Aperiomics is a system I thought of in 1989, I’ve been working on it mainly privately since then but am now starting to publish it. More detailed of it are found at Aperiomics.org, it is based on 12 mathematical principles of chaos and randomness that combine to explain events in war, economics, crime, sociology, evolution, etc.
People are welcome to read, they can correspond with me at email@example.com.
of antidepressant medications have reported only modest benefits over
placebo treatment, and when unpublished trial data are
included, the benefit falls below accepted criteria for
clinical significance. Yet, the efficacy of the antidepressants
may also depend on the severity of initial depression scores. The
purpose of this analysis is to establish the relation of
baseline severity and antidepressant efficacy using a
relevant dataset of published and unpublished clinical trials.
Methods and Findings
obtained data on all clinical trials submitted to the US Food and Drug
Administration (FDA) for the licensing of the four
new-generation antidepressants for which full datasets were
available. We then used meta-analytic techniques to assess
linear and quadratic effects of initial severity on improvement scores
for drug and placebo groups and on drug–placebo difference
scores. Drug–placebo differences increased as a function of
initial severity, rising from virtually no difference at
moderate levels of initial depression to a relatively small difference
for patients with very severe depression, reaching
conventional criteria for clinical significance only for
patients at the upper end of the very severely depressed category.
Meta-regression analyses indicated that the relation of baseline
severity and improvement was curvilinear in drug groups and
showed a strong, negative linear component in placebo
differences in antidepressant efficacy increase as a function of
baseline severity, but are relatively small even for severely
depressed patients. The relationship between initial
severity and antidepressant efficacy is attributable to
decreased responsiveness to placebo among very severely depressed
patients, rather than to increased responsiveness to
The authors selected published FDA trials on antidepressants
to meta analyze, they found no average efficacy for mild to moderate depression
compared to placebo.
The cited NCHS paper shows antidepressant use by 11% of the
population over 12, exacerbated by unethical papers like this. It unequivocally
promotes antidepressants for severe depression though the cited “Emperor’s New
Drugs…” investigates breaking of blind conditions as one cause.
The cited paper by Turner et al implies antidepressant trials
are encouraged by journals towards showing positive results, the project paper
tries to reduce this bias by its methodology but then gives a misleading result
by failing to include or mention any of these withheld trials in its results.
Turner et al also found 31% of FDA trials of antidepressants were not published
implying 94% were positive when only 51% were.
The cited paper by Montcrieff and Kirsch implies artificial
cut off points between remission and non-remission are unethically used to
amplify small effects. The project paper ethically uses continuous results on
the HRSD scale, it also implies some trials use disproportionately more
patients in the severe versus moderate category cutoff to avoid unfavorable placebo
paper by Dunlop and Baja implies pressure to unethically eliminate placebo
trials with antidepressants ostensibly to protect patients. The project paper
confronts this ethically by concluding on average attrition doesn’t affect its
results, implying patients are not harmed by substituting placebos.
The authors fail to point out that severely depressed patients
don’t give informed consent to trial antidepressants little better than
placebos, nor to have the results distorted to deceive many uninformed doctor’s
patients with placebo effects. When the public receives placebo medications the
trial participants become uninformed accomplices to fraud. The authors
ethically mention that declining responses from placebos don’t mean
antidepressants are working, disclosed in the cited paper “Initial Severity…”
by Kirsch et al.
The HRSD scale also measures subjective feelings rather than
just disease symptoms, this incentivizes trials testing for drugs people like
rather than treating disease. Montcrieff and Cohen show alcohol or sedatives improve
HRSD scores but cannot be ethically promoted as antidepressants. The project
paper critically fails to explain or reference how or even if antidepressants
work while endorsing them, providing correlation without explaining its nature
Drowsiness and gastrointestinal upsets mean patients often
detect the antidepressants, the project paper then biases towards higher HRSD
scores from these severely depressed patients’ expectations. The project paper
ignores bias from shorter trials artificially cutting off lower scores from later
disappointments or relapse. Sometimes patients previously responsive to
antidepressants are then selected for other trials, another ignored bias.
