debate in front of a roomful of microbiologists, you’ve lost the argument, and incidentally if you’re debating in front of a roomful of microbiologists, chances are you’ve lost the argument before you even opened your mouth, because they’re not going to give you a fair shake.

      But there are counters to the arguments that the orthodoxy uses against the other half-dozen or so arguments that you claim are worthless, and the counters that are available to you are pretty damning whether you’re debating in front of laymen or professionals.

      The bottom line is that there is no one argument that will prevail in all debates, and if you only know one argument, you’re doomed in any serious debate. Might as well enter a chess tournament knowing only one strategy. You should probably spend more time actually researching these other arguments so that you understand why they are important, and less time taking the lazy man’s way out and trying to distill the entire debate down to a single argument (which is not nearly as infallible as you seem to think it is.)

      — Gos
      gos@nerosopeningact.com
      “Nobody here but us heretics…”

      • Dennis Gor said

        Gos Wrote:

        “studies like Jackson et al (Journal of Clinical Microbiology, Jan 1990), to prove that HIV can be “cultured” in 100% of AIDS patients and asymptomatic HIV-positives, and not at all in seronegatives. I would suggest that you read Jackson et al very closely if you’ve never seen it before, or you’re gonna get clobbered one day when an orthodox advocate blindsides you with it. If you need a link or you need help debunking Jackson, I’ll be more than happy to help.”

        Please post a link for the reference (or please discuss it if it is not readily available online. Thanks.

      • LaVaughn said

        Here’s what I don’t get. If it can be cultured in all seropositives, but not in seronegatives, why don’t they use a culturing test to validate ELISA results, instead of a Western Blot or further ELISA testing? I mean, since virtually every test says it’s not supposed to be used for diagnosis, why do they keep relying further clinical criteria? If they gotten so good at culturing it, wouldn’t that be the best way to determine a true positive result?

      • Gos,

        I stand by my statement “there’s nothing wrong with using the characteristics of a patient to ‘interpret’ a diagnostic test result. It’s a routine application of Bayes’ Theorem.”, provided “characteristics of a patient” is interpreted to mean pre-test probability (aka prevalence). Mathematically, computation of PPV from prevalence, spec, and sens is precisely Bayes’ theorem.

        I’m not sure what you’re driving at in your “reversed logic” discussion. You seem to be confusing spec/sens with PPV/NPV. Your example about the relationship between child molestation and pedophilia is actually a good example of using Bayes’ theorem.

        I think part of the problem may stem from the fact that you’re making a common mistake, thinking that “seroprevalence” means “prevalence” in terms of binary classification testing. “Prevalence”, in binary classification testing, refers to the prevalence of the GOLD STANDARD. If you’re trying to determine the PPV of the Western blot, e.g. then “seroprevalence” is NOT “prevalence”.

        A lot of the other points you make about my “misuse” of Bayes’ simply don’t have content, because, as I’ll say for the TEN-THOUSANTH time, if you haven’t defined a well-defined gold standard, the terms “spec”, “sens”, “PPV”, and “NPV” HAVE NO MEANING. You’re just talking gibberish. I really don’t know how to say this enough times. It’s IMPOSSIBLE to carry on a MEANINGFUL exchange of ideas on anything related to this, when the basic terminology are ambiguous.

        Regarding #2 in particular, you’re completely missing the point. If the ELISA is only a diagnostic test, NOT the gold standard, then it doesn’t matter what the nature of the antibodies are. Where they came from, what they’re directed against. They could come from the rings of Saturn or the moons of Jupiter for all I care. The ONLY thing that matters is WHEN they light up the test. So, the fact there’s a cut-off is irrelevant. In fact, LOTS of diagnostic antibody tests have various cut-off values that trade-off sens vs spec. It’s a very common thing.

        Regarding #3, all you have to do is take the differently defined Western blots as different diagnostic tests. Call WB in USA “WB-CDC” and WB in Africa “WB-Africa”. It doesn’t matter that they’re different, because THEY’RE NOT THE GOLD STANDARD. Who says you’re not allowed to have more than one kind of diagnostic test?

        Regarding #4, this is the only possible serious problem with the tests that is hard to explain away. But even so, not every test is going to be 100% reproducible (have perfect 100% sens/spec compared to itself). So, I’ll grant you something on this point.

        Re: Jackson et al., see my comments below. I’ve read it VERY closely.

        “But there are counters to the arguments that the orthodoxy uses against the other half-dozen or so arguments that you claim are worthless, and the counters that are available to you are pretty damning whether you’re debating in front of laymen or professionals.”

        NO, that’s what I’m saying is WRONG. What I’m saying is, IF we allow to slip in an assumption of a well-defined gold standard, and we allow this assumption to go UNCHALLENGED, THEN NONE OF OUR “COUNTERS” ARE VALID. We lose the debate, BECAUSE WE WILL BE WRONG. Their points are valid and we have no defensible counters to them.

        I’m not saying we should focus on ONE debating point because we’re the best at it, or because I like it best, or whatever. I’m saying we should focus on the one debating point because, IF WE DON’T ADDRESS IT, we lose all other arguments.

        To continue the chess analogy, it’s like developing a whole variety of tactics for a given position, except each of them leaves your king in jeopardy. Sure, we have “counters” to all their lines, but what are good are they, if all of them end with us losing our king? And that’s what’s been going on for years now. We keep repeating the same talking points (repeating the same lines in the chess game), getting our king mated, and wondering why it keeps happening.

      • MacDonald said

        If you really think that the orthodoxy doesn’t have standard, cut-and-paste answers to the “gold standard” question, then you haven’t spent nearly enough time debating with the orthodoxy. They love nothing more than to be challenged with the “gold standard” argument, because it gives them the opportunity to trot out pictures of what they allege are HIV particles, and studies like Jackson et al (Journal of Clinical Microbiology, Jan 1990), to prove that HIV can be “cultured” in 100% of AIDS patients and asymptomatic HIV-positives(Gos)

        Ignoring speculations on what a lay audience might take home for the moment, I have a hard time understanding why Jackson et al would be a knockout argument, although of course one has to be prepared for it. I believe La Vaughn’s counter is the correct one to present to a lay audience anyway:

        Here’s what I don’t get. If it can be cultured in all seropositives, but not in seronegatives, why don’t they use a culturing test to validate ELISA results, instead of a Western Blot or further ELISA testing? I mean, since virtually every test says it’s not supposed to be used for diagnosis, why do they keep relying further clinical criteria? If they gotten so good at culturing it, wouldn’t that be the best way to determine a true positive result? (La Vaugn)

        I have argued the strength of Jackson/Duesberg below, which boils down to the correlation between negative results: WB, serology, PCR etc. might not always agree on who is infected (although they do so in Jackson et al.), but in general they show sufficient agreement on who is not infected, as per Duesberg’s argument, given below in this series.

