The drugs were also linked to impaired adaptive functioning and social skills more generally.

The researchers draw attention to the fact that these harms, along with the risk of congenital abnormalities, are well-known in the neurology field but that psychiatry appears to ignore them. The drugs—commonly prescribed for depression and bipolar disorder—are often used at higher doses in psychiatry, bringing more risk.

“That ASM use is linked to adverse neurodevelopmental outcomes has been appreciated in the field of epilepsy for many years, yet has been largely overlooked by psychiatry despite the widespread usage of ASMs in the treatment of disorders such as depression and bipolar and at higher dosages than is typically used in epilepsy.,” the researchers write.

Other antiseizure drugs (phenobarbital, levetiracetam, carbamazepine) were also linked to neurodevelopmental problems, but methodological issues in the original studies hindered the ability to draw conclusions. Many popular antiseizure drugs, such as gabapentin and pregabalin, did not have enough data to analyze. The one exception to the finding in this analysis was lamotrigine, which did not appear linked to neurodevelopmental outcomes.

Most studies also found that polypharmacy—taking multiple antiseizure drugs—was associated with worse outcomes in all neurodevelopmental domains.

The research was led by Eliza Honybun and overseen by senior authors Piero Perucca and Genevieve Rayner at the University of Melbourne. It was published in Neurology, a top neurology journal.

The study adds to a large body of research on the impact of psychiatric drugs in pregnancy. In particular, many studies have linked in-utero antidepressant use to poor outcomes for babies, including neonatal withdrawal syndrome. However, little research has focused on antiseizure drugs, though they are commonly prescribed, particularly for bipolar disorder.

The current study was a systematic review of 43 studies that assessed neurodevelopmental outcomes in children after their mothers used antiseizure drugs during pregnancy. The outcomes included measures of social development, adaptive functioning, emotional functioning, and official psychiatric diagnoses.

Of the included studies, 10 were population-based, 19 were prospective cohort studies, nine were retrospective cohort studies, and five were cross-sectional observational studies.

The review found that the quality of evidence was generally low. Some studies lacked a comparison group (those not exposed to antiseizure drugs) or did not control for confounding factors like maternal age, smoking, other diagnoses, etc. Some studies lacked a blinded assessment, lost many subjects to follow-up, or were simply too small to analyze. The specific outcomes were highly variable, with studies including different measures and measuring different types of outcomes. There was a high variation in the duration of follow-up and when the outcomes were assessed.

The researchers broke down their results by drug:

Valproate and topiramate: Drugs with evidence for a large increased risk

Valproate: 40 of the 43 studies included valproate. Exposure to the drug in utero was linked to worse adaptive and social functioning, as well as up to four times the risk of ASD, five times the risk of ID, and 1.5 times the risk of ADHD. In some studies, there appeared to be a dose-dependent relationship, where higher doses increased the risk. However, this wasn’t a consistent finding. Six of the studies had a sample size too small to analyze, and 10 studies failed to account for confounding variables. However, this leaves dozens of well-conducted studies that found a harmful effect of valproate on neurodevelopmental outcomes, so this is considered the strongest evidence.

Topiramate: 11 studies included topiramate. One study found a doubling of the risk of ASD and 3.5 times the risk of ID; another found 2.38 times the risk for ADHD. A small study linked the drug to poor adaptive functioning. The studies that analyzed doses found a connection: higher doses appeared to be linked to worse functioning. Five of the studies had a sample size too small to analyze.

Drugs with mixed results

Phenytoin: 13 studies included phenytoin, with mixed results. Several found no effect, but at least one found a dose-dependent effect on adaptive functioning. Seven of the studies had a sample size too small to analyze, and seven failed to account for confounding variables.

Carbamazepine: 34 studies included carbamazepine. Several showed that the drug was linked to behavioral and emotional problems, and one study found the drug linked to 1.8 times the risk of tic disorders. Much of this comes from small, preliminary studies. Three of the studies had a sample size too small to analyze, and nine of the studies failed to account for confounding variables.

Levetiracetam: 13 studies included levetiracetam. One population study linked the drug to 1.8 times the risk of ADHD and 2.2 times the risk of anxiety diagnoses. The researchers write that the evidence was not consistent, though. Six of the studies had a sample size too small to analyze, and two of the studies failed to account for confounding variables.

Phenobarbital: Eight studies included phenobarbital. One study found a large increase of 7.6 times the risk for behavioral and emotional disorders, and another found an increased risk of learning disorders. However, these were small preliminary studies and are not considered solid evidence. Three of the studies had a sample size too small to analyze, and three of the studies failed to account for confounding variables.

Drugs with a lack of evidence to draw conclusions

Oxcarbazepine: 11 studies included oxcarbazepine. Although there were some inconsistent results, most of the studies found no connection between the drug and neurodevelopmental problems. Five of the studies had a sample size too small to analyze, and one study failed to account for confounding variables.

Clonazepam: 10 studies included clonazepam. Although there were some inconsistent results, most of the studies found no connection between the drug and neurodevelopmental problems. Four of the studies had a sample size too small to analyze.

Gabapentin: Seven studies included gabapentin. The included studies found no connection between the drug and neurodevelopmental problems. Three of the studies had a sample size too small to analyze.

Lamotrigine: No evidence for increased risk

Lamotrigine: 28 studies included lamotrigine. Although two studies found an increase in “autistic traits,” five large population studies found no connection. Four of the studies had a sample size too small to analyze, and six studies failed to account for confounding variables. The researchers conclude that there is no connection between lamotrigine and neurodevelopmental problems.

Ultimately, the researchers write that these findings should impact treatment decisions in pregnancy.

“The adverse neurobehavioral outcomes linked to prenatal [antiseizure drug] exposure in this study have significant implications for the treatment and counseling of women of childbearing age because they often have lifelong flow on impacts for both the child and carer’s lifestyle and quality of life.”