N Engl J Med. 2008 Jan 17;358(3):252-60. doi: 10.1056/NEJMsa065779.Selective
publication of antidepressant trials and its influence on apparent
efficacy.Turner EH, Matthews AM, Linardatos E, Tell RA, Rosenthal R.
Kirsch I, Deacon BJ, Huedo-Medina TB, Scoboria A, Moore TJ, et al. (2008)
Initial Severity and Antidepressant Benefits: A Meta-Analysis of Data Submitted
to the Food and Drug Administration. PLoS Med 5(2): e45.
Efficacy of antidepressants in adults BMJ 2005; 331 doi:
http://dx.doi.org/10.1136/bmj.331.7509.155 (Published 14 July 2005) NCHS Data Brief ■ No. 76 ■ October 2011 Antid
Most people with depression are initially treated with
antidepressants. But how well do the data support their use, and should
we reconsider our strategy?
The National Institute for Health and Clinical Excellence
(NICE) recently recommended that antidepressants, in particular
selective serotonin reuptake inhibitors, should be first line treatment
for moderate or severe depression.1 This conclusion has broadly been accepted as valid.2
The message is essentially the same as that of the Defeat Depression
Campaign in the early 1990s, which probably contributed to the 253% rise
in antidepressant prescribing in 10 years.1
From our involvement in commenting on the evidence base for the
guideline we believe these recommendations ignore NICE data. The
continuing concern that selective serotonin reuptake inhibitors may
increase the risk of suicidal behaviourw1 w2 means there
needs to be further consideration of evidence for the efficacy of
antidepressants in adults as there has been in children.
Although the NICE meta-analysis of placebo controlled trials
of selective serotonin reuptake inhibitors found significant
differences in levels of symptoms, these were so small that the effects
were deemed unlikely to be clinically important.1
The conclusion that the drugs had clinically important benefits was
based on analysis of response and remission rates. However, in our
comments on the draft guidelines, we pointed out that these categorical
outcomes were derived from the same continuous data for symptoms scores
that were found to show no clinically relevant effects. As NICE notes,
“dichotomising scores into remission and non-remission creates an
artificial boundary, with patients just over the cut-off score often
being clinically indistinguishable from those just under the cut-off.”
In V-Bi statistics there is a paradoxical relationship between significant and insignificant results, if they are over the 95% confidence level then they may be approved but a 94% level may not be. This represents a tipping point that can be chaotic between success and failure, similar boundaries can be manipulated to make it appear a result is more useful. For example a drug might not work but people expecting to be helped might be happier in the earlier stages of a trial. So counting evidence of happiness such as smiles and laughter might give an appearance that the drug is causing this rather than expectations. This problem is compounded with depression scales of measurements that are based on behavior like this, people expect to be helped and a remission can appear to occur from this expectance of this.
Although antidepressant medication is widely regarded as efficacious, a recent meta-analysis
of published clinical trials indicates that 75percent of the response to antidepressants is
duplicated by placebo (Kirsch & Sapirstein, 1998). These data have been challenged on a
number of grounds, including the restriction of the analyses to patients who had completed
the trials, the limited number of clinical trials assessed, the methodological characteristics of
those trials, and the use of meta-analytic statistical procedures (Klein, 1998).
The present article reports analyses of a data set to which these objections do not apply,
namely, the data submitted to the U.S. Food and Drug Administration(FDA) for approval of
recent antidepressant medications. We analyzed the efficacy data submitted to the FDA for
the six most widely prescribed antidepressants approved between 1987 and 1999 (RxList:
The Internet Drug Index, 1999): fluoxetine (Prozac), paroxetine(Paxil), sertraline (Zoloft),
venlafaxine (Effexor), nefazodone (Serzone), and citalopram (Celexa). These represent all
but one of the selective serotonin reuptakeinhibitors (SSRI) approved during the study
period. The FDA data set includes analyses of data from all patients who attended at least
one evaluation visit, even if they subsequently dropped out of the trial prematurely. Results
are reported from all well controlled efficacy trials of the use of these medications for the
treatment of depression. FDA medical and statistical reviewers had access to the raw data
and evaluated the trials independently. The findings of the primary medical and statistical
reviewers were verified by at least one other reviewer, and the analysis was also assessed by
an independent advisory panel. More important, the FDA data constitute the basis on which
these medications were approved. Approval of these medications implies that these
particular data are strong enough and reliable enough to warrant approval. To the extent that
these data are flawed, the medications should not have been approved.