        But a gold standard does not arise out of correlation or agreement between tests alone, so we could still ask what that agreement refers to. The inescapable answer is “true infection status”:

        “The evaluation of the sensitivity and specificity of PCR for the diagnosis of HIV infection in infants is particularly difficult because there is no reference or ‘gold standard’ test that determines unequivocally the true infection status of the patient…”
        Owens DK et al. “A Meta-analytic Evaluation of the Polymerase Chain Reaction for the Diagnosis of HIV Infection in Infants”. JAMA. 1996 May 1; 275 (17): 1342-1348.

        I my experience, the orthodoxy will attempt a variation over the quibble with the meaning of “isolation” and “purification”. Rethinkers, or their ill-prepared lawyers will often say isolation, by which they mean purification before isolation. But technically, these days, isolation refers to something else, for instance extracting “genomic HIV” from a cell soup. This “viral soul” is then cloned as an allegedly infectious particle (transfection), at which stage it has indeed been “isolated” completely from the original soup.

        The strategy, then, is to ridicule the Rethinker for his/her lack of grasp of technical terminology and simply dodge the substantive issue. (AIDSpravda Credo: We never debate denialists on the issues)

        Likewise, they will roll their eyes and say that we don’t understand what gold standard means, ultimately trading in a possible confusion between what the gold standard determines (Owens et al.) and the gold standard test – the tool that does the determining.

        If anybody has followed my namesake’s exchange with Snout on New Scientist, they will have seen a classic example of how that plays out (except that he cut and pasted the wrong quote to begin with, Abbott test kit insert instead of Owens et al.- NOT part of the strategy)

        However, Owens et al takes care of that argument as well by using the delightful expression “determine unequivocally true infection status”.

        Snout descended into the sewers pretty quickly, but let us help him along a little bit: Could there conceivably exist something else, something which is not a test per se, but which determines unequivocally the true infection status, i.e. the presence of the virus? Yes Sir, proper virus isolation. The question then is, why has Owens et al., or anybody else in the history of lavish HIV/AIDS, funding not used such a virus isolation procedure to determine specificity and sensitivy of PCR, and the other tests?

        Duesberg is unfortunately not available for comment, and since he is the one who has furnished the orthodoxy with their best pro-isolation arguments, they’re apparently stuck until he comes out of retirement and helps them with this problem – unless of course Gos or Darin has a solution. . .

      • I want to make a clarification to what I said above. When I said “we will be wrong, unless we address the isolation issue”, I was ONLY referring specifically to the issue of the accuracy of the various tests, NOT to the issue of HIV causation. I think there are other strategies that do manage to sidestep the isolation issue, yet at the same time, are very effective at casting doubt on viral causation. Some of Duesberg’s early epidemiological arguments fall into category for me. Ditto for alternate causation hypotheses which seek to displace viral causation altogether (oxidative stress, gut microflora, etc.), and Bauer’s original papers on HIV antibody test demographics, e.g.

        I think I understand what you were getting at re: child molestation and pedophilia example. The problem there is that people confuse P(A|B) (probability A given B) with P(B|A) (probability B given A). That’s not a MISUSE of Bayes’ theorem, it’s a misunderstanding of conditional probability. It is STILL true that Bayes’ theorem will tell us that someone who was molested as a child has a higher probability of being a pedophile than someone who was not; however, it doesn’t mean it’s equal to the probability that someone who is a pedophile was molested, it just means because the pre-test probability is so incredibly small, that the probability increases from miniscule to very, very unlikely.

        MacD, you REALLY hit the nail on the head those last 2 paragraphs. IF they really believe Jackson et al. furnishes a virus isolation process (not a test “per se”, although any process which gives a binary answer would meet the definition of “test” to me), why have they NOT used it to determine specificity and sensitivity of the various tests? This is the line of argument we should pursue with them — no matter which way they answer, they’re “damned if they do, damned if they don’t”, so to speak.

      • MacDonald said

        I should perhaps also clarify which Duesberg argument I am referring to regarding correlation between negative test results. It is the following:

        However, the Papadopulos-Lanka challenge, that HIV does not exist, fails to explain (i) why virtually all people who contain HIV DNA also contain antibodies against Montagnier”s HIV strain -the global standard of all “HIV tests”- and (ii) why most, but certainly not all people who lack HIV DNA contain no such antibodies. The presence of HIV-reactive antibodies in some uninfected people reflects an inherent limitation of tests for antibodies against viruses and other microbes. Since even the simplest microbes display thousands of antibody docking sites, termed epitopes, antibodies against a given microbe may cross-react with an otherwise unrelated microbe if the two share some epitopes.

        The postulated almost-perfect correlation between a negative HIV DNA test and a negative antibody test (WB) is what is so impressive, because it implies great specificity of HIV antibodies (Darin will have to excuse me for using the term specificity about the relation between antibody and antigen rather than the relation between tests and antigen/antibody). But how good is the correlation really, and what is the nature of this ‘HIV DNA’?

        What is less impressive about Duesberg’s isolation argument is that the extraction and cloning of ‘HIV RNA’ is still an indirect method. Duesberg IMO breaks the rules of engagement when he challenges Perth and Lanka to explain where ‘HIV RNA’ comes from if not an exogenous virus. By making the genetic material a coherent viral entity by default, Duesberg is basically kiling the discussion.

        In their reply Perth point out, correctly IMO, that it is not their task to explain where ‘HIV RNA’ comes from. Besides any answer is bound to be highly speculative, which means that Duesberg’s challenge amounts to a demand that Perth prove the negative, that this is NOT the RNA of a unique, exogenous virus.

        Peth’ counter is sound: it is not their task to prove a negative, rather it is Duesberg’s task to deliver positive, direct proof that his ‘HIV RNA’ is indeed HIV RNA.

        Duesberg’s Exogenous-Virus-By-Default position is very unfortunate because it has deprived us of the person best qualified by far to meet his own challenge.