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Honybun, E., Cockle, E., Malpas, C. B., O’Brien, T. J., Vajda, F. J., Perucca, P., & Rayner, G. (2024). Neurodevelopmental and functional outcomes following in utero exposure to antiseizure medication: A systematic review. Neurology, 102, e209175. doi:10.1212/WNL.0000000000209175 (Link)

The post Antiseizure Drug Exposure in Pregnancy Linked to Large Risk of Autism, ADHD, and Intellectual Disability appeared first on Mad In America.

“Many patients with psychosis want to discontinue their antipsychotic drugs due to serious side effects hampering their daily functioning in the long term. The main drawback of discontinuation is relapse. Modern tapering strategies seem to reduce relapse risk to an acceptable level,” Wunderink writes.

He adds that although these findings still need replication, several studies are already being conducted that could provide confirmation and further details about the best tapering processes.

According to Wunderink, antipsychotic drugs can be effective in the immediate treatment of psychosis—reducing the hallucinations and delusions that are hallmarks of the syndrome. However, he notes that the drugs come with harmful effects (e.g., sexual dysfunction, tardive dyskinesia, metabolic syndrome) and even worsen the so-called “negative symptoms” of apathy, anhedonia, and cognitive impairment. Due to the strong negative effects on quality of life, many patients want to reduce the dose or eliminate the drug altogether.

According to Wunderink, studies have shown that it is actually possible to do so without any increase in relapse risk. A 2023 study demonstrated that using a personalized, slow taper, 74.5% of patients were able to reduce their dose and end up with better outcomes than those who kept taking the drugs. Only 11.8% experienced relapse—a rate comparable to those who continued taking the full dose of antipsychotic drugs.

He writes, “After remission of the positive symptoms, antidopaminergic drugs may do more harm than good, unless they are necessary to prevent dopaminergic derangement in vulnerable patients: We must find the lowest antipsychotic dose that prevents positive symptoms to reemerge in every individual case.”

Wunderink also cites the results of his seven-year follow-up of people reducing their antipsychotic prescription. While the initial two-year trial showed a higher risk of relapse for those who began tapering antipsychotics, after seven years, those in the dose-reduction group were more than twice as likely to recover than those who were maintained on the drugs (40.4% versus 17.6%).

Similarly, a recent meta-analysis found that people with schizophrenia who stopped taking antipsychotic drugs had better long-term outcomes in terms of social functioning, employment, and quality of life. Bolstering Wunderink’s point, that analysis found that studies involving individualized tapering strategies showed the best results.

Wunderink notes that one of the major issues with antipsychotics is dopamine hypersensitization: since the drugs block D2 dopamine receptors, the brain compensates by upregulation. When the drugs are removed, the brain is hypersensitive to dopamine, making the patient more likely to relapse. For this reason, Wunderink writes, a slow taper is needed in order to allow the brain time to adjust to the different levels of dopamine.

“This might explain why multiple-episode and chronic patients generally need higher doses of antipsychotics than first-episode patients, why the incidence of tardive dyskinesia is linearly dependent on the duration of dopamine blockade, and why so-called rebound psychoses occur after abrupt discontinuation of dopamine blocking drugs,” he writes.

As far back as 1967, researchers had identified that outcomes for patients taking antipsychotics were no better than they had been before the introduction of these drugs; outcomes were even, in some ways, worse. In 1976, researchers raised the question: “Is the cure worse than the disease?” This result continued to be found, with researchers in 1977 and over the next few years suggesting that the drugs themselves might be responsible for altering the brain in harmful ways, worsening outcomes for those who used them.

Indeed, an NIMH-funded trial by Martin Harrow and Thomas Jobe found that after 15 years, those who stopped taking antipsychotic drugs were eight times more likely to recover.

They compared outcomes for people with other disorders—not just schizophrenia—as a way of accounting for confounding by indication. Those with schizophrenia (the most serious diagnosis) who stopped taking antipsychotics had better outcomes than those with less serious diagnoses who did take antipsychotics. Those with schizophrenia who continued with drug treatment fared the worst.

This continues to be the main finding of longer-term outcomes to the present day. In a 2023 study of five-year outcomes after first-episode psychosis, researchers found that those who did not receive antipsychotics within the first month were twice as likely to be in recovery. A previous study by the same authors looked at cumulative exposure to antipsychotics for all patients with first-episode psychosis over a 19-year period; that study also found that those who took the most drugs for the longest period had worse outcomes, including higher mortality rates. In both of these studies, the researchers carefully accounted for confounding by indication and other possible factors.

In a 2013 systematic review, researchers found that recovery rates for those with psychosis have declined over time, with a particularly steep decline in the modern era of antipsychotic drug treatment. From a high of 18% in 1941-1955, the recovery rate has fallen to 6% since the late 1990s.

Ultimately, according to Wunderink, due to the powerful negative effects of the drugs, patients will continue to want to reduce or discontinue antipsychotics. Thus, doctors must help patients reduce their dose, lest the patients discontinue abruptly and relapse due to dopamine hypersensitization. The best evidence that exists indicates that a personalized, slow tapering process—with the ability to stop once the patient begins having difficulties—is the best option.

This also has the advantage, according to Wunderink, of enhancing the relationship and trust between the patient and provider, thus enabling better treatment.

Wunderink writes, “We still do not understand the most important mechanisms causing psychosis and relapse, nor are we able to predict who is dependent on antipsychotic drugs after remission of psychosis and who is not. To accept this is important but may be even more important is to work together with your patients and try to find the best individualized treatment for every single person having to deal with psychosis.”

