A few months ago I was surprised to receive a request from an obscure journal of consciousness studies to review a paper. I was surprised because, although it was not immediately obvious from the title, the paper contained the first reports of the primary outcome measure of the massive and notorious STAR-D study, 14 years after the study was finished.
What in the world were the main findings of the world’s largest ever antidepressant trial doing being presented now in a little known journal? The answer may lie in the fact that they show how miserably poor the results of standard medical treatment for depression really are!
With 4041 participants, the STAR-D study is by far the largest and most expensive study of antidepressants ever conducted. The intention of the study was to see how antidepressant treatment combined with high quality care performed in usual clinical conditions. It did not involve a placebo or any sort of control. All treatment was provided free for the duration of the study to maximise engagement.
The paper I was asked to review, which is now published in Psychology of Consciousness: Theory, Research and Practice, is written by a group led by Irving Kirsch and based on the original data obtained through the NIMH.1Shannon Peters describes its findings in detail.
Kirsch’s group point out that the paper that describes the design of the STAR-D trial clearly identifies the Hamilton Rating Scale for Depression (HRSD) as the primary outcome.2 This makes sense since the HRSD is one of the most commonly used rating scales in trials of treatment of depression, especially trials of antidepressants. As the STAR-D authors note in the study protocol “the HAM-D17 (HRSD), the primary outcome, allows comparison to the vast RCT literature” (cited in (1)).
Yet the outcome that was presented in almost all the study papers was the QIDS (Quick Inventory of Depressive Symptomatology), a measure made up especially for the STAR-D study, with no prior or subsequent credentials. In fact, as the authors of the present paper point out, this measure was devised not as an outcome measure, but as a way of tracking symptoms during the course of treatment, and the original study protocol explicitly stated that it should not be used as an outcome measure.
The analysis found that over the first 12 weeks of antidepressant treatment, people in the STAR-D study showed an improvement of 6.6 points on the HRSD. This level of change fails to reach the threshold required to indicate a ‘minimal improvement’ according to the Clinical Global Impressions scale (a global rating scale), which would be 7 points. It is also below average placebo improvement in placebo-controlled trials of antidepressants. A meta-analysis of paroxetine trials, for example, found that the average improvement in placebo-treated patients was 8.4 points on the HRSD.3 A meta-analysis of trials of fluoxetine and venlafaxine reported average levels of improvement on placebo of 9.3 points over just 6 weeks.4 Another meta-analysis found placebo improvement levels of between 6.7 and 8.9 points in placebo groups across trials involving a variety of antidepressants.5
The proportion of people classified as showing a ‘response’ (using the arbitrary but commonly used definition of a 50% decrease in HRSD score as per the original protocol) was 32.5% in the STAR-D study, and the proportion classified as showing remission (HRSD score ≤7) was 25.6%. The meta-analysis of placebo-controlled trials of fluoxetine and venlafaxine reported response rates of 39.9% among people allocated to placebo, and remission rates of 29.3%. In another antidepressant meta-analysis, the response rate on placebo was just above the STAR-D level at 34.7%,6 and in another it was just below at 30.0%.7
The authors of the current paper point out, however, that improvement is lower in placebo-controlled trials, even in the people treated with antidepressants, than it is in trials that compare one antidepressant against another without placebo controls. This is presumably because people in placebo controlled trials are told that there is a chance that they will receive a dummy tablet, while in comparative trials, they know they will receive some sort of active drug. Therefore they compare the results of the STAR-D study to the results of a large meta-analysis of comparative trials (cited in (6)). These find average HRSD improvement levels of 14.8 points; response rates of 65.2% and remission rates of 48.4%. Therefore the STAR-D results are approximately half the magnitude of those obtained in standard comparative drug trials.
The authors propose that the reasons for this poor performance of antidepressants in the STAR-D study is due to the selection of more complex patients. Industry studies in particular exclude people with ‘co-morbid’ conditions and symptoms or history of self-harm, and often recruit people via advertisements. It may also be due to the intensive attention and assessment procedures people undergo in industry-funded studies, and the added placebo effect of being in a trial of a ‘new’ treatment, which most trials involve.