        There is an RA event coming up, and I for one would very much like to see an objective, open-minded discussion of these three related issues; the lack of a viral gold standard, the specificity of HIV antibodies and the possible origin and nature of ‘HIV RNA’, headed by Prof. Duesberg.

        This would and should not be a discussion about the existence or non-existence of the Virus. The framing of the issue in existential terms is wrong, crude and has done great damage. What we have is a signifier, HIV, and a signified, or rather a plethora of signifieds. The primary task before us is to examine the relationship between them, not their ontological status.

  4. Michael said

    “…from a mathematical standpoint, there’s nothing wrong with “giving the benefit of the doubt” to someone from a “low-risk group” and “not giving the benefit of the doubt” to someone from a “high-risk group”. and “I can hear Michael and Liam going into fits already. But let me make exactly clear what I’m saying.”

    Yes, Darin, you are correct about the fits, and deservedly so with good reason I believe. Millions of Real Live Human Beings, just like yourself and your family members are being diagnosed and adversely affected here, not stick figures on a mathematicians chalkboard.

    And we are not talking about a possibly joy-filled pregnancy test, or a bit of a let down that the test failed and the happy couple are not on their way to a family of 3.

    We are not talking about common flu illness where the consequence might by missing a few days of work or missing a vacation or taking some likely innocuous short treatment of antibiotics.

    But particularly, as we are talking about real life/death consequences in real peoples lives, such as suicide, or such as the diagnosis itself creating chronic stress resulting in the very illnesses attributed to the purported virus, or such as taking a lifelong subscription to black label drugs.

    So while mathematically proper, to a mathematicians best tools, or from a heterosexual lab researcher who has nothing at risk for themselves or their own family, the use of bayesian theory may be just fine to do use for coming up with best guess statistics or probabilities.

    However, from a humanitarian aspect, it is immoral and borders on criminal to be using such best guesswork statistics to base a diagnosis for anyone presenting themselves as an authority to be giving someone a possibly life wrecking diagnosis that is not all that different from a court judge imposing a death sentence on a prisoner.

    There is no room whatsoever for anyh such “guess work” to be used diagnostically without FULLY INFORMING the patient that the diagnosis is simply that! Nothing verified or verifiable, but simply plain old best mathematical probabilities.

    Unless a diagnostician knows for an absolute fact that the person is “infected” by anything, they should not be telling the patient that they are infected, when the truth is that they simply think they might be or even most likely are.

    All who take an HIV test, should be told that the test is nothing but guesswork, regardless of bayes, and regardless of whether there is a gold standard or not.

    All that said, beating up the FDA, hiv researchers, and health authorities who tout the tests as 99.9% accurate on the fact that no gold standard exists, may be the best way to get them to be honest with the patients being diagnosed, and admitting that HIV testing is purely guesswork, to the point that even a mathematician using bayesian theory cannot properly evaluate because there is no gold standard starting point for any probabilities to be correctly based upon.

    • Michael, I didn’t mean to downplay the obvious effects of someone being given a positive diagnosis.

      My main purpose above, as is often the case, was to point out some of their best rejoinders, perhaps even completely valid rejoinders, so that we can sharpen and improve our own presentation. The argument is often put to them that interpreting HIV test results based on patient characteristics is a scientific flaw, when it is not.

      My main purpose is to get us away from flawed arguments, for which they have cut-and-paste valid responses, to good arguments. And that just what I got you to do above. Nothing in medicine should ever have the certainty to warrant the kind of psychological sentence implied by a positive HIV result. Regardless of the science or math. The psychosocial nature of the test itself is immoral. That’s an argument we should pursue. But often we get sidetracked into making this moral argument a scientific one, which has a valid rebuttal.

      I should add one important clarification on this:

      When I say that “interpreting HIV test results based on patient characteristics is a scientific flaw, when it is not”, I am referring to using patient characteristics to determine a posterior probability. I am not referring to using patient characteristics to determine the result of the diagnostic test. This is a well-known error called “diagnostic bias” and is most definitely a scientific flaw.

    • Just to be very clear about my last distinction/clarification. There are two situations I’m considering:

      1. You send out 2 identical blood samples (from the same individual) to a laboratory, one labelled “White”, the other labelled “Black”. Despite identical laboratory data, the labelling influences (biases) the laboratory worker carrying out the diagnosis, so that the sample labelled “White” is returned to the clinician as negative, and the sample labelled “Black” is returned to the clinician as positive.

      2. You send out 2 identical blood samples (from the same individual) to a laboratory, one labelled “White”, the other labelled “Black”. The labelling is ignored by the laboratory worker, and both are deemed to be positive, but because of the labelled patient characteristics, the clinican to whom the laboratory results are sent concludes the sample labelled “Black” has a greater probability of coming from an individual who is a true positive, compared to the sample labelled “White”.

      The former (1) is a scientific flaw. Patient characteristics should not influence the laboratory result.

      The latter (2) is not a scientific flaw. Patient characteristics can (should) be used to adjust pre-test (prior) probabilities to post-test (posterior) probabilities.

      Now above, I’m considering a hypothetical binary test. Of course, with HIV tests, there is no gold standard, so prior and posterior probabilities have no meaning.

      I understand the HIV tests are wrong on many grounds, both scientific and moral. But we only hurt ourselves when we attack as unscientific procedures which are actually quite common and well-understood in medical testing. In other words, when we wish to attack unscientific practices such as (1), but we mistakenly confuse (1) and (2), and end up attacking (2), we run the risk of losing credibility with medical testing professionals. So we should keep this distinction between (1) and (2) above very clear.

      • Henry Bauer said

        Darin:
        I have no disagreement with you over a distinction between technical matters and matters of judgment. But I think the title of my post remains accurate, doesn’t it? Whether it’s the clinician or the lab, “HIV” tests are self-fulfilling prophecies becase a given technical result is interpreted according to prior probability.

      • Yes, you’re right, the title of your post is still accurate. My point is that the reason is not “because a given technical result is interpreted according to prior probability”, but because of a lack of gold standard, the reasoning from prior to posterior probability is circular logic: “If we know a positive WB comes from a black, then it’s more likely to be a true positive than if it comes from a white. How do we know this? Because blacks test WB positive more often. Or because we all know AIDS came from Africa. Or because blacks are sexually promiscuous and black men are on the down low.” That’s completely circular, not to mention racist. When Bayesian probabilities are correctly used, they are not “self-fulfilling”. That’s not the case with HIV.

