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Medical Forum / Diseases and Disorders / AIDS / November 2005Effects of ARV Therapy on Mortality
Mocroft A, Vella S, Benfield TL, Chiesi A, Miller V, Gargalianos P, d'Arminio Monforte A, Yust I, Bruun JN, Phillips AN, Lundgren JD. Changing patterns of mortality across Europe in patients infected with HIV-1. EuroSIDA Study Group. Lancet. 1998 Nov 28;352(9142):1725-30. Royal Free Centre for HIV Medicine and Department of Primary Care and Population Sciences, Royal Free and University College Medical School, University College London, UK. amanda@rfhsm.ac.uk BACKGROUND: The introduction of combination antiretroviral therapy and protease inhibitors has led to reports of falling mortality rates among people infected with HIV-1. We examined the change in these mortality rates of HIV-1-infected patients across Europe during 1994-98, and assessed the extent to which changes can be explained by the use of new therapeutic regimens. METHODS: We analysed data from EuroSIDA, which is a prospective, observational, European, multicentre cohort of 4270 HIV-1-infected patients. We compared death rates in each 6 month period from September, 1994, to March, 1998. FINDINGS: By March, 1998, 1215 patients had died. The mortality rate from March to September, 1995, was 23.3 deaths per 100 person-years of follow-up (95% CI 20.6-26.0), and fell to 4.1 per 100 person-years of follow-up (2.3-5.9) between September, 1997, and March, 1998. From March to September, 1997, the death rate was 65.4 per 100 person-years of follow-up for those on no treatment, 7.5 per 100 person-years of follow-up for patients on dual therapy, and 3.4 per 100 person-years of follow-up for patients on triple-combination therapy. Compared with patients who were followed up from September, 1994, to March, 1995, patients seen between September, 1997, and March, 1998, had a relative hazard of death of 0.16 (0.08-0.32), which rose to 0.90 (0.50-1.64) after adjustment for treatment. INTERPRETATION: Death rates across Europe among patients infected with HIV-1 have been falling since September, 1995, and at the beginning of 1998 were less than a fifth of their previous level. A large proportion of the reduction in mortality could be explained by new treatments or combinations of treatments. > Mocroft A, Vella S, Benfield TL, Chiesi A, Miller V, Gargalianos P, > d'Arminio Monforte A, Yust I, Bruun JN, Phillips AN, Lundgren JD. [quoted text clipped - 31 lines] > mortality could be explained by new treatments or combinations of > treatments. But George didn't you get the memo ARV is 'DEADLY' this research just has to be wrong because Rasnick and Mullis say so. The entire EuroSIDA dataset a subset of which was used for this study is even more definitive when it comes to showing the effectiveness of ARV. I have posted references to the EuroSIDA data a huge number of times yet up to this point not a single denialist has bothered to study the information or make any attempt to explain that data's impact on there assertion that ARV kills. Gary Stein snip. >But George didn't you get the memo ARV is 'DEADLY' this research just has to >be wrong because Rasnick and Mullis say so. And within a matter of MINUTES! This according to a rhodochrosite conclave that informed me...but I chose to ignore them! mwahahahaha! >The entire EuroSIDA dataset a subset of which was used for this study is >even more definitive when it comes to showing the effectiveness of ARV. I >have posted references to the EuroSIDA data a huge number of times yet up to >this point not a single denialist has bothered to study the information or >make any attempt to explain that data's impact on there assertion that ARV >kills. Data are irrelevant. The intelligent designer done told me so. We are borg. Resistance is mutable. George Mary Magnetite I am not impressed by this confuscation (if that's a made up word - I still like it). I haven't a bloody clue what these researchers have done. 1215 of 4270 died and that's the only thing I know for sure. Why do they need a death rate expressed in terms of "per 100 person years" of follow up? What is this term supposed to normalize and does it accomplish what it is set out to do? I'm confused by the use of a confidence interval on a mortality rate. The mortality rate from March to September, 1995, was 23.3 deaths per 100 person-years of follow-up (95% CI 20.6-26.0), and fell to 4.1 per 100 person-years of follow-up (2.3-5.9) between September, 1997, and March, 1998. I don't get it. We are 95% certain that between 20.6 and 26.0 deaths per "" occurred between such and such dates? Why isn't that a "hard" number? Did they die or not? These numbers may seem impressive but I have so many questions about these patients that I don't know where to begin before I agree with the authors qualified "could" conclusion. What was the health of these patients upon entry into this study? What was the criteria used for treatment? How was the "no treatment" group defined? Were they simply those who didn't take so-called ARV's? Were they treated for presenting diseases? Were they junkies? Were they health food juicing vegans? How do I know? What's the overall "health" of the surviving treated group? Are they barely hanging on? Are they in and out of the hospital? Are they leading "productive" lives? Were they ever "sick" in the first place? I suppose you can tell me I'm too dumb to understand science and to