Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy

http://032912b.membershipsoftware.org/libdocuments/Antidepressants_meta-analysis.pdf


This paper shows that negative results of trials are often withheld, when the results of drugs are 
completely random compared to placebo this can make the drug appear to be working.

Selective Publication of Antidepressant

Trials and Its Influence on Apparent Efficacy

Erick H. Turner, M.D., Annette M. Matthews, M.D., Eftihia Linardatos, B.S.,

Robert A. Tell, L.C.S.W., and Robert Rosenthal, Ph.D.

From the Departments of Psychiatry

(E.H.T., A.M.M.) and Pharmacology

(E.H.T.), Oregon Health and Science Uni

-

versity; and the Behavioral Health and

Neurosciences Division, Portland Veter

-

ans Affairs Medical Center (E.H.T., A.M.M.,

R.A.T.)

—

both in Portland, OR; the De

-

partment of Psychology, Kent State Uni

-

versity, Kent, OH (E.L.); the Department

of Psychology, University of California–

Riverside, Riverside (R.R.); and Harvard

University, Cambridge, MA (R.R.). Address

reprint requests to Dr. Turner at Portland

VA Medical Center, P3MHDC, 3710 SW

US Veterans Hospital Rd., Portland, OR

97239, or at turnere@ohsu.edu.

N Engl J Med 2008;358:252-60.

Copyright © 2008 Massachusetts Medical Society.

A B S T R A C T

BACKGROUND

Evidence-based medicine is valuable to the extent that the evidence base is complete

and unbiased. Selective publication of clinical trials — and the outcomes within

those trials — can lead to unrealistic estimates of drug effectiveness and alter the

apparent risk–benefit ratio.

METHODS

We obtained reviews from the Food and Drug Administration (FDA) for studies of

12 antidepressant agents involving 12,564 patients. We conducted a systematic lit

-

erature search to identify matching publications. For trials that were reported in the

literature, we compared the published outcomes with the FDA outcomes. We also

compared the effect size derived from the published reports with the effect size de

-

rived from the entire FDA data set.

RESULTS

Among 74 FDA-registered studies, 31%, accounting for 3449 study participants, were

not published. Whether and how the studies were published were associated with

the study outcome. A total of 37 studies viewed by the FDA as having positive results

were published; 1 study viewed as positive was not published. Studies viewed by the

FDA as having negative or questionable results were, with 3 exceptions, either not

published (22 studies) or published in a way that, in our opinion, conveyed a posi

-

tive outcome (11 studies). According to the published literature, it appeared that

94% of the trials conducted were positive. By contrast, the FDA analysis showed that

51% were positive. Separate meta-analyses of the FDA and journal data sets showed

that the increase in effect size ranged from 11 to 69% for individual drugs and was

32% overall.

CONCLUSIONS

We cannot determine whether the bias observed resulted from a failure to submit

manuscripts on the part of authors and sponsors, from decisions by journal editors

and reviewers not to publish, or both. Selective reporting of clinical trial results may

have adverse consequences for researchers, study participants, health care profes

-

sionals, and patients

Initial Severity and Antidepressant Benefits: A Meta-Analysis of Data Submitted to the Food and Drug Administration

http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0050045

  Another people implying that antidepressants work no better than placebos, it also shows that patients leaving the trials early has no effect on this conclusion.

 

Initial Severity and Antidepressant Benefits: A Meta-Analysis of Data Submitted to the Food and Drug Administration

• Irving Kirsch mail,
  
  
• Brett J Deacon,
• Tania B Huedo-Medina,
• Alan Scoboria,
• Thomas J Moore,
• Blair T Johnson

• Article
• About the Authors
• Metrics
• Comments
• Related Content

12

Hide Figures

• Abstract
• Editors' Summary
• Introduction
• Methods
• Results
• Discussion
• Supporting Information
• Author Contributions
• References

• Reader Comments (46)
• Figures

Abstract

Background

Meta-analyses 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

We 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 groups.

Conclusions

Drug–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 medication.

Antidepressants versus placebo

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 comparisons.

The cited 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 or causation.

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.

References

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. doi:10.1371/journal.pmed.0050045
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

http://www.bmj.com/content/331/7509/155?ijkey=26c8afe7ad38424073e7794ec14de137dc7b7616&keytype2=tf_ipsecsha

Efficacy of antidepressants in adults

BMJ 2005; 331 doi: http://dx.doi.org/10.1136/bmj.331.7509.155 (Published 14 July 2005)

Cite this as: BMJ 2005;331:155

• Drugs: musculoskeletal and joint diseases

Most people with depression are initially treated with antidepressants. But how well do the data support their use, and should we reconsider our strategy?

Introduction

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 behaviour^{w1 w2} means there needs to be further consideration of evidence for the efficacy of antidepressants in adults as there has been in children.

Efficacy

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.

Placebo Response in Randomized Controlled Trials of Antidepressants for Pediatric Major Depressive Disorder

http://ajp.psychiatryonline.org/data/Journals/AJP/3879/09aj0042.PDF

 

The increasing publicity of how antidepressants usually perform

no better than placebo is causing more concern, for example

larger and more widely distributed trials seem to be erasing

some of the few benefits over placebo they have.   