      • Henry Bauer said

        Darin:
        AGREED!

  5. Henry Bauer said

    cooler:

    You sent three comments, and I e-mailed you — to the address you had given — the following:
    “I think you have some points probably worth making, but the three comments you sent are a bit incoherent, and I don’t understand well enough what you want to say to be able to edit them. How about submitting a single, clearer and more concise, comment?

    Thanks!”

    My e-mail to you was returned as undeliverable. Please note what I say about that in the “Re Comments” page.

  6. onecleverkid said

    Do you suppose the POW (“Prevention On Wheels”) mobile “HIV” testing vans, parked in front of popular gay nightclubs in Los Angeles, are full of highly educated specialists who carefully explain to the (drunk and vulnerable) “high-risk” men who enter that their “positive” Rapid test result is most likely meaningless? I would guess, based on the inaccurate characterization of “HIV” testing as some form of “prevention,” that their own understanding of the test, and the diagnoses they are handing out, are lacking in any of the finer points explained in this blog.

    This type of “HIV” testing is targeted, predatory and likely to lead to more “positive” results, wouldn’t you say? The scenario is almost comical, “Hey guys, go order a round of drinks, I’ll be right there after I get tested! See ya…….” It has given rise to a new cultural phenomenon of wearing one’s “neg” results as a badge of honor, posting the date and result on their online profiles with pride.

  7. Michael said

    Here is an interesting one for you to ponder Henry,

    Just how was anyone even diagnosed before HIV tests were accessible to the public in 1985?

    Look at this hillarious rewriting of history from Australia’s first and largest AIDS Advocacy Group, the Bobby Goldsmith Foundation as it describes the 1983 diagnosing and 1984 death of Bobby Goldsmith himself:

    http://www.bgf.org.au/site/index.php?pageID=181

    The piece says he was diagnosed with HIV in 1983! How could he have been diagnosed with HIV when it was not identified until April of 1984? It says he died of “AIDS related illness” in June of 84. What does that mean? Most likely means that he had been put into chronic stress by his diagnosis, which alone caused his immune system to be suppressed, and it is likely that he died of good old fashioned pneumonia or some other common cause of death.

    No wonder those defenders of HIV theory from Australia, such as Chris Noble and Snout are so easily offended by us dissidents. They have a lot of historical falsehoods to defend.

    • Henry Bauer said

      Michael:
      The kindest interpretation, I think, is that HIV/AIDS or HIV=AIDS has become so ingrained that people don’t distinguish between them; so someone diagnosed with AIDS in 1983 is now said to have been diagnosed with HIV!

  8. cooler said

    Hi.
    My points were that According to Duesberg et al there is a gold standard, the HIV PCR. In the Jackson et al. study everyone with a positive HIV PCR had a positive antibody test, and nearly everyone HIV negative had a negative PCR.

    http://www.duesberg.com/papers/continu1.html

    If this is accepted as a gold standard, then repeat testing would be more sound IMO than looking at what risk groups the person is in.

    Nevertheless, I know there are paradoxes with the tests, ie if the proteins on the WB are specific to HIV why wouldn’t only one positive protein be sufficient to be diagnosed as HIV positive? Why do dogs test positive on some proteins on the WB? So I see good points on both sides on the isolation question, but as I’m not an expert I do not know what the correct answer to this dilemma is. As a layperson myself I think Koch’s postulates are much more easy to understand than proper techniques of viral isolation.

    Secondly, if anything to do with the patient lends more credence to a laboratory result it should be how the patient feels more than being part of any risk group. If you feel totally healthy this should call into question any positive test result for a infectious disease. It is very suspect when certain infections like HIV and Hepatitis C have latent periods that get extended from months to decades to explain away people who presently don’t have any symptoms at all.

    • Henry Bauer said

      cooler:
      Dilemmas indeed.
      I too don’t have the expertise to get into the Duesberg vs. Perth-Group technicalities, but it does seem to me that there’s a circularity to the PCR-antibody reasoning that you cite. The only gold standard surely is getting actual particles of whole virus direct from a supposedly infected person. Then you can be sure what the RNA really is and what the proteins really are.

      • cooler said

        What would be really interesting is finding the first study where the HIV DNA PCR was used and from where the genetic code was retrieved from. Was it retrieved from HIV’s true isolation, or some soup from Gallo’s lab? I have no idea. Duesberg says that HIV has been isolated by molecular cloning……although he gets very technical so I don’t understand it all.

      • Henry Bauer said

        cooler:
        The genetic code wasn’t retrieved from isolation of HIV virions, because that’s never been done. “HIV” particles have been SYNTHESIZED, based on beliefs about what the code is, but those synthetic particles self-destructed. One might take that as an indication that it was not the correct code of the hypothetical actively infectious “HIV”.

      • Gos said

        Dr. Bauer,

        Could you elaborate on what you mean by “Synthesized”? …And can you give me references to articles on the subject?

        — Gos
        gos@nerosopeningact.com
        “Nobody here but us heretics…”

      • Henry Bauer said

        Gos:

        Synthesized HIV: Using what is believed to be knowledge of the RNA genome, assemble the units.

        I’ve long been frustrated at losing a key reference, where a bunch of authors including J P Moore (he was not first author) published electron micrographs of “HIV virions” which they had made, and found that they self-destructed in a matter of hours and were not infectious. I got the reference from New AIDS Review http://www.newaidsreview.org/ a year or two ago, it had even a copy of a micrograph photo; I think in J Virology and in the mid- to-late 1990s. I tried unsuccessfully to use the SEARCH at New AIDS Review to find it again.

      • Henry Bauer said

        Gos:

        Here it is:
        1: Virology. 1992 Aug;189(2):695-714.
        Links
        Factors underlying spontaneous inactivation and susceptibility to neutralization of human immunodeficiency virus.
        Layne SP, Merges MJ, Dembo M, Spouge JL, Conley SR, Moore JP, Raina JL, Renz H, Gelderblom HR, Nara PL.

        Theoretical Division, Los Alamos National Laboratory, New Mexico 87545.