just shut up and take your word for it that this is a definitive study. Go ahead, but that just make me even more suspicious that there's something to be said for those who say it's time to take a good hard look at what us morons have been being told all these years. No, tryingtomakesomesenseofit, you are correct. These kinds of studies are nonsense. The begin with assumptions that have not been demonstrated to be acccurate. Often, the studies that supposedly demonstrate the underlying assumption actually show the opposite. Here's an easy example: there is a claim that only two kinds of fatty acid molecules are "essential," yet there is no biochemical reason for this to be the case. Experiments were done that did not have proper controls, yet even there, some of the pregnant animals gave birth to healthy offspring. Thus, if these molecules were truly essential, there would have been no healthy offspring, yet they use this to say that it has been "proven" that these molecules are essential. In the case of "AIDS," there are definitions of what is "AIDS" and what is not, and these definitions are not scientific, that is, based on controlled experiments which follow the scientific method. In fact, they vary from one nation to another, as does "HIV positive" status. If the underlying assumptions are not accurate, it's a "garbage in, garbage out" proposition. However, the other problem is that even if they are correct, it does not mean that the "HIV/AIDS" claims are correct, because such toxic medication can act as a surrogate immune system, at least for a while (until the liver begins to fail). Thus, this would need to be controlled for. I have been suggesting for a couple of years now that one only needs to keep biochemical activity low, while ensuring that the body can produce energy efficiently (mitochondria need to be protected and "fed" properly). I have made offers to do animal experiments to demonstrate my claims (which are all based on solid biochemical evidence), but nobody will take me up on any of my offers. Why? Because the loser must pay for all expenses, and while these people are generally quite deluded, they seem to be cheapskates first and foremost. Here's something to consider in this context: A Scientist Rebuts Business Day's Praise Of AIDS Drugs By David Rasnick, Ph.D. David Rasnick, a professor of molecular and cell biology at the University of California at Berkeley, is currently a visiting scholar in South Africa. The following is a letter he wrote this week to Business Day. The headline on an August 2 story by Chris van Gass in Business Day about a study published in The Lancet announced, "TAC welcomes U.K. study showing AIDS drugs prolong life." The article in the July 30 issue of The Lancet did say, "Treatment Action Campaign (TAC) has welcomed research by British scientists showing that cocktails of AIDS drugs cut the rate of progression from HIV infection to full-blown AIDS by 86 percent compared with patients not receiving treatment." The article also begins by saying, "For ethical reasons, there has been no placebo-controlled randomized trial of HAART (Highly Active Antiretroviral Therapy). The effectiveness of this treatment over several years is therefore unknown." This is what I, and many other "dissidents," have been saying for years. In other words, after American taxpayers have spent a total of $170 billion on AIDS (through 2005), there is still no controlled clinical study showing that people taking the antiretroviral drugs live longer, or at least better, lives than a similar group of people not taking the drugs. And, as The Lancet authors acknowledge, their study doesn't qualify either. The authors state, "Without trial evidence, this information must come from observational cohort studies. However, estimation of treatment effects in observational studies is not straightforward...." Indeed it is not, yet that is exactly what the authors did by using a "novel methodology to overcome this problem." To generate the results that so heartened TAC, the authors had to resort to a statistical method that they acknowledge "is not widely used in clinical research" and, in fact, "may not be widely known in the clinical research community." Yet, their results are not obtainable without this unused and unknown methodology. Furthermore, their "results depend on the assumption that treated and untreated individuals with the same values of measured prognostic factors were similar. Prospective information about the reasons that patients remain untreated is not recorded in the database, so we cannot address this issue directly." They also "assumed that once on therapy, a patient remains on therapy." Finally, the authors wrote that they "used a combined endpoint of AIDS or death from all causes, which has been widely used in clinical HIV/AIDS research. We would have liked to examine the two endpoints separately. In the era of HAART, an increasing proportion of deaths is not associated with recent AIDS-defining events, and the current definition of AIDS is no longer a near-complete marker for overall progression. We could not do so for two reasons: the number of deaths during follow-up was small, and good information on causes of deaths is lacking in the Swiss and other cohort studies." With the help of these assumptions, considerable hand waving and an unused and unknown methodology, the authors concluded in the absence of basic mortality data that "HAART