The hands of frontline medical practitioners have been tied treating Covid19 cases because the drugs that work on the virus work against Big Pharma profits. Computers were employed to produce attack papers overwhelming the growing confidence that HCQ helps patients. A recent paper later on describes how medical science is corrupted to follow the money rather than fight disease.
Context: The Attack on Medical Practitioners Using HCQ
What happened in the publishing and press worlds is summarized by Elizabeth Woodsworth, Canadian Health Sciences librarian specialized in medical statistics. Leaked: “Deadly” Hydroxychloroquine (HCQ) to treat Covid 19: How the World’s Top Medical Journals, The Lancet and NEJM, Were Cynically Exploited by Big Pharma Excerpts in italics with my bolds.
On May 22, 2020, the time-honoured Lancet[vi]– one of the world’s two top medical journals – published the stunning claim that 671 hospitals on six continents were reporting life-threatening heart rhythms in patients taking hydroxychloroquine (HCQ) for Covid-19.
The headlines that followed were breath-taking.
Although wider access to the drug had recently been urged in a petition signed by nearly 500,000 French doctors and citizens,[vii] WHO and other agencies responded to the article by immediately suspending the clinical trials that may have cleared it for use.
North American headlines did not mention that HCQ has been on the WHO list of essential drugs since the list began in 1977. Nor did they mention an investigative report on the bad press that hydroxychloroquine had been getting prior to May 22, and how financial interests had been intersecting with medicine to favour Gilead’s new, more expensive drug, Remdesivir.[viii]
The statistics behind the headlines
As a Canadian health sciences librarian who delivered statistics to a large public health agency for 25 years, I sensed almost immediately that the article had to be flawed.
Why? Because health statistics are developed for different purposes and in different contexts, causing them to exist in isolated data “stovepipes.”[ix] Many health databases, even within a single region or country, are not standardized and are thus virtually useless for comparative research.
On May 28, an open letter from 200 scientists to the authors and The Lancet requested details of the data and an independent audit. The letter was “signed by clinicians, medical researchers, statisticians, and ethicists from across the world.”[xii]
The authors declined to supply the data, or even the hospital names. Meanwhile, investigative analysis was showing the statistics to be deeply flawed.[xiii][xiv]
If this were not enough, the lead author was found to be in a conflict of interest with HCQ’s rival drug, Remdesivir: In view of the foregoing, the article was retracted by three of its authors on June 5.
How did this fraud get past The Lancet reviewers in the first place?
The answer emerges from what has remained an obscure French interview, although it has been quoted in the alternative media.[xvi]
On May 24, a closed-door Chatham House expert meeting about Covid included the editors-in-chief of The Lancet and the NEJM. Comments regarding the article were leaked to the French press by a well-known health figure, Dr. Philippe Douste-Blazy,[xvii] who felt compelled to blow the whistle.
His resulting BFM TV interview was posted to YouTube with English subtitles on May 31,[xviii] but it was not picked up by the English-speaking media.
These were The Lancet editor Dr. Richard Horton’s words, as reported by Dr. Douste-Blazy:
“If this continues, we are not going to be able to publish any more clinical research data because pharmaceutical companies are so financially powerful today, and are able to use such methodologies as to have us accept papers which are apparently methodologically perfect, but which, in reality, manage to conclude what they want to conclude.” [xix]
Doust-Blazy made his own comments on Horton’s words:
“I never thought the boss of The Lancet could say that. And the boss of the New England Journal of Medicine too. He even said it was ‘criminal’. The word was used by them.”[xx]
The final words in Doust-Blazy’s interview were:
“When there is an outbreak like Covid, in reality, there are people like us – doctors – who see mortality and suffering. And there are people who see dollars. That’s it.”[xxi]
The scientific process of building a trustworthy knowledge base is one of the foundations of our civilization. Violating this process is a crime against both truth and humanity.
Evidently the North American media does not consider this extraordinary crime to be worth reporting.
How the Science was Rigged Against HCQ
This paper describes how scientific data can be manipulated to serve an agenda. Clinical Efficacy of Chloroquine derivatives in COVID-19 Infection: Comparative meta-analysis between the Big data and the real world Excerpts in italics with my bolds.
In the context of a pandemic with an unknown virus, development of new drugs is a major opportunity for “big pharma” industry, and this is potentially associated with a very high risk of conflicts of interest. This led us to consider these conflicts of interest as a moderator variable in the present work. As major financial issues are at stake, and may impact the interpretation of scientific data, we felt it was important to mention that none of us have conflict of interest with any pharmaceutical company.
The following outcomes were considered: hospitalization rate, duration of cough, duration of fever, clinical cure, lymphocyte count, C-reactive protein level, Interleukin-6 level, thoracic CT-scan imaging, aggravation to severe, death, transfer to intensive care unit (ICU), ventilation, length of hospital stay and persistent viral shedding as assessed by PCR.