        To determine the factors governing inactivation and neutralization, physical, chemical, and biological assays were performed on a molecular clone of human immunodeficiency type 1 (HIV-1HXB3). This included quantitative electron microscopy, gp120 and p24 enzyme-linked immunosorbent assays, reverse, transcriptase assays, and quantitative infectivity assays. For freshly harvested stocks, the ratio of infectious to noninfectious viral particles ranged from 10(-4) to 10(-7) in viral stocks containing 10(9) to 10(10) physical particles per milliliter. There were relatively few gp120 knobs per HIV particle, mean approximately 10 when averaged over the total particle count. Each HIV particle contained a mean approximately 5 x 10(-17) g of p24 and approximately 2 x 10(-16) g of RNA polymerase, corresponding to about 1200 and 80 molecules, respectively. The spontaneous shedding of gp120 envelope proteins from virions was exponential, with a half-life approximately 30 hr. The loss of RNA polymerase activity in virons was also exponential, with a half-life approximately 40 hr. The physical breakup of virions and the dissolution of p24 core proteins were slow (half-life greater than 100 hr) compared to the gp120 shedding and polymerase loss rates. The decay of HIV-1 infectivity was found to obey superimposed single- and multihit kinetics. At short preincubation times, the loss of infectivity correlated with spontaneous shedding of gp120 from virions. At longer times, an accelerating decay rate indicated that HIV requires a minimal number of gp120 molecules for efficient infection of CD4+ cells. The blocking activity of recombinant soluble CD4 (sCD4) and phosphonoformate (foscarnet) varied with the number of gp120 molecules and number of active RNA polymerase molecules per virion, respectively. These results demonstrate that the physical state of virions greatly influences infectivity and neutralization. The knowledge gained from these findings will improve the reliability of in vitro assays, enhance the study of wild-type strains, and facilitate the evaluation of potential HIV therapeutics and vaccines.

        PMID: 1386485 [PubMed – indexed for MEDLINE

      • Gos said

        Thank you so much. 🙂

        — Gos

    • Jackson et al., like many authors, seem hopelessly confused on the meaning of “gold standard”, “sensitivity”, “specificity”, etc.

      For example, they use each of “AIDS patient”, “ARC patient”, “HIV-1 antibody-positive”, and “at least one of the above” as gold standards:

      “Our results indicate that HIV-1 can be isolated [sic, actually “culturing”] from 100% of AIDS patients, 99% of ARC patients, and 98% of HIV-1 antibody-positive asymptomatic individuals. In contrast, the sensitivities of serum antigen testing for HIV-1 in these same patient groups were only 42, 37, and 17% respectively

      “Comparison of HIV-1 culture [i.e. “isolation”, see above] and PCR analysis showed similar sensitivities (97%) and excellent specificities (100%) in the detection of HIV-1 infection” [emphasis mine]

      “AIDS patient” (clinical definition) is clearly an unsuitable gold standard for HIV infection (presence of a microbe). Similarly for “ARC patient” (now defunct term)

      “HIV-1 antibody-positive”, as with any antibody test, is also unsuitable as a gold standard, for reasons Val and Eleni have pointed out repeatedly.

      Jackson et al. confuse things backwards — they think because someone “has AIDS” or “has ARC” or has a positive antibody test result, they must (of course) be infected, and then they go about “isolating” (read: culturing), and then saying the “isolation” techniques have sensitivities and specificities! In other words, “isolation” is not actually a gold standard!

      The point is, until they can agree on a gold standard, until they can present any kind of coherent thought process in this direction, any attempts to evaluate the validity of a given test are gibberish.

    • Gos said

      Cooler and Dr. Bauer,

      I once debated the merits of Jackson et al. (along with Duesberg’s citation of it) with a biologist. I used Bayesian mathematics to show how such a study has only a miniscule chance of being valid (the odds against are literally astronomical), since out of 409 seropositives used in the study, there surely had to have been some who were false-positive, and therefore Jackson et al. shouldn’t have been able to “culture” HIV from at least these individuals.

      Another thing that should be noted about Jackson is that HIV was detected in the “cultures” by indirect means (reverse transcriptase) rather than direct means (isolation), and where it couldn’t be detected in culture, PCR was used instead as an ersatz form of “isolation” (this was how they boosted the correlation up to 100%, from 98.3%).

      So Darin’s criticism of Jackson’s “gold standard” is correct, but for incorrect reasons. Neither the presence of “AIDS”, “ARC” or “HIV seropositivity” were used as gold standards by Jackson et al. The gold standard they used was RT activity in a putative culture, and failing that, they used PCR as a gold standard.

      — Gos
      gos@nerosopeningact.com
      “Nobody here but us heretics…”

      • Gos, you said,

        Neither the presence of “AIDS”, “ARC” or “HIV seropositivity” were used as gold standards by Jackson et al.

        But these are Jackson et al.’s own words:

        “Our results indicate that HIV-1 can be isolated [sic, actually “culturing”] from 100% of AIDS patients, 99% of ARC patients, and 98% of HIV-1 antibody-positive asymptomatic individuals. In contrast, the sensitivities of serum antigen testing for HIV-1 in these same patient groups were only 42, 37, and 17% respectively

        The word “sensitivity” has a very specific meaning in the context of binary classification testing. It is the fraction of true (gold standard) positives which give a positive result for the diagnostic test. The above clearly indicates that the diagnostic (culturing) is being compared to being a member of a “patient group”, in other words, that being a member of a “patient group” is being used as a gold standard. Again, that’s just what the word “sensitivity” means. If they didn’t intend for “patient group” to be interpreted as a gold standard, they should not have used the word “sensitivity”, they should have said, “HIV-1 can be isolated [cultured/recovered, etc.] from x% of patients…” or, if they did indeed intend for culturing to be the gold standard, they should have said, “the positive predictive value of being a member of [patient group] for HIV-1 infection is x%.”

        To be honest, Gos, I don’t really understand your criticism of Jackson et al. When you say some of the 409 seropositives in which HIV was cultured must have been “false positives”, how would you know? What’s your gold standard? And that’s just my point — I don’t really care what Jackson et al. deem their gold standard, all I ask is that they at least be internally consistent in their own paper. The same holds true for HIV/AIDS research as a whole — I just ask that they at least be internally consistent.

        That’s what I meant by the “gibberish” comment above; if your reasoning doesn’t even meet minimum standards of internal consistency, whether it’s “correct” or not is a non-starter.

      • Gos said

        Darin Brown wrote: “The word ‘sensitivity’ has a very specific meaning in the context of binary classification testing. It is the fraction of true (gold standard) positives which give a positive result for the diagnostic test.”

        Darin,

        You are making an extremely common mistake. You’ve got the cart before the horse. It isn’t sensitivity that’s the problem here, it’s specificity.