reduced the rate of progression to AIDS or death by 86 percent, and that its effectiveness compared with no treatment increased with time since initiation." The authors' chart titled "Estimated effect of HAART from unweighted (standard) and weighted Cox models" captures the artificialness of their results. It shows four different results for the same data ranging from marginal, if any, effect to their 86 percent effect based on their "novel methodology." Why would anyone uncritically accept such a conclusion based on flimsy data and unproved methodology, when doing so entails tremendous consequences? Only a placebo-controlled randomized trial can determine whether or not a therapy prolongs or improves life compared to no therapy. >Here's something to consider in this context: > [quoted text clipped - 6 lines] >in South Africa. The following is a letter he wrote this week to >Business Day. http://groups.google.com/group/misc.health.aids/msg/01382d8dbbef8921?hl=en  SignatureDavid Canzi "I am not denying anything." -- Celia Farber >>Here's something to consider in this context: >> [quoted text clipped - 8 lines] > > http://groups.google.com/group/misc.health.aids/msg/01382d8dbbef8921?hl=en The authors of the Lancet article Dr. Rasnick is criticizing used a relatively new statistical method, "marginal structural models", to better extract the signal of causation from the noise of confounding factors in the observational data. Any statistical method is mathematical by nature. This method will be based on assumptions about the effects a causal relationship and confounding factors will have on the observational data, and justified by mathematical arguments. There is no sign that Dr. Rasnick has examined the assumptions and arguments supporting the new method. Therefore, when he criticizes the new method as "unused and unknown", he is criticizing the new method not for any known flaws, but for the fact that he doesn't understand it. SignatureDavid Canzi "I am not denying anything." -- Celia Farber >"There is no sign that Dr. Rasnick has examined the assumptions and arguments supporting the new method. Therefore, when he criticizes the new method as "unused and unknown", he is criticizing the new method not for any known flaws, but for the fact that he doesn't understand it." Please explain this "unused and unknown" method to me, Mr.Canzi. I guarantee you I'll understand it. > >"There is no sign that Dr. Rasnick has > examined the assumptions and arguments supporting the new method. [quoted text clipped - 4 lines] > Please explain this "unused and unknown" method to me, Mr.Canzi. I > guarantee you I'll understand it. Why don't you just read the paper yourself claster? Gary Stein >>"There is no sign that Dr. Rasnick has >examined the assumptions and arguments supporting the new method. [quoted text clipped - 4 lines] >Please explain this "unused and unknown" method to me, Mr.Canzi. I >guarantee you I'll understand it. I don't know the method. I don't need to just to point out that Rasnick's criticism is not based on any actual knowledge of it. His sole objection is that the method is new -- not yet widely known and not yet widely used. Obviously Rasnick's paradigm is being threatened by new knowledge and he's reacting defensively. SignatureDavid Canzi "I am not denying anything." -- Celia Farber snip >I don't know the method. I don't need to just to point out that >Rasnick's criticism is not based on any actual knowledge of it. Sort of like Iconoclaster who never reads any of the papers. George M. Carter Mr Carter I read this paper you posted. Every word. I can't make sense of it, so since you're so smart and you claim to understand how they came to this conclusion, would you mind explaining it to me? >Mr Carter >I read this paper you posted. Every word. I can't make sense of it, so >since you're so smart and you claim to understand how they came to this >conclusion, would you mind explaining it to me? Which paper? >"Sort of like Iconoclaster who never reads any of the papers." Not true, mr. Carter, and you know it. I've often commented on papers that wer quoted here. Even on 20 of the 29 fluff papers from tht AIDS meeting in Rio. But lately I see a tendency to start new threads where no new thread is warranted, and often I'm not even aware that a link has been presented to a relevant paper. Is this a dodging manoever? >>"Sort of like Iconoclaster who never reads any of the papers." > >Not true, mr. Carter, and you know it. I've often commented on papers >that wer quoted here. Most of which you never read. Your comments kinda indicated that, sweetie. Iconoclaster This study is available for free on the Lancet website. You apparently don't like it either. Can you explain to me why? Do you understand what they have done here? Why in the world is a mortality rate expressed with a CI? Shouldn't mortality be a hard number? 10/100 died 10% mortality CI=100% What am I missing here? How can one tell me with a straight face that they are 95% confident that between 20.6% and 26.0% have died? > Iconoclaster > This study is available for free on the Lancet website. You apparently [quoted text clipped - 4 lines] > What am I missing here? How can one tell me with a straight face that they > are 95% confident that between 20.6% and 26.0% have died? What paper are you talking about if you want people to comment you need to reply to messages in a manner that leaves the previous posters data in your reply so that the context for your question remains. Most of us don't save messages after the first time they have been read. Gary Stein Mocroft A, Vella S, Benfield TL, Chiesi A, Miller V, Gargalianos P, d'Arminio Monforte A, Yust I, Bruun JN, Phillips AN, Lundgren JD. Changing patterns of mortality across Europe in patients infected with HIV-1. EuroSIDA Study Group. Lancet. 