“HIV” tests are self-fulfilling prophecies

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.