 

 

 

Article

42

Am J Psychiatry 166:1, January 2009

ajp.psychiatryonline.org

This article is featured in this month’s AJP

Audio

and is discussed in an editorial by Dr. Emslie (p. 1).

Placebo Response in Randomized Controlled Trials of

Antidepressants for Pediatric Major Depressive Disorder

Jeffrey A. Bridge, Ph.D.

Boris Birmaher, M.D.

Satish Iyengar, Ph.D.

Rémy P. Barbe, M.D.

David A. Brent, M.D.

Objective:

The authors examined char-

acteristics and predictors of response to placebo in all available reports of short-

term randomized controlled trials of anti-

depressants for pediatric major depres-

sive disorder.

Method:

Response, defined as a score

≤

2

on the improvement item of the Clinical

Global Impression scale, and potential

predictors were extracted from 12 pub-

lished and unpublished randomized con-

trolled trials of second-generation antide-

pressants in participants 6–18 years of

age with major depression.

Results:

The single best predictor of the

proportion of patients taking placebo

who responded to treatment was the

number of study sites. Baseline severity of

illness also emerged as a significant in-

verse predictor of placebo response, al-

though the strength of this relationship

was diminished when number of sites

was controlled for. After one large fluoxe-

tine trial was excluded, younger partici-

pants showed a higher placebo response

rate than older adolescents. Higher pla-

cebo response rates in more recent stud-

ies were explained by an increasing trend

toward large multisite trials and by publi-

cation delays and failures to publish some

negative trials.

Conclusions:

The recent shift toward

large multisite trials of antidepressant

medications for pediatric major depres-

sion may be contributing to an increasing

incidence of response to placebo. Phar-

macotherapy studies of pediatric depres-

sion that carefully recruit patients with at

least moderately severe depression may

be more informative and efficient than

many trials conducted to date. Such stud-

ies should have sufficient power to deter-

mine whether age moderates medication

and placebo response.

The Emperor's New Dru g s: An Anal y sis of Antidepressant Medication Data Submitted to the U.S. Food and Drug Administration

http://alphachoices.com/repository/assets/pdf/EmperorsNewDrugs.pdf

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.

http://jme.bmj.com/content/35/6/384.short

J Med Ethics 2009;35:384-389 doi:10.1136/jme.2008.028357

• Research ethics

A renewed, ethical defense of placebo-controlled trials of new treatments for major depression and anxiety disorders

1. B W Dunlop1,
2. J Banja2

+ Author Affiliations

1. ¹

   Emory University School of Medicine, Atlanta, Georgia, USA
2. ²

   Atlanta Clinical and Translational Science Institute, Emory University School of Medicine, Atlanta, Georgia, USA

1. 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; bdunlop@emory.edu

• Received 18 November 2008
• Revised 30 January 2009
• Accepted 3 March 2009

Abstract

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 beneficent-based, “best proven diagnostic and therapeutic method” that the original Helsinki Declaration of 1964 famously asserted participants are 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 people treated 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 clinical benefit, 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 unduly jeopardised 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 controls.

Antibiotics in the Animals We Eat | The Scientist

http://www.the-scientist.com/?articles.view/articleNo/31895/title/Antibiotics-in-the-Animals-We-Eat/


While US farmers and other stakeholders have argued tenaciously for the continuation of subtherapeutic dosing, Europeans adopted the “precautionary principle,” instituting sequential bans on the practice beginning in the mid-1990s. Arguments on both sides of this issue continue to the present day, but evidence of the negative consequences of low-dose antibiotic feeding has been mounting. Since 1976, several persuasive scientific studies have illustrated how animals fed low-dose antibiotics not only propagate resistant bacteria, but spread these resistant strains to farmers, their families, community residents, and ultimately, hospitalized patients. Particularly worrisome is the continued use in animals of antibiotics that are close structural relatives of those that are used in human medicine.  It is feared that, in time, these drugs will lose potency as bacteria express “cross-resistance” to the related drugs.

Iv-B business acts as an overtone to Oy-R battles against R disease. R acts in effect like terrorism in a population, trying to eradicate it as it hides between healthy cells like terrorists hide between civilians. Attacking these germs too much such as with an antiseptic environment for children can lead to mutations and resistance just like suppressing too much R dissent can lead to more R people and organized Ro resistance with mobs and demonstrations.

Some researchers have countered that the resistant bacterial strains found in serious hospital infections bear little or no resemblance to the strains found in farm animals. They argue that eliminating antibiotics on the farm would harm animal health, result in economic loss, and have little or no impact on reducing human morbidity and mortality. However, these rebuttals overlook the inherently promiscuous nature of bacteria—in particular, the transferable genetic elements they often carry (e.g., bacterial plasmids, transposons, phages) that can readily share DNA segments bearing resistance genes. They pass among strains, species, and even diverse bacterial genera, rearranging and accumulating even more resistance genes. Tracking the evolution of such complex bacterial exchanges from food animals to people poses a daunting challenge, making definitive proof elusive. But we argue that the preponderance of evidence, coupled with a diminishing pipeline of new antibiotics and the appearance of multidrug-resistant “superbugs,” warrants closer scrutiny of how and where we are using these antimicrobials—and the adoption of stricter measures of control.