1998 Nov 28;352(9142):1725-30. Give me a break - you're not smart enough to find the origninal post? I thought I was the stupid one here. >Mocroft A, Vella S, Benfield TL, Chiesi A, Miller V, Gargalianos P, >d'Arminio Monforte A, Yust I, Bruun JN, Phillips AN, Lundgren JD. >Changing patterns of mortality across Europe in patients infected with >HIV-1. EuroSIDA Study Group. Lancet. 1998 Nov 28;352(9142):1725-30. Royal Free Centre for HIV Medicine and Department of Primary Care and Population Sciences, Royal Free and University College Medical School, University College London, UK. amanda@rfhsm.ac.uk BACKGROUND: The introduction of combination antiretroviral therapy and protease inhibitors has led to reports of falling mortality rates among people infected with HIV-1. We examined the change in these mortality rates of HIV-1-infected patients across Europe during 1994-98, and assessed the extent to which changes can be explained by the use of new therapeutic regimens. METHODS: We analysed data from EuroSIDA, which is a prospective, observational, European, multicentre cohort of 4270 HIV-1-infected patients. We compared death rates in each 6 month period from September, 1994, to March, 1998. FINDINGS: By March, 1998, 1215 patients had died. The mortality rate from March to September, 1995, was 23.3 deaths per 100 person-years of follow-up (95% CI 20.6-26.0), and fell to 4.1 per 100 person-years of follow-up (2.3-5.9) between September, 1997, and March, 1998. From March to September, 1997, the death rate was 65.4 per 100 person-years of follow-up for those on no treatment, 7.5 per 100 person-years of follow-up for patients on dual therapy, and 3.4 per 100 person-years of follow-up for patients on triple-combination therapy. Compared with patients who were followed up from September, 1994, to March, 1995, patients seen between September, 1997, and March, 1998, had a relative hazard of death of 0.16 (0.08-0.32), which rose to 0.90 (0.50-1.64) after adjustment for treatment. INTERPRETATION: Death rates across Europe among patients infected with HIV-1 have been falling since September, 1995, and at the beginning of 1998 were less than a fifth of their previous level. A large proportion of the reduction in mortality could be explained by new treatments or combinations of treatments. Yeah, that was it, Mr. Carter. My previous comments stand. A person is dead or he isn't. If they want to do a statistical study, let them *predict* the number of deaths per 100 person-years. Counting the dead, and then reasoning backwards is not very convincing. >Yeah, that was it, Mr. Carter. My previous comments stand. A person is >dead or he isn't. Generally speaking, yes. (Tho there are cases like Terri Schiavo where life and death are relative.) >If they want to do a statistical study, let them *predict* the number of >deaths per 100 person-years. >Counting the dead, and then reasoning backwards is not very convincing. No, once again you've distorted the findings to press your whacked out agenda by making an invalid criticism of a trivial point while ignoring the main findings of the study. George M. Carter >"What am I missing here? How can one tell me with a straight face that they are 95% confident that between 20.6% and 26.0% have died?" You are not missing anything. THEY are. The people who perpetrate clinical trials are notoriously bad at statistics. They try to cover it up, though, with scholarly-sounding buzzwords. And afterward, they accuse any critics of not understanding their methds. In reality, they are just following a fixed recipe from a cookbook on statistics by Ronald Fisher. And that's why you get served up a number of people who died with a C.I. of 95%. OF COURSE this should be a hard number, as you said. It may be fractional, because it's normalized on a basis of 100 person-years, but it is a hard number with probability=1, because it is an observed fact. This is a common problem I've seen with a lot of this work. I call it "reverse statistics" (or J. Edgar Hoover statistics). It goes like this: You take an observed result. Then you look for a factor that occurs frequently, then you declare that that factor is the cause of the event. An example: There have been 400 car accidents in the past month. In 87% of these cases, the driver was not wearing a tie. Conclusion: Not wearing a tie causes car accidents. (!) Now this is rather obvious nonsense, but in "HIV science" you find the same kind of reasoning: In the eighties, it was reasoned: Among people who came down with full-blow AIDS (any of the 29 flavors), *almost* all of them had a positive reaction for (what's supposed to be) antibodies against (what's supposed to be) HIV. Conclusion: HIV causes AIDS. And let's face it: 20 years later very few people remember that the basic reasoning was wrong in the first place. Epidemiological "evidence" is always suspect. And I'm sure you know: There are lies, damn lies... and statistics. These clinicians don't even know statistics. But they have their cookbooks. |
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