        In a group of 409 antibody-positives (“confirmed” by WB,) using the standard tests of that time period, there should be some false positives. I have actually calculated the number of false positives that should have existed among those 409 patients, and the minimum number of false positives is 12, and at the upper range it could be anywhere from 98 to all 409. But at the bare minimum (and this was assuming that 100% of the US HIV-positive population was in the gay community, for maximum seroprevalence and therefore fewest false positives,) there should have been at least a dozen or so false positives in such a large group of seropositives.

        Now, as to the significance of this, what it means is that there should have been at least a dozen or so subjects in that group who didn’t actually have HIV. And yet, Jackson et al claim to have “isolated” HIV from 100% of these 409 seropositives (“isolated” being defined in Jackson as detection of RT activity in co-culture or alternately detection of “HIV particles” by PCR).

        It is a common claim of the orthodoxy, when challenged with the “gold standard” argument, to cite Jackson as proof that HIV tests have been validated by the gold standard of isolation. Now, if you’re confronted with such an argument, you can sputter and spew all you want to about how co-culturing isn’t isolation and PCR isn’t isolation, but most people aren’t going to understand what you mean by that. The average joe can, however, understand that Jackson “isolated” HIV from 100% of AIDS patients, ARC patients, and asymptomatic HIV-positives, so at this point you look like a fool to them no matter how correct your arguments are.

        And the point I’m trying to make is this: No one argument is going to win every debate. And if you could distill it down to one argument that made all other questions moot, the orthodoxy would waste no time finding a counter-argument for it that looked good to the public (no matter how specious), and you’d be screwed trying to build a case in the court of public opinion.

        Remember the “Magic Bullet Theory” of the Kennedy assassination? Remember how many people hinged the whole question of a conspiracy on the “Magic Bullet Theory”? Nothing else mattered, there was no way this one bullet could have passed through the bodies of both the President and Governor Connally, and that was all the proof anyone needed that there were multiple shooters and a cover-up at the highest levels.

        I’ve done quite a bit of research into the so-called “magic bullet”, and I for one am 100% convinced that a single bullet, fired from the rear left of the vehicle (possibly the TSBD), passed through Kennedy’s throat, proceeded through Connally’s body, emerged from his chest, struck his wrist, and lodged in his leg, just like the Warren Commission reported. I would go so far as to say that this is possibly the best-documented fact of the entire event. If you look at the Zapruder film (in motion, NOT frame-by-frame), you can plainly see Kennedy and Connally react almost simultaneously to their injuries (Kennedy is just a hair faster, as you might expect if he were hit first.)

        Now, does this prove that there was no conspiracy, and no cover-up? I’m not convinced that it does, but recently those who espouse the lone gunman theory have scored a lot of points with the public using the “Magic Bullet Theory” to embarrass those who allowed the whole of their argument to hinge on this one factor.

        Similarly, if you allow the whole of your argument to rest on a single factor and you don’t even bother to learn the other arguments, you’re going to find yourself similarly embarrassed, and it won’t matter that you have the truth on your side.

        — Gos

  9. MacDonald said

    Darin, Gos, gentlemen, I think you are talking at cross purposes here (and forgive me for starting a separate post, but these myriads of replies to the same point tend to wear a little thin – literally).

    I’ll try and simplify for the benefit of people like Seth Kalichman:

    1. Darin is saying that the convenient jumps between different gold standards are internally inconsistent. Any scientific hypothesis or philosophy must be internally consistent at a minimum – it could still be wrong, but it should at least be logically coherent on its own premises.

    2. Gos is saying that:

    Jackson et al is an example of the “Too-Good-To-Be-True” results HIV science occasionally produces – especially when the objective is to debunk Duesberg.

    Even on their own premises, Jackson et al should have come up with less than 100% correlation between the different tests in such a large study population, because it is acknowledged by HIV researchers themselves that the correlation isn’t 100% – certainly wasn’t back then. Gallo himself only managed to
    “isolate” HIV from ca. 1/3 of his subjects.

    Therefore Jackson’s perfect result is cause for suspicion that the method is not valid. Gos, doesn’t need a gold standard to point out that the perfect result is in itself internally inconsistent; likely a fluke or a result of invalid methodology.

    But, Gos, the logical inconsistency, the jumps/confusion between gold standards, which Darin points to, already contains your point about invalid methodology. It doesn’t matter whether it is RT, Patients, Culture or whatever that is used as gold standard, as long as it is clear that there is confusion about it in the paper = logical inconsistency = invalid methods/premises.

    • At the risk of further talking at cross purposes, I want to first make a few comments in relation to remarks I made above, and then respond to some points Gos made.

      First, I went back and read Jackson et al. again. The original statement I made, they use each of “AIDS patient”, “ARC patient”, “HIV-1 antibody-positive”, and “at least one of the above” as gold standards: is not entirely accurate. Of course, as Gos has pointed out, all of the 409 patients in the study were WB positive.

      This is a crucial point. Jackson et al. speak of “sensitivities” and “specificities” of various procedures. Whenever someone uses these terms, there is a definite binary question one is trying to answer: Does a particular “state of affairs” hold in a given individual? In medical diagnosis, the “state of affairs” is, in the most general sense, “being sick”, and so the definite binary question one is trying to answer is: “Is this person actually sick?”

      So, when Jackson et al. speak of “sensitivities” and “specificities”, we need to ask ourselves, “What question are they trying to answer?”. It seems to me there are two possibilities, and for each possibility there are different motives for asking the question:

      1. Does this person have AIDS?
      2. Is this person infected with HIV?

      The former question would concern disease causation. In other words, you already have a procedure for determining whether someone is an AIDS patient, (ideally, a procedure independent of HIV, although already by 1987 that was not the case), and you are finding the “sensitivities” and “specificities” of various methods of HIV detection in comparison to AIDS, in hopes that you can use this data to support your claim that HIV is indeed at least a plausible causal factor for AIDS.

      The latter question would concern the accuracy of microbial tests. AIDS per se, and viral causation in particular, are not relevant. All that matters is whether certain tests do a good job of determining if someone is actually infected with HIV. Again, this latter question is entirely unrelated to AIDS and HIV causation.