Whatever the reason, STAR-D suggests that in real life situations (which the STAR-D mimicked better than other trials) people taking antidepressants do not do very well. In fact, given that for the vast majority of people depression is a naturally remitting condition, it is difficult to believe that people treated with antidepressants do any better than people who are offered no treatment at all.
It seems this may be the reason why the results of the main outcome of the STAR-D study have remained buried for so long. Instead, a measure was selected that showed results in a slightly better light. Incidentally, even then results were pretty poor, especially over the long-term, as Piggott et al have showed in a previous analysis.8
Whether this was deliberate on the part of the original STAR-D authors or not, it was certainly not made explicit. There should surely be uproar about the withholding of information about one of the world’s most widely prescribed class of drugs. We must be grateful to Kirsch and his co-authors for finally putting this data in the public domain.
“Half his board, he explained unhappily, had told him that unless he
pulled the article, they would all resign and ‘harass the journal’ he
had founded 25 years earlier ‘until it died.’ Faced with the loss of his
own scientific legacy, he had capitulated.” An article on a controversial topic disappears. without a trace. (Theodore Hill, Quillette)
“Corruption, the Lack of Academic Integrity and Other Ethical Issues in Higher Education: What Can Be Done Within the Bologna Process?”
Is that anything like salami slicing? (Elena Denisova-Schmidt, European
Higher Education Area: The Impact of Past and Future Policies)
“I think what everyone has to understand is that unhealthy
discussion leads to unsuccessful funding applications, with referees
pointing out that there is a controversy in the matter.” Katarina
Zimmer digs into the Smart Flares controversy. (The Scientist)
“An article in a BMJ journal that criticised a Cochrane review on
human papillomavirus vaccine made allegations that were not warranted
and gave an inaccurate and sensationalised report of the review’s
findings, say Cochrane’s two top editors.” It’sone group of Cochrane editors vs. another group of Cochrane editors. (Nigel Hawkes, The BMJ)
What does this mean, OMICS? An article “accepted for
publication…considering the statements provided in the article as
personal opinion of the author which was found not having any or biasness towards anything.” Is it even the right article? (Journal of Arthritis)
“Drug companies routinely tweak their clinical trial designs in ways that seem designed to obtain opportune results. Very often, the FDA doesn’t mind.” (Dan Robitzski, Ashley Lyles & Cici Zhang, Undark)
A look at citation sentiment — whether citations to retracted papers are positive or negative — that draws on our retraction database. (by David Ciudad, presented by Daniel Ecer)
junk science Wonder how many researchers can get away with publicly attacking the President and get a federal grant at the same time?
NEJM
editor Jeffrey Drazen has decided to risk his and his journal’s
reputations to defend air quality lies coming from the Harvard-based EPA
air quality mafia. Game on. Here’s the grant to Drazen. Note the dates.
(CNSNews.com) – Cement, the ubiquitous material used to build roads, buildings and other infrastructure, absorbs about one billion tons of atmospheric carbon dioxide (CO2) annually, according to a new study published Monday in the journal Nature Geoscience.
The study found that cement’s natural carbonation process not only offsets the fossil fuel emissions released during its production, it also “represents a large and growing net sink of CO2” that has not been taken into account by the IPCC.
“It is well known that the weathering of carbonate and silicate materials removes CO2 from the atmosphere on geologic timescales,” said the study, entitled Substantial Global Carbon Uptake by Cement Carbonation.
“However, the potential for removal by the weathering of cement materials has only been recently recognized. Our results indicate that such enhanced weathering is already occurring on a large scale; existing cement stocks worldwide sequester approximately one billion tons of atmospheric CO2 each year.”
The study, which was conducted in China by China Emission Accounts and Datasets (CEADs), explained that the physiochemical process of carbonation, which absorbs CO2 into the pores of cement materials such as concrete and mortar, is “a slow process that takes place throughout the entire life cycle of cement-based materials,” and even continues when a cement structure is demolished and the concrete is repurposed.