Only studies comparing a group of COVID19 patients treated with a chloroquine derivative to a control group without chloroquine derivatives were included. Non-comparative (single arm) studies and studies comparing two groups treated with chloroquine derivatives at different dosages or with different delay of treatment were excluded. Studies were classified as “big data” studies when conducted on electronic medical records extracted by public health specialists and epidemiologists who did not care COVID106 19 patients themselves. Conversely, studies were classified as “clinical studies” when mentioning details of treatments (dosages, duration, contraindications, monitoring…) and conducted by authors physicians (infectious diseases and internal medicine specialists, and pulmonologists) who cared for COVID-19 patients themselves.
Twenty studies were identified involving 105,040 patients (19,270 treated patients) from nine countries (Brazil, China, France, Iran, Saudi Arabia, South Korea, Spain, and USA). Big data observational studies were associated with conflict of interest, lack of treatment dosage and duration, and absence of favorable outcome. Clinical studies were associated with favorable outcomes and details on therapy. Among clinical studies, three of four randomized controlled trials reported a significant favorable effect.
Among clinical studies, a significant favorable summary effect was observed for duration of cough (Odds ratio (OR), 0.19, p = .00003), duration of fever (0.11, p = .039), clinical cure (0.21, p = .0495), death (0.32, p = 4.1×10-6) and viral shedding (0.43, p = .031). A trend for a favorable effect was noted for the outcome “death and/or ICU transfer” (0.29, p = .069) with a point estimate remarkably similar to that observed for death (∼0.3). In conclusion, a meta-analysis of publicly available clinical reports demonstrates that chloroquine derivatives are effective to improve clinical and virological outcomes but, more importantly, it reduces mortality by a factor 3 in patients infected with COVID-19.
All “big data” studies reported a lack of beneficial effect of the treatment and were significantly more likely associated with “Cons” variable (5/5 vs 3/15, p = .004). This was also observed by examination of the meta-analysis forest plot (Figure 2, Table S3 to S8). In addition, both “conflicts of interest” (p = .01) and “not described treatment protocol” variables (p = .004) were associated with “Cons” variable. Conversely, clinical studies were more likely to report a favorable effect of chloroquine derivatives in COVID-19 patients (p <.05). Consistently, clinical studies with detailed treatment protocol were more likely associated with the observation of a favorable effect of the treatment (p < .05).
In the big data analyses, 4 comparisons reported a significant effect, and all were deleterious (4/4). In the clinical studies, 17 comparisons reported a significant effect, and all were beneficial.
The clinical studies used a standardized treatment protocol with methods that included assessment of contraindications, daily dosage, adjuvant measures and duration of treatment with at least 48 hours of treatment before the objective could be assessed. For example, assessment of kalemia and
electrocardiogram is critical prior to treatment, especially when the chloroquine derivative is combined with AZ (37). At the same time, we observed that virtual big data studies did not mention these elements and considered the presence of chloroquine derivative prescription in electronic records in a binary fashion. Obviously, the number of patients included in the database analyses was much higher than the number of patients included in the clinical studies, because these databases are made up of thousands of electronic medical records (EMR). As mentioned in the past (4), this type of studies have tremendous statistical power but are limited by clinical inaccuracy that makes their conclusions difficult to believe.
The major elements of this study are that, overall there is an extremely significant difference between the analyses of data not collected directly by the doctors who cared for patients and the studies carried out by the physicians who set up these studies and cared for patients, including the randomized studies. The second thing is that in these studies conducted electronically, the treatment is never really specified, with the dosage and duration of treatment making it impossible to assess efficacy (dose too low) or toxicity (dose too high). In addition to this major bias, we also noted a significant bias when the authors had conflicts of interest due to their relationship with industrialists trying to market molecules in the same therapeutic framework competing with HCQ.
Overall, and as previously published, the relevance of the analysis of important medical data depends on clinical accuracy (4). Indeed, the discrepancy between clinicians and epidemiologists reflects a major trend, that of the analysis of large medical data, with database warehouse more or less well filled by individuals who are not directly included in the work reported. This analysis is unrelated to the observations made by physicians who are in direct contact with patients and which lead to divergent interpretations and opposite conclusions, which are of real interest and show that the world predicted by Baudrillard (39); that of a parallel world of numerical analysis completely disconnected from reality; is being born.
Under these conditions, a meta-analysis allowing for the combination of different studies makes it possible to identify a general trend. This makes it possible to reconcile the chloroquine derivative efficacy that many doctors have perceived with the results of the first published studies. This meta-analysis is based on several studies, including four RCTs, and identifies a favorable trend toward the benefit of chloroquine derivatives in the treatment of COVID-19 patients, enabling us to make a grade I recommendation for its use against the disease.
Footnote: “The parallel world of numerical analysis disconnected from reality” sounds a lot like climate science. We are in a Brave New World where narratives are primary, while facts and data are servants to the agenda. See Climate Science Was Broken
via Science Matters
June 23, 2020 at 08:18AM