      The problem with Jackson et al. is that, due to the confused thought of AIDS science and the lack of clarification in the paper, it is difficult to tell which question they’re trying to answer. In my opinion, they pull off a delicate form of bait and switch on the reader. From the very first paragraph, we read:

      The role of [HIV-1] as the cause of [AIDS] has been challenged, because HIV-1 was not isolated from 6 to 50% of HIV-1 seropositive AIDS cases reported. … However, at least three studies have reported 100% isolation rates of HIV-1 from AIDS patients studied, but we are aware of no study in which HIV-1 has been isolated or directly detected in hundreds of consecutively tested HIV-1 seropositive symptomatic and asymptomatic patients. In this report, we demonstrate the presence of HIV-1 infection in all 409 consecutive HIV-1 antibody positive patients (including 144 patients with AIDS or [ARC]) … Moreover, we demonstrate that PCR analysis is as sensitive and specific as current culture techniques for the detection of HIV-1.

      And from the closing discussion:

      In summary, we were able to definitely demonstrate that HIV-1 infection is present in all HIV-1 antibody-positive adults, regardless of clinical status, by using a sensitive culture or PCR assay for detection of the virus. Certainly the argument that HIV-1 is not the cause of AIDS because it is not present in all HIV-1 seropositive AIDS patients is no longer tenable. This large study confirms earlier reports that all HIV-1 antibody-positive adults are at risk for the development of AIDS [emphasis mine]

      Based on these excerpts, it is clear that the purpose of the paper is not to determine the accuracy of certain HIV tests, but rather to consolidate certainty around the viral etiology hypothesis. Given this observation, a number of questions come to mind, all related to the crucial fact that all of the 409 patients in the study were WB positive:

      1. Why didn’t they consider AIDS patients who were seronegative, or indeterminate? Shouldn’t they have been interested whether they could have detected HIV by culture or PCR in these people? (Remember, their alleged purpose was to bolster support for viral causation, not to validate a test for HIV infection.)

      2. On the flip side, why did they even consider asymptomatic seropositive patients at all? These people had not even been diagnosed with AIDS, so why did they even care whether they could detect HIV by culture or PCR in these people? (Again, remember, their alleged purpose was to bolster support for viral causation, not to validate a test for HIV infection.)

      The effect of (1) and (2) is that while Jackson et al. give lip service to the purpose of proving viral causation, in actuality they are performing exactly the same research that someone would do if they were validating culturing and PCR as diagnostic tests for HIV infection, using Western Blot as the gold standard. They just dress it up in the language of causation, which by this time was quite easy to do, because positive antibody status itself was considered a pathological state.

      Given this, it is truly remarkable that the orthodoxy cites Jackson et al. as some sort of rebuttal to dissident charges that a well-defined gold standard for HIV infection does not exist. Indeed, the NIAID/NIH “Evidence That HIV Causes AIDS” cites Jackson et al. as evidence that the antibody tests have been validated using culturing and PCR as gold standards! In direct contradiction to Jackson et al. using Western Blot as gold standard:

      Progress in testing methodology has also enabled detection of viral genetic material, antigens and the virus itself in body fluids and cells. While not widely used for routine testing due to high cost and requirements in laboratory equipment, these direct testing techniques have confirmed the validity of the antibody tests (Jackson et al. J Clin Microbiol 1990;28:16; …)

      So, here’s the situation. We have a paper which, by its own admission, presents data that are, to quote MacD, “suspicious”, to say the least. Its procedures (validating culturing and PCR against WB) are at odds with its stated aims (proving HIV causation), its use of precise terminology is unclear, and it’s frequently cited by the orthodoxy as evidence for something which was never one of its goals, and this can be seen by anyone taking time to read it.

      And this was published 20 years ago. And anyone wonders why AIDS science is in a catastrophic state of affairs?

      • MacDonald said

        Forgive me if I rephrase points already made, but it is intriguing that Jackson et al can switch between patients and culture as gold standard. As Darin suggests, that can only be done if,

        1. one considers Western Blot the “ultimate” viral gold standard, and if

        2. one considers all asymptomatic Western Blot positives “patients”.

        Here’s the passage again:

        We demonstrate the presence of HIV-1 infection in all 409 consecutive HIV-1 antibody positive patients (including 144 patients with AIDS or [ARC])… Moreover, we demonstrate that PCR analysis is as sensitive and specific as current culture techniques for the detection of HIV-1.

        It is extraordinary that asymptomatic study subjects are already considered patients in a study that supposedly seeks to demonstrate that these subjects are in fact patients in any meaningful sense. If nothing else, it indicates bias on the part of the authors.

        Note that in the second part of the quote, it is clear that PCR does not detect “patients” but HIV-1. That means it already goes without saying that, when HIV-1 is detected, one has detected a patient — which again was what the study was supposed to prove rather than presume.

        It is also baffling, as Darin has also mentioned, that the specificity and sensitivity of PCR and culture can be judged against WB (WB positive = patient) in a paper that sets out to validate WB using culture and PCR as isolation and “direct detection” of HIV-1 respectively.

        It is the classic merry-go-round of tests validating each other, but we should not be satisfied with merely pointing this out, so I will now challenge our distinguished commentators by laying out the strength of Jackson et al.’s indirect proof.

        1. So-called Rethinkers can talk about the specificity of and origin of “HIV” antibodies all they want, but WB detected those antibodies in 409 people.

        2. Culture and PCR, Rethinkers can call it detection of RT or pieces of RNA to their heart’s content, but the fact is that, at least in the case of PCR, they indicate the presence of a specific antigen.

        WB, PCR and culture do not detect the same thing; one detects the antibody, the others the antigen. If there were no causal relationship between antigen and antibody, how come the correlation is so good (even if Jackson et al. are a little too good to be true)?

        If HIV antibodies are non-specific markers, how come they correlate so well with specific antigens (RT activity in culture or RNA fragments?)

        Where these antigens are not found, i.e. PCR and/or culture negatives, the antibodies are likewise rarely found. How can that be if the designated antibodies are not quite specific to the designated antigens?

        It is true that the old Rethinker objection that like has not been compared with like can be used against Jackson et al., because they call their controls “healthy”.

        None of 131 healthy HIV-1 antibody-negative individuals were HIV-1 culture positive, nor were HIV-1 DNA sequences detected by PCR in the blood specimens of 43 seronegative individuals.

        However, there were some controls from a recognised risk group, which cannot be said to be healthy, again with good correlation:

        In addition, HIV-1 PCR and HIV-1 culture were compared in testing the PBMC of 59 HIV-1 antibody-positive and 20 HIV-1 antibody-negative hemophiliacs. Both methods were found to have sensitivities and specificities of at least 97 and 100%, respectively.