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Wunderink, L. (2024). Changing vistas of psychosis and antipsychotic drug dosing toward personalized management of antipsychotics in clinical practice. Psychiatric Rehabilitation Journal. Published online April 22, 2024. https://dx.doi.org/10.1037/prj0000614 (Link)

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“Although benzodiazepines and related drugs (BZDRs) are effective for short-term treatment of insomnia, their use is associated with risk of several adverse outcomes, e.g., increased risk for tolerance, withdrawal symptoms and rebound effects as well as the development of dependence syndrome. For these reasons, most clinical guidelines recommend BZDRs only for short-term use,” the researchers write.

The research was led by Heidi Taipale at Karolinska Institutet and the University of Eastern Finland and published in European Psychiatry.

The post Long-Term Benzo Use Linked to Increased Disability appeared first on Mad In America.

“Large trials are rare in the field of antidepressant research. In the few existing trials, key outcomes such as suicidality and the functional impact of mental disorders were little studied. A significant proportion of these trials could be marketing trials (‘seeding trials’),” the researchers write.

The study, led by Samuel Martineau at the University of Rennes, France, was published in BMJ Open. The researchers also included Florian Naudet and Ioana-Alina Cristea, who have co-authored previous studies on how pharma undermines drug regulators in multiple ways as well as how medical journals make biased publication decisions.

The post Antidepressant Trials “Hijacked for Marketing Purposes,” Researchers Say appeared first on Mad In America.

The study contradicts widely held beliefs that people with schizophrenia need to take antipsychotics for life and that it is dangerous for people to go “off their meds.”

Shorter-term follow-up (less than two years) also demonstrated no difference in outcomes between those who continued to take antipsychotics and those who stopped, which should call into question the need for continuing to take such drugs.

“Our results showed that whilst short-term follow-ups (<2 years) on social functioning did not yield significant differences between maintenance and discontinuation, middle- and long-term follow-ups significantly favored discontinuation,” the researchers write.

According to the researchers, a high risk of bias in the included trials reduces the quality of their results, and they advise that more high-quality research be conducted to ensure that this finding is accurate. Still, this study reflects the best evidence available on how to proceed in the long term.

The research was conducted by Björn Schlier, Laura Buck, Matthias Pillny, and others at Universität Hamburg, Germany. It was published in the Lancet journal eClinical Medicine.

The post Long-term Outcomes Better for Those Who Stop Taking Antipsychotics appeared first on Mad In America.

This contradicts the accepted wisdom that untreated maternal depression is harmful to children. Instead, it suggests that treating maternal depression is detrimental to kids, while maternal depression itself is actually associated with benefits to child development.

The researchers found that one in five children was exposed to antidepressants in utero (20.8%), indicating that a large proportion of children are being exposed to the drug’s harmful effects on development.

Narimene Ait Belkacem and Anick Bérard led the study at the University of Montreal, Canada. It was conducted during the pandemic and published in the Journal of Clinical Medicine.

 “This study aimed to assess the exposure to prenatal maternal mental health (depression, anxiety, and overall pandemic-related stress) in utero, during the COVID-19 pandemic on children’s development at 18 months,” the researchers write.

The post Antidepressant Use in Pregnancy Harms Child Development, Untreated Maternal Depression Shows Benefit appeared first on Mad In America.

“The results of our analysis consistently demonstrated positive trends for both antidepressant prescription prevalence and suicide rates over time as well as positive associations between them. These findings update those from previous studies and are at odds with the notion that, at a population level, more antidepressant prescriptions would lead to lower suicide rates,” the researchers write.

The study was conducted by Simone Amendola, Martin Plöderl, and Michael P. Hengartner, and published in Crisis: The Journal of Crisis Intervention and Suicide Prevention.

The post Antidepressant Use Tightly Correlates with Increased Suicide Rates appeared first on Mad In America.

In the article, Torrey reviews the history of the Human Genome Project, their hopes for identifying the genetic basis for schizophrenia, and how those hopes have been dashed by the complete failure to find anything of the sort.

Torrey writes, “Over twenty years later not a single gene has been identified to cause schizophrenia, despite the expenditure of almost $8 billion in genetic research by NIMH. Nor have any new treatments become available from this research.”

This paper is surprising since Torrey has long argued that schizophrenia is a brain disease to be treated biomedically.

Who Is E. Fuller Torrey?

Torrey is a psychiatrist and a researcher on schizophrenia and bipolar disorder. In research circles, he’s known as the founder and executive director of the controversial Stanley Medical Research Institute, which has spent more than $550 million on biological research on schizophrenia and bipolar disorder over the past few decades.

Torrey is one of the primary researchers studying the possibility of immunological causes of schizophrenia. In particular, his research focuses on the parasite toxoplasma gondii, commonly carried by cats and which easily passes to humans. Some studies have found that exposure to that parasite, and exposure to cats in childhood more generally, is associated with a heightened risk of schizophrenia. However, other studies have not found a statistically significant correlation, so it is still considered theoretical. Even if a connection exists, it likely explains only a fraction of schizophrenia cases.

To most, though, Torrey is more well-known as the founder of the Treatment Advocacy Center (TAC), which lobbies politicians to support forced treatment for people with schizophrenia. For this reason, Torrey is a controversial figure: Psychiatric survivor group Mind Freedom International labeled him “one of the most feverishly pro-force psychiatrists in the world.”

Torrey and the TAC have been at the forefront of politicians’ plans for forced treatment, including shepherding Kendra’s law in New York as well as working with Mayor Adams on a plan to sweep up the unhoused population into psychiatric institutions.

However, studies since the 1990s, including a Cochrane review in 2017, have found forced treatment to be ineffective, concluding that it doesn’t reduce rehospitalization or criminality, or improve social functioning, quality of life, or even treatment adherence. Worse, research has found that involuntary treatment increases the risk of suicide. In addition, laws around involuntary treatment have been criticized for racial bias.