“Existing cement is a large and overlooked carbon sink and future emissions inventories and carbon budgets may be improved by including this,” said Prof. Guan.
The research team estimated that cement reabsorbed 4.5 gigatons of carbon (GtC) worldwide between 1930 and 2013, offsetting 43 per cent of the emissions from its production over the same period, not counting emissions associated with fossil fuel use.
About 44 per cent of cement process emissions produced each year between 1980 and 2013 were offset by the annual cement “sink”, the study found. And because demolition exposes new surfaces to atmospheric CO2, cement continues to absorb it even when a structure has been torn down.
We suggest that if carbon capture and storage technology were applied to cement process emissions, the produced cements might represent a source of negative CO2 emissions “We suggest that if carbon capture and storage technology were applied to cement process emissions, the produced cements might represent a source of negative CO2 emissions,” Guan stated.
“Policymakers might also investigate ways to increase the completeness and rate of carbonation of cement waste, for example as a part of an enhanced weathering scheme, to further reduce the climate impacts of cement emissions,” he added.
Since the study shows that cement sequesters about one billion tons of CO2 annually that the IPCC has not taken into consideration, wouldn't they have to adjust their numbers accordingly and decrease he amount of CO2 reductions necessary to prevent global warming? CNSNews asked Guan.
“Current emission inventory adopted by IPCC is territorial emissions approach, which does not account for all emissions sources/sinks,” Guan replied in an email.
“We (CEADs, China Emission Accounts and Datasets – a group of researchers from different countries globally,) have been attempting to further develop the emission accounting method, test robustness and improve emission estimation accuracy over past decades. Cement natural carbonation over life-time as carbon sink is a brand new research we present here,” he continued.
“IPCC and global climate change community have been advocated emission data accuracy and transparencies. The Paris Adoption (so-called Paris Agreement for Climate Change) formally wrote in the Article 4.1 as: ‘Parties shall account for their nationally determined contributions. In accounting for anthropogenic emissions and removals corresponding to their nationally determined contributions, Parties shall promote environmental integrity, transparency, accuracy, completeness, comparability and consistency, and ensure the avoidance of double counting, in accordance with guidance adopted by the Conference of the Parties serving as the meeting of the Parties to the Paris Agreement.’
“I hope our studies will provide quantitative evidence for improving IPCC emission inventory method and data,” Guan added.
Here's 3 more Doctors sticking their noses in where they don't belong to repackage and sell self aggrandizing, anti-scienced, Behavorism. Let that sink in. Doctors. Life and Death. Last Ditch. Medicare and Medicaid. Your Money. Charlatans. Hucksters. Par for the course.
"we have a paper that was accepted to a journal, passed peer review, but somehow managed to be in the wrong field, tried to take ownership of a non issue and manages to misconstrue success as failure."
We are all aware of the bad ideas the left likes to peddle. They range from gender is a social construct, babies aren’t alive until sometime after birth, paying people not to work will somehow motivate them to industriousness, businesses are evil and and exist to prevent people from employment, or my favorite you can waste money to make yourself wealthy. If you think about these concepts you can’t help but scratch your head and wonder how do they get started and how do they gain traction. I think I have had the horror of seeing one of these trying to get its start.
Variations in mortality from legal intervention in the United States—1999 to 2013 is the rather bland title of what would seem to be at first glance a report from the law enforcement community. It isn’t. It’s a paper by three physicians presented not as statistics but as findings about preventative medicine. Here we have start of the dominoes falling. You have authors who have gone completely outside of their realm of expertise and into another field entirely. If you accept the premise, you have accepted deaths due to law enforcement actions are a medical issue, and medical experts are the people qualified to solve the problem. In short the authors start by moving the goal posts to where they want them. Continue Reading here. Thank You Joliphant and Redstate.