Iv-B chaos in business creates mutated drugs as an Oy counter innovation to new apparent diseases or contagions as R and B in society. These drugs then mutate until some apparently have a beneficial effect on these diseases, however this Oy drug process is chaotic and and R-B diseases are also some times chaotic. Trying to work out their effectiveness using random based normal curves often leads to errors. For example people can be depressed because of stress or bad things in their lives, it can then be unnatural to remove this depression without improving their lives. If this is the cause of depression then the drug is acting to alter mind states like alcohol to drown a person's sorrows. A drug then that takes a person's mind off problems can deceptively appear to be a treatment. This business can then grow where each is deceiving their other, the B patients deceive the doctors that they are getting better to explore this mind altering feeling rather than attempting to fix the cause of the depression. The doctors and pharmaceutical companies deceive the patients and each other with hype that all end up believing until it crashes into reality when patients don't get better.
When only positive trials are published this allows chaos to grow through random trials by deceptively appearing as a significant treatment.
Emory University School of Medicine, Atlanta, Georgia, USA
Atlanta Clinical and Translational Science Institute, Emory University School of Medicine, Atlanta, Georgia, USA
Boadie W Dunlop, Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 1256 Briarcliff Road
NE, Building A, 3rd Floor, Atlanta, GA 30322, USA; firstname.lastname@example.org
Received 18 November 2008
Revised 30 January 2009
Accepted 3 March 2009
The use of placebo as a
control condition in clinical trials of major depressive disorder and
anxiety disorders continues
to be an area of ethical concern.
Typically, opponents of placebo controls argue that they violate the
proven diagnostic and therapeutic
method” that the original Helsinki Declaration of 1964 famously asserted
owed. A more consequentialist,
oppositional argument is that participants receiving placebo might
suffer enormously by being
deprived of their usual medication(s).
Nevertheless, recent findings of potential for suicidality in young
with antidepressants, along with
meta-analyses suggesting that antidepressants add no significant
clinical benefit over placebos,
warrant a re-evaluation of the
arguments against placebo.
In V-Bi science the normal curve is used to determine efficacy of drugs along with their side effects. issues like whether patients can be denied medication when enrolled in trials can also be decided with normal curve statistics. One problem is that issues below a significance level can persist from drugs that pass trials, also that the structure of a trial can get a drug just over the 5% significance level it needs. There is then a minimum uncertainty between randomness appearing to be a good drug or one without side effects or chaos where deterministic variables are actively causing problems. These are referred two as Type 1 and Type 2 errors in statistics.
It is possible however to have trials that are close to this significance level without any efficacy, for example withholding trials with poor results can bias the other trials so chance appears to be significant improvements in patients.
Furthermore, the nature of placebo treatment
in short-term clinical
trials is often not well understood,
and lack of understanding can foster opposition to it. This paper will
show how scientific
justifications for placebo use are
morally relevant. The fundamental ethical importance of placebo controls
is discussed in
relation to several aspects of clinical
trials, including detection of adverse events, accurate assessment of
advancing understanding of the
heterogeneity of depression and anxiety disorders and respecting
informed consent requirements.
Prohibiting the use of placebo controls
is morally concerning in that such prohibitions allow for the
possibility of serious
adverse public health consequences.
Moral worries that research participants receiving placebo are being
will be shown to be exaggerated,
especially in relation to the net benefits for end-users to be gained
from the quality of
data resulting from using placebo