The United Nations has called for member states to ban forced treatment, saying that it “may well amount to torture” and that it violates human rights. And the World Health Organization has called for a transformation of mental health services to focus on person-centered and rights-based approaches.

The Human Genome Project

Despite advocating for the idea that psychosis has biological causes, and despite his presence on research teams involved in heritability studies, Torrey has long taken a somewhat skeptical view of genetics research. Yet laypeople, and many mental health professionals, still believe that schizophrenia is a genetic disorder. Indeed, the NIH’s MedlinePlus website lists schizophrenia as a “genetic condition,” even while admitting that its causes are “not well understood” and calling it “an active area of research.”

In the 1990s, the Human Genome Project—a massive effort to understand every human gene—promised to solve this riddle by uncovering the genetic basis of the disorder.

A few rare diseases are directly caused by a single gene variant (like Huntington’s disease, cystic fibrosis, and sickle cell anemia, for example). More commonly, though, people with certain identifiable genetic variants are at much higher risk for certain diseases. For instance, about 60% of women with the BRCA1 or BRCA2 variant develop breast cancer, compared to 13% of women without those variants. Variants that increase risk in this way are known as “risk genes.”

These strong correlations with specific heritable genetic variants are helpful for delineating the biological pathway of these diseases. For instance, the BRCA gene is considered a tumor-suppressing gene, so it makes sense that differences in that gene can strongly affect cancer risk.

If specific genetic variants could be identified that increase the risk of schizophrenia in a similar way, researchers could learn more about the possible biological pathways of schizophrenia and potentially develop drugs that target that biology. It might also make it possible to develop preventive measures specifically for those at high risk.

This was the dream of the Human Genome Project and its founders. As Torrey tells it, for many of the major figures involved in the creation and direction of the Human Genome Project, identifying the genetic basis of schizophrenia was to be one of the main drivers of their work. Torrey specifically notes that Charles Delisi, James Watson, and Senator Pete Domenici all had relationships that led to a personal obsession with schizophrenia.

It was Delisi who, in 1985, first floated the idea of the Human Genome Project with his colleagues and spent the next few years shepherding the project forward. His wife, Lynn, was one of the researchers focusing on how schizophrenia seemed to run in families.

Watson, already famous as a co-discoverer of the structure of DNA, was the first director of the Human Genome Project. For Watson, the focus on schizophrenia came when his son experienced a crisis at age 15, including a suicide attempt and a runaway scare, along with being diagnosed with schizophrenia and hospitalized for six months.

And according to Torrey, Domenici was known for putting the kibosh on expensive projects in his position on the budget and appropriations committees. But his daughter had been diagnosed with schizophrenia, and he was eager to move forward any research that might help with that specific diagnosis. It was with his help that the project was ultimately funded.

Thus, from the beginning, the Human Genome Project was designed by true believers with the promise of discovering the genetic basis of psychiatric disorders, especially schizophrenia. They spent the 1990s working to sequence the more than 20,000 human genes at an ultimate cost of $2.7 billion. In 2000, with about 90% of the genome mapped, their efforts were heralded as a success in a famous White House press conference (the full sequence was finally finished in 2022).

The Promise—and Failure—of Genetics

After that press conference in 2000, prominent scientists and politicians promised that our understanding of the genetics of mental illness was about to explode, leading to amazing new treatments that would totally change the landscape of psychiatry.

Torrey quotes Francis Collins, director of the Human Genome Project, who stated that by 2020, “gene-based designer drugs” would be available to treat and prevent everything from diabetes to Alzheimer’s disease, “and the diagnosis and treatment of mental illness will be transformed.”

Torrey also quotes Steven Hyman, who was director of the NIMH during the Human Genome Project era: “The search for the genes associated with most mental illnesses will now move forward at a greatly accelerated pace….Highly selective, safe, and effective new therapies will become available for the treatment of the common mental illnesses in the not-too distant future.”

But the promised gains never materialized. The Human Genome Project did help in our understanding of other conditions, especially cancer, as well as the single-gene disorders. But for psychiatric disorders, no genetic test was found; no biological test was found; no psychiatric drug was developed based on a genetic discovery. Not for depression, anxiety, psychosis, bipolar disorder, OCD, ADHD, or any other “mental illness.”

Current research has found that genetic testing could explain less than 1% of whether someone would receive a diagnosis of schizophrenia. Including the entire genome, another study found an explanatory power of 2.28%. Still another found that genetic causes might explain up to 3.4% of whether someone received the diagnosis.

By comparison, a study that included all known genetic factors as well as “environmental factors”—life experiences, social circumstances, family history, pain—found that genetics predicted 0.5% of the risk for schizophrenia, while environmental factors explained about 17%.

That finding was consistent with previous research finding strong correlations between schizophrenia and various life experiences, but no effect of genetics on risk for schizophrenia.

And other researchers have concluded that genetic results provided no useful data, even when considering genes theoretically associated with psychiatric disorders.

This failure of genetic research has paralleled the failure of the rest of psychiatry. Despite a massive increase in the amount of people receiving a diagnosis and taking psychiatric drugs, outcomes have only worsened over the years.

Researchers write that psychiatric drugs do not improve the course of mental illness or prevent hospitalization or suicide; they write that there is no evidence that psychiatry has improved outcomes over time; and they have found that antidepressant use, antipsychotic use, and even just receiving a psychiatric diagnosis all lead to worse outcomes than for those who don’t get diagnosed or treated—even after controlling for symptom severity.

Breakthroughs Proven Wrong, Again and Again

Torrey begins his discussion by noting that the failure to find any relevant genes for schizophrenia is ironic considering the hyperbolic promises of researchers throughout the years, including constant announcements in the media that researchers have discovered the genetic key to understanding it.