      • Okay, MacD, I’ll give it my best shot.😮

        So-called Rethinkers can talk about the specificity of and origin of “HIV” antibodies all they want, but WB detected those antibodies in 409 people.

        And I’m sure there are more than 409 antibody-positives out there? Not sure what the point is here. Can you elaborate?

        Culture and PCR, Rethinkers can call it detection of RT or pieces of RNA to their heart’s content, but the fact is that, at least in the case of PCR, they indicate the presence of a specific antigen.

        In the sense that the 115-base fragment is definitely there, yes. But even if there were a perfect correlation between antibodies and this fragment, that’s not proof that the fragment came from an exogenous virus and that the antibodies were generated in response to that virus.

        Also, correct me if I’m wrong, but Jackson et al. only performed PCR on the handful (less than 10) of culture-negatives among the 409 antibody-positivies, so as far as the possible correlation between HIV antibodies and RNA fragments is concerned, the paper says nothing.

        If HIV antibodies are non-specific markers, how come they correlate so well with specific antigens (RT activity in culture or RNA fragments?)

        Hmmm… I think HL23V is a counterexample? Aspecific antibodies correlated well with RT activity in culture and similar RNA fragments (in particular, gag and env). But it turned out there were no “HL23V antibodies” after all.

        (even if Jackson et al. are a little too good to be true)?

        More than a little? Others have characterized their results as “non-reproducible”.

      • MacDonald said

        My point is simply this, using the word “predict” a little loosely, the presence of “HIV” antibodies predicts the presence of a specific RNA (or DNA) sequence.

        The absence of “HIV” antibodies predicts the absence of a specific RNA (or DNA) sequence.

        As a bonus, the so-called culturing of HIV worked well for Jackson et al.

        Duesberg explains:

        However, the Papadopulos-Lanka challenge, that HIV does not exist, fails to explain (i) why virtually all people who contain HIV DNA also contain antibodies against Montagnier”s HIV strain -the global standard of all “HIV tests”- and (ii) why most, but certainly not all people who lack HIV DNA contain no such antibodies. The presence of HIV-reactive antibodies in some uninfected people reflects an inherent limitation of tests for antibodies against viruses and other microbes. Since even the simplest microbes display thousands of antibody docking sites, termed epitopes, antibodies against a given microbe may cross-react with an otherwise unrelated microbe if the two share some epitopes.

        Jackson et al. are impressive not so much because of their positive results, but because of the specificity of HIV antibodies, indicated by their negative results. If we assume that the 409 WB-positives were chosen according to a careful test algorithm, and the same criteria applied to the negatives, we see that “false positives”, that is, non-correlation between antibodies and a specific antigen (or RT), is indeed a rare event:

        None of 131 healthy HIV-1 antibody-negative individuals were HIV-1 culture positive, nor were HIV-1 DNA sequences detected by PCR in the blood specimens of 43 seronegative individuals.

        This says nothing about where the antigen, “HIV”, comes from, but it challenges the Rethinker. . . myth? that HIV antibodies are non-specific markers to a greater extent than what might be expected given the “inherent limitation of tests for antibodies against viruses and other microbes.”

      • Henry Bauer said

        Darin, MacDonald:

        Re Jackson et al. and correlations between DNA/RNA and antibodies: Is it not relevant that all the experiments are done with mixtures?

        Recall the oft-cited
        Gluschankof, P., I. Mondor, H. R. Gelderblom, and Q. J. Sattentau. 1997. Cell membrane vesicles are a major contaminant of gradient-enriched human immunodeficiency virus type-1 preparations. Virology 230:125–33
        and
        Bess, J. W., R. J. Gorelick, W. J. Bosche, L. E. Henderson, and L. O. Arthur. 1997. Microvesicles are a source of contaminating cellular proteins found in purified HIV-1 preparations. Virology 230:134–44.

        Antibodies are sought in motley mixtures of cell debris, and “HIV” DNA/RNA in similarly motley mixtures. ELISA and WB “positives” may arise from just about any two or three among a dozen antibodies to supposedly “HIV” antigens, including p24 which apparently is rather ubiquitous especially in Africans.

        Moreover, what “HIV” RNA/DNA even is was inferred in the first place from motley mixtures identified by being antibody-containing. The whole business is circular, isn’t it? The correlation between the “specific” antibodies and the “HIV” nucleotides was pre-determined.

        The correlation would be rather more convincing if
        1. It was ALWAYS there
        2. If the examined materials were pure. Recall the constant refrain that “HIV” mutates incessantly:

        “no two virus isolates are identical…. Within a single … host, HIV-1 population represents a complex mixture, or swarm, of mutant virus variants … [whose] prevalence … is changing … on almost a daily basis (intrahost evolution). Moreover, infected individuals within a human population harbor distinct viruses (interhost or populationwide heterogeneity). Finally, the global HIV-1 pandemic is composed of many local epidemics, which generally differ in … virus genotypes in circulation (global variation)”
        Lukashov V. V., J. Goudsmit, and W. A. Paxton. 2002. The genetic diversity of HIV-1 and its implications for vaccine development. In AIDS vaccine research, ed. Flossie Wong-Staal and Robert C. Gallo. Chapter 3, 93–120. New York: Marcel Dekker.

      • Philip said

        Forgive me if the point I am about to raise has already been brought up but…

        “no two virus isolates are identical…. Within a single … host, HIV-1 population represents a complex mixture, or swarm, of mutant virus variants … [whose] prevalence … is changing … on almost a daily basis (intrahost evolution). Moreover, infected individuals within a human population harbor distinct viruses (interhost or populationwide heterogeneity). Finally, the global HIV-1 pandemic is composed of many local epidemics, which generally differ in … virus genotypes in circulation (global variation)”
        Lukashov V. V., J. Goudsmit, and W. A. Paxton. 2002. The genetic diversity of HIV-1 and its implications for vaccine development. In AIDS vaccine research, ed. Flossie Wong-Staal and Robert C. Gallo. Chapter 3, 93–120. New York: Marcel Dekker.

        If no two virus isolates are identical, then how the heck can researchers claim evidence of transmission by saying that persons A and B have the same strain ergo A must have given it to B (as is often cited in the 2004 porn stars case, the Kimberly Bergalis cases, and some other case studies I’ve read).

      • Henry Bauer said

        Philip:
        That “swarm” quotation is a favorite of mine, I used it also in my book.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s