Virtually No Patients Improving. Anyone Surprised? madinamerica;
October 25, 2014
“As disability awards for PTSD have grown nearly fivefold over the past 13 years, so have concerns that many veterans might be exaggerating or lying to win benefits,” reports the Washington Post. The Post quotes studies and experts suggesting that “roughly half” of veterans may not really have PTSD.
“Depending on severity, veterans with PTSD can receive up to $3,000 a month tax-free, making the disorder the biggest contributor to the growth of a disability system in which payments have more than doubled to $49 billion since 2002,” reports the Post.
In addition, the Post notes that virtually no veterans ever seem to be getting better. “Of the 572,612 veterans on the disability rolls for PTSD at the end of 2012, 1,868 — a third of 1 percent — had lower ratings the next year, according to statistics provided by the VA.”
They're not struggling anywhere near enough yet. madinamerica;
October 21, 2014
Since the 1960s, the positive response rates to antipsychotic medications have been dropping steadily, according to a meta-analysis published in JAMA Psychiatry by Columbia University and New York State Psychiatric Institute researchers. At the same time, the positive response rates to placebos have been increasing, and antipsychotic medications are therefore appearing less effective in comparison. This situation necessitates re-thinking how clinical trials are done, wrote the researchers, in order to overcome this appearance of ineffectiveness of antipsychotics.
In their study, the researchers wrote that slim drug-placebo differences in drug trials have been increasing the numbers of “failed antipsychotic trials,” which in turn have been increasing “the cost of drug development” and also causing some pharmaceutical companies to reduce their psychiatric research. “Thus, it is imperative to determine what is causing these increased placebo response rates in antipsychotic trials.”
The researchers examined randomized controlled trials (RCT) published between 1960 and July 2013 that compared antipsychotics to placebos or to other comparable medications in adults with schizophrenia or schizoaffective disorder, and that lasted between 4 and 24 weeks.
“(T)he placebo response was shown to be significantly increasing from 1960 to the present,” they wrote. They found that the average placebo-treated patient in an RCT of antipsychotic drugs during the 1960s worsened by 3.5 Brief Psychiatric Rating Scale (BPRS) points. Yet in the 2000s, the average placebo-treated patient improved by 3.2 BPRS points.
Over the same time span, antipsychotic effectiveness dropped significantly. “The average RCT participant receiving an effective dose of medication in the 1960s improved by 13.8 BPRS points, whereas this difference diminished to 9.7 BPRS points by the 2000s.”
“The consequence of these divergent trends,” the researchers noted, “was a significant decrease in drug-placebo differences from 1960 to the present.”
The researchers found that one factor accounting for this trend seemed to be that people with less severe symptoms — who also responded less well to treatment — were being enrolled in clinical trials in more recent years. They also found that when patients and physicians both knew that patients had higher odds of receiving a drug instead of a placebo in drug comparison trials, response rates improved across the board, possibly due to either heightened patient expectation or clinician “rater bias” or both. In addition, they found that the longer clinical trials lasted, the less effective antipsychotics appeared.
In their conclusion, the researchers suggested that efforts could be made to improve “signal detection,” or the appearance of drug effectiveness. Among such advisable changes, they suggested, “would be to recruit more severely ill patients” and “limit study duration to no longer than 8 to 12 weeks.”
The researchers also concluded that clinical trial designs should “dispense with single-blind placebo lead-in periods.” The study did not go into detail on alternative trial designs; however, a 2012 webinar by UNC at Chapel Hill biostatistician Anastasia Ivanova made the same argument. Discussing many of the same antipsychotic drug trials as were later identified in the JAMA Psychiatry study, Ivanova explained that, “The fact that an increasing number of medications are unable to beat sugar pills has thrown the industry into crisis. The placebo effect has become the elephant in the boardroom.” Ivanova then described in detail how the single-blind placebo lead-in design was an effort to remove people who responded to placebos from clinical trials that did not succeed, and should be replaced by a multi-stage trial design that was much more effective at strategically eliminating people who responded to placebos.