“Schizophrenia alone has probably been the subject of more genetic breakthrough announcements over the last thirty years than any other human disease,” Torrey writes.

But, he adds, the problem is that none of those supposed “breakthroughs” was subsequently replicated. The pattern, according to Torrey, is that one study would find a “breakthrough” genetic correlation, but the next study would prove it wrong. But that study would find a completely different correlation and get heralded as another “breakthrough”—until the next one proved it wrong and found a new “breakthrough,” over and over for decades.

Facetiously, Torrey notes, “This cycle of hypomanic enthusiasm followed by depression after a failure to replicate is similar to the clinical course of bipolar disorder itself.”

Why Does Schizophrenia Run in Families?

One key question for researchers was how to explain the finding that schizophrenia appears to run in families. Early studies of twins and siblings raised separately seemed to support the notion that schizophrenia was heritable. This led many researchers to the genetic hypothesis. But, according to Torrey, more modern research has shown that these studies are methodologically flawed. The fact is, schizophrenia may run in families because child abuse, trauma, and other environmental factors also run in families.

Studies have attempted to disentangle this fact by claiming to include siblings—sometimes twins—“reared apart,” but these studies actually include mostly siblings and twins who were raised together for at least some time, raised by a close family member, or who reconnected before volunteering for the study—meaning that they don’t actually account for family environment at all.

Moreover, according to Torrey, there are biological factors besides genetics that also affect these results—such as the presence of environmental contaminants in the neighborhood (some siblings, even if supposedly raised apart, were raised in homes in the same neighborhood or spent plenty of time in their home of origin). Another factor: fetal environment. Infections—such as Torrey’s favorite parasite, toxoplasma gondii—may be passed down during pregnancy. Thus, even if the siblings were raised separately, they may have shared the same immunological factors before birth.

To bring this point home, Torrey notes that a large twin study in 2018 found that only 15% of the participants shared a diagnosis of schizophrenia with their identical (monozygotic) twin (12 out of 81 pairs in which at least one had the diagnosis), despite sharing 100% of the same genetic material. For fraternal (dizygotic) twins, it was 3%, despite sharing 50% of the same genetic material.

Torrey writes that this concordance rate is similar to that for infectious diseases—with polio having a 36% concordance rate and tuberculosis a 31% concordance rate in twins.

The hope of the Human Genome Project researchers, though, was that genetics studies could get around these methodological problems and directly identify the genes responsible.

The Failure of a Wide Variety of Genetic Studies

In the search for possible genetic roots of a disorder that runs in families, perhaps the most helpful type of study is a linkage analysis. Torrey writes that there have been “at least” 32 linkage analysis studies of schizophrenia and 40 of bipolar disorder. None of them were able to replicate the findings of the others.

Torrey writes, “The coup de grace for schizophrenia linkage analysis studies was administered in 2002 by [Lynn] DeLisi, who had carried out a linkage analysis on 309 families in which at least two siblings had been diagnosed with schizophrenia or a related disorder, including the Galvin family in which 7 of the 12 children had been diagnosed with schizophrenia. DeLisi was unable to replicate the findings of previous linkage studies and her own findings for linkage were weak. She concluded that linkage analysis was not an effective technique for identifying the genetic roots of schizophrenia.”

Another approach was to try to predict candidate genes: guessing which genes might be responsible for a given diagnosis, and then checking to see if they were more common in those with the disorder than without. Since schizophrenia was thought to involve the dopamine system, candidate gene studies often looked at genes that were responsible for regulating or developing that system in the brain.

Over a thousand candidate gene studies were conducted on schizophrenia, according to Torrey, with hundreds more for bipolar disorder. But this approach failed just as completely as the linkage analysis approach.

As Martilias Farrell and colleagues wrote in a 2015 paper: “The current empirical evidence strongly supports the idea that the historical candidate gene literature yielded no robust and replicable insights into the etiology of schizophrenia.”

And in 2017, Emma C. Johnson and colleagues wrote, “Taken as a group, schizophrenia candidate genes are no more associated with schizophrenia than random sets of control genes.”

(Torrey also notes that candidate gene studies of depression completely failed in the same way.)

Genome-wide association studies (GWAS) were viewed as the next breakthrough. This type of study casts a wide net at more than a million mutations called single-nucleotide polymorphisms (SNPs). These SNPs are like markers that flag nearby genes as potentially increasing risk for a disease.

Torrey writes, “It was hoped that [GWAS] would lead to the discovery of a few genes of large effect which are involved in the cause of schizophrenia. Unfortunately that is not what researchers found. Rather than finding a few genes of large effect which could be linked causally to schizophrenia, they found hundreds of genes of very small effect which have not been linked causally to this disorder.”

Even if the hundreds of genes identified are truly related to schizophrenia, even in aggregate they explain such a microscopic amount of the risk that there is no clinical utility in listing them.

Worse, the problem of causality is paramount here. As one example of how these studies can confound correlation and causation, Torrey writes that people with schizophrenia are far more likely to be tobacco smokers, so some genes found in a GWAS to be associated with schizophrenia might actually just be genes linked to smoking.

Differences in ancestry can also produce spurious results. For instance, due to racial biases in diagnostic categories, far more Black people are diagnosed with schizophrenia. Thus, GWAS studies might inadvertently identify genes related to African ancestry as increasing the risk for schizophrenia.

Finally, Torrey adds that the genes identified by GWAS as increasing risk for schizophrenia overlap among all psychiatric diagnoses, including depression, ADHD, and autism. Thus, these genes are not specific, but rather seem associated with emotional distress in general and altered cognition of many kinds.

The closest thing a GWAS has found to a consistent genetic link to schizophrenia is the Major Histocompatibility Complex (MHC), a correlation that was replicated in several studies. This area of chromosome 6 has been studied since the 1970s as a potential factor in schizophrenia. But this is certainly not a specific finding: the MHC has been linked to nearly every autoimmune disorder and a wide variety of infectious diseases. To some extent, this supports Torrey’s belief that schizophrenia can be caused by toxoplasma gondii. But, like the other GWAS findings, this correlation explains very little of the risk and is too broad to be of any clinical utility.

Torrey notes that Lynn Delisi and colleagues studied the entire genome of nine families that had multiple members with the schizophrenia diagnosis.

He writes, “Surely, it was thought, such heavily burdened families would lead to the identification of causal genes of large effect. Alas, each of the 9 families had different genetic findings, none of which were widely shared among the other families or among other individuals with schizophrenia. Nor could any of the genetic findings be definitively linked to the cause of the disease and none of the variants identified overlapped with the SNP loci identified in the GWAS study of schizophrenia.”

To sum up the failure of GWAS, Torrey quotes researchers McClellan and King, who published a thorough overview of the topic in 2010:

“The general failure to confirm common risk variants is not due to a failure to carry out GWAS properly. The problem is underlying biology, not the operationalization of study design. The common disease–common variant model has been the primary focus of human genomics over the last decade. Numerous international collaborative efforts representing hundreds of important human diseases and traits have been carried out with large well-characterized cohorts of cases and controls. If common alleles influenced common diseases, many would have been found by now. The issue is not how to develop still larger studies, or how to parse the data still further, but rather whether the common disease–common variant hypothesis has now been tested and found not to apply to most complex human diseases.”

After the failure of GWAS, researchers turned to the next type of genetic study: identifying copy number variants (CNVs). Some part of the human genome consists of repeated genetic patterns; copy number variation is a term for the difference in the number of times certain parts of the pattern repeat. Essentially, CNVs are either extra copies (duplication) or missing copies (deletion) of genetic code. CNVs are common and usually they don’t cause any problems. However, certain CNVs have been identified as causing genetic disorders. For instance, Huntington’s disease is directly caused by a large number of repeats of the CAG trinucleotide of the HTT gene, and the more times the code repeats, the earlier the onset of Huntington’s.

The CNV that causes DiGeorge syndrome is associated with an increased risk for schizophrenia, and it is estimated that about 1% of people with schizophrenia have that CNV, compared with about 0.025% of the general population. But again, this does little to explain a cause for the other 99% of people with schizophrenia—or why most people with DiGeorge syndrome don’t develop schizophrenia.

A newer type of genetics study focuses solely on “rare coding variants” that are detectable using exome sequencing. The problem, according to Torrey, is that the variants detected using exome sequencing are indeed extremely rare. Thus, even if there is a slight correlation in which people with these variants are more likely to develop schizophrenia, it has very little clinical utility. The vast majority of those with the diagnosis do not have these variants. Of course, this also means that these variants are not a very good indicator for understanding the theoretical underlying biology.

According to Torrey, “it is unclear what role, if any, the rare variants play in causing schizophrenia.”

Indeed, researchers who completed an exome study for schizophrenia wrote that “The main conclusion of this investigation is a negative one. The diagnostic yield for exome sequencing of known neuropsychiatric genes in this sample is about 1%.”

Searching for the Psychiatric Yeti

To sum it all up, Torrey quotes a number of eminent researchers on the failure to identify a genetic basis for schizophrenia:

• Gershon, 2011: “Where is the missing heritability? […] Among scientists in the field, there is a sense of disappointment in the air.”
• Crow, 2011: “There comes a point at which the genetic skeptic can be pardoned for the suggestion that if the genes are so small and so multiple, what they are hardly matters, the dividing line between polygenes and no genes is of little practical consequence. Have we reached this point?”
• Uher and Rutter, 2012: “It can be summarized that molecular genetic studies of psychiatric disorders have done a lot to find very little. In fact, in the era of genome-wide association studies, psychiatric disorders have distinguished themselves from most types of physical illness by the absence of strong genetic associations.”
• Latham, 2011: “The most likely explanation for why genes for common diseases have not been found is that, with few exceptions, they do not exist.”

Perhaps the most telling quote comes from Steven Hyman, director of the NIMH during the Human Genome Project era:

“I made one enormous error. I thought that family and genetic studies, advances in neuroscience, and the newly emerging discipline of molecular biology would soon elucidate pathogenesis and result in improved therapeutics. How wrong I turned out to be.”

Ultimately, Torrey writes that the search for schizophrenia genes can be compared to a wild goose chase—although, he adds, “it is even worse than that since a wild goose chase has, at least theoretically, a wild goose that might be caught. If indeed genes causing schizophrenia do not exist, then the thirty year search has been more like a search for a psychiatric yeti.”

Evolution

Torrey’s final argument against schizophrenia as a heritable disease is an evolutionary one. According to a study in 2010, people with psychiatric diagnoses are far less likely to have children than people without a diagnosis. Those with schizophrenia are at the lowest extreme. For every 100 men without a diagnosis who have a child, only 10 men with schizophrenia have a child; for every 100 women without a diagnosis who have a child, only 18 women with schizophrenia have a child.

Moreover, Torrey notes, hundreds of thousands of people with schizophrenia were forced to undergo sterilization as part of the eugenics movement in the first half of the 1900s, including 18,000 people in the United States. In Nazi Germany, in addition to sterilizing about 132,000 people with schizophrenia, about an equal number were murdered.

Yet, during that same time (1850-1950), the number of new incidences of schizophrenia only increased, including by sevenfold in the United States.

Torrey writes, “Schizophrenia as we know it clinically has been well described for over 200 years during which time the reproduction rate of those affected has been exceedingly low. If schizophrenia was truly a genetic disease it should have died out by now. Thus, the fact that it still exists is strong evidence that it is not a genetic disease.”

Conclusion

Despite the investment of billions of dollars into research on the supposed genetics of schizophrenia over the course of decades, nothing useful has been found. Continuing down this road, Torrey argues, is a waste of time and money.

He writes, “NIMH invested extensive resources in this research with little to show for it and at the expense of alternative research projects. Since schizophrenia does not appear to be a genetic disorder, NIMH’s research portfolio should be reviewed.”

Torrey suggests that the NIMH should focus on basic research into the biological causes of schizophrenia, including his pet theory, that schizophrenia is caused by immunological problems (lead candidate: toxoplasma gondii). He also suggests that the NIMH should fund more clinical trials in an effort to develop new drugs to treat the disorder.

However, the NIMH’s tight focus on funding genetic research has also prevented the exploration of the known psychological causes of schizophrenia, such as the impact of trauma, isolation, and poverty. It has also prevented the proliferation of non-biological understandings of psychosis, such as the Hearing Voices movement, and non-medical treatments, like Open Dialogue and Soteria.

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The post Searching for the “Psychiatric Yeti”: Schizophrenia Is Not Genetic appeared first on Mad In America.

In fact, those who received a placebo but thought they received Prozac improved more than those who received the drug and knew it.

That is, the researchers write that the drug is not actually effective in depression treatment (“the absence of actual effects”) but is perceived to be effective by the researchers because the results were contaminated by the placebo effect.

This finding is similar to another recent finding, which referred to the placebo effect as “subjective beliefs.” In that article, researchers found that in three different studies of neuromodulation for depression, participants’ beliefs that they would improve after using the devices was a significant predictor of outcome, but the actual use of the devices was not, compared to placebo. (In a fourth study, belief was a significant predictor of outcome, but so was the actual treatment.)

The current study was authored by Jon Jureidini, Julie Klau, Natalie Aboustate, and Melissa Raven at the University of Adelaide, Australia, and Joanna Moncrieff at University College London, UK. It was published in the Australian & New Zealand Journal of Psychiatry. Jureidini has been interviewed by Mad in America about his work on the lack of evidence base for psychiatric treatments, including antidepressants for children and adolescents. Moncrieff has also been interviewed by Mad in America, and was the lead author on a 2022 study that put the final nail in the coffin of the chemical imbalance myth of depression.

Fluoxetine is the only FDA-approved antidepressant for use in children and adolescents. Nonetheless, its effectiveness has been questioned, even as it is known to increase the risk of suicide in kids. One recent study found a threefold increase in suicide risk and another study found that the risk may be as high as six times greater. Even in adults, antidepressants may double the risk of suicide.

Placebo-Controlled Studies

In placebo-controlled studies, the group that receives an intervention is compared to a group that does not. But those in that control group are given something (the placebo) that makes them think they have received the intervention. Having this group allows researchers to account for a couple of things. For instance, one is that people may get better naturally, without an intervention, so having a control group that doesn’t receive the intervention allows researchers to compare the intervention to the natural improvement that people experience over time.

But another thing the placebo group controls for is the placebo effect—that people improve when they believe that they have received a treatment, whether they actually did or not. A key feature of this kind of study is blinding, a term for keeping participants, researchers, and/or treatment clinicians in the dark about whether the subject received the treatment or not. This is intended to equalize the two groups: if no one knows whether they received the treatment, then the effect should be consistent across the whole study.

Unfortunately, in this type of study, the blind is often broken. One aspect that can easily break the blind is adverse effects: people know the potential side effects of the drug, so if they experience those effects, they can guess that they are probably in the treatment group, not the placebo group. Those who guess that they are receiving the treatment are likely to have an enhanced placebo effect—to do better because they expect to do better. At the same time, those who guess they received the placebo are likely to do worse because they know they did not receive the actual treatment.

But how much impact those guesses have, and whether the placebo effect is stronger than the actual efficacy of the treatment, is different for every study, treatment, and condition.

The Current Study

Back in 2003, the NIMH-sponsored Treatment for Adolescents with Depression Study (TADS) included 439 adolescents aged 12-17 who met DSM-IV criteria for depression. There were four treatment arms, including fluoxetine (Prozac) only; cognitive-behavioral therapy (CBT) only; fluoxetine and CBT; and placebo. The psychotherapy groups were not able to be blinded. The randomized trial lasted for 12 weeks, and participants were asked which group they believed they were in at both 6 weeks and 12 weeks. Improvement in depression was measured with the Children’s Depression Rating Scale–Revised (CDRS-R).

The TADS study is commonly cited as evidence for Prozac’s effectiveness in depression treatment, because the combined drug and CBT group did slightly better than the placebo group. However, the drug group alone did no better than the placebo group in the TADS analysis of the CDRS-R.

The current analysis was conducted as part of the Restoring Invisible and Abandoned Trials (RIAT) initiative, which allowed the researchers access to the raw data from the TADS study. They obtained information on the fluoxetine group (109 participants) and the placebo group (111 participants), since those were the two blinded groups, in order to directly compare the effects of unblinding.

In all the groups, more than 60% of the participants and raters correctly guessed whether they received the drug or placebo (a perfectly blinded study would result in 50% guessing correctly).

The researchers found that the placebo effect was stronger than the actual treatment itself. Those who guessed that they received the treatment were more likely to improve than those who guessed they received the placebo—even if their guess was incorrect. That is, on average, those who believed they received the drug improved, even if they actually received the placebo. Likewise, those who believed they received the placebo were less likely to improve, even if they actually received the drug.

Those who believed they received the drug, on average, improved by 10 points more on the CDRS-R than those who believed they received the placebo. Those who believed they received the drug improved by 26.98 points, on average. Those who believed they received the placebo improved by 16.65 points, on average.

Amazingly, the group that did the best was those who believed they received the drug, but actually received the placebo. These patients did better than those who received the drug and knew it!

Finally, the researchers confirmed the initial finding of TADS: after accounting for the placebo effect (treatment guess), the researchers found that taking Prozac did not improve depression.

The researchers conclude that unblinding, which amplifies the placebo effect, may be the reason antidepressants typically beat placebo by a slight margin in clinical trials. They add that future studies need to make sure to assess unblinding in order to provide accurate data on drug efficacy.

Moreover, since clinical practice guidelines are based on evidence from studies like TADS, the researchers argue that guideline authors need to reassess the evidence base for their recommendations. Recommending antidepressants on the basis of studies like TADS is poor science.

Indeed, the evidence base for antidepressants—even for adults—is so poor that a recent article, authored by 30+ prominent figures in the field, recommends against their use in all but “the most severe depression.” The World Health Organization (WHO) guidelines agree: “Antidepressant medications are not needed for mild depression,” according to the WHO. There are plenty of other approaches, with fewer side effects, that are just as effective.

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Jureidini, J., Moncrieff, J., Klau, J., Aboustate, N., & Raven, M. (2023). Treatment guesses in the Treatment for Adolescents with Depression Study: Accuracy, unblinding and influence on outcomes. Australian & New Zealand Journal of Psychiatry. Published online December 21, 2023. https://doi.org/10.1177/0004867423121862 (Full Text)

The post Placebo Effect—Not Antidepressants—Responsible for Depression Improvement appeared first on Mad In America.

Those who did not receive antipsychotics within the first month after being diagnosed with their first episode of psychosis were, on average, almost twice as likely to be in recovery five years later than those who did immediately receive the drugs. According to the researchers, this means there are many patients who do not need antipsychotics, at least not right away.

The authors of the study were Tomi Bergström at the University of Jyväskylä and the Wellbeing Services County of Lapland, Finland, and Tapio Gauffin at the Wellbeing Services County of Lapland, Finland.

Bergström and Gauffin used the Finnish National Health Registry to identify all those who met the study criteria. This included 3714 adolescents ages 13-20 who received a diagnosis of a psychotic disorder between 2003 and 2013 and had never before taken antipsychotic drugs. The researchers followed their records for five years (or until death). During the first month after diagnosis, 1549 (42%) did not receive antipsychotics. Over five years, 29% ended up never taking the drugs.

The researchers found that, on average, those 1549 people were 1.8 times as likely to be in recovery after five years.

Those in recovery, in this study, were defined as those who were still alive and had not received any form of psychiatric treatment, supportive housing, or disability allowances at five years. The researchers note that these services are provided to the entire population as needed and recorded in the registry based on their universal healthcare system.

Next, the researchers wanted to see if those who eventually did end up on antipsychotics fared worse if there was a delay. That is, is there a subset of patients who need to be put on the drugs immediately and who will be harmed by waiting a month?

To test this, Bergström and Gauffin looked at only the patients who took the drugs by the end of the study and compared those who started immediately with those who ended up taking the drugs later.

They found that there was no difference in most outcomes—recovery and mortality rates—but that those who started the drugs immediately were more likely to receive disability payments and to die younger than those who delayed taking the drugs.

The researchers write:

One explanation often floated against this type of study is “confounding by indication”—that those who have the most severe baseline symptoms are the ones who receive the drugs and also the ones who would be expected to have the worst outcomes. Thus, those who receive the drugs would have worse outcomes not because of the drugs but because of baseline severity.

To account for this, the researchers used a statistical model called stabilized inverse probability of treatment weighting (SIPTW) to control for these possible confounds. After their analysis, all of their results remained the same, indicating that the finding was not due to confounding by indication.

This latest study builds on Bergström’s previous work, particularly a 2020 study that looked at cumulative exposure to antipsychotics for all patients with first-episode psychosis over 19 years. That study also found that those who took the most drugs for the longest period had worse outcomes, including higher mortality rates. And the researchers controlled for confounding by indication in that study as well.

Researchers have found that cognitive-behavioral therapy without antipsychotics is just as effective for first-episode psychosis—that adding drugs provided no additional improvement.

Previous research has also found that interventions for those considered at ultrahigh risk for psychosis, including antipsychotic drugs, can lead to worse outcomes.

And decades of research by luminaries like Wunderink, Harrow, and Jobe have found that those who stop taking antipsychotics have better long-term outcomes.

Researchers have increasingly identified childhood trauma as the primary cause of psychosis, even as biological theories involving dopamine and genetics have been debunked. This is consistent with previous studies that found that experiencing childhood trauma, not heritability, was associated with psychosis.

Thus, interventions that focus on healing from trauma and those that foster empathy, empowerment, and human connection—and respect those with lived experience—may be a more successful route to recovery.

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Bergström, T., & Gauffin, T. (2023). The association of antipsychotic postponement with 5-year outcomes of adolescent first-episode psychosis. Schizophrenia Bulletin Open, 4(1), sgad032. https://doi.org/10.1093/schizbullopen/sgad032 (Link)

The post Antipsychotics Lead to Worse Outcomes in First-Episode Psychosis appeared first on Mad In America.

The 30-plus list of authors reads as a veritable “who’s who” of names in critical psychiatry. The lead author was James Davies, co-founder of the Council for Evidence-Based Psychiatry (CEP), senior lecturer in social anthropology and psychotherapy at the University of Roehampton, and practicing psychotherapist in the UK. The second author was John Read, chair of the International Institute for Psychiatric Drug Withdrawal, professor of clinical psychology at the University of East London, editor of the journal Psychosis, and expert on ECT and psychosis.

Other prominent authors include Joanna Moncrieff (professor of critical and social psychiatry at University College London and founder of the Critical Psychiatry Network) and Mark Horowitz (clinical research fellow in psychiatry at North East London NHS Foundation Trust), whose 2022 paper put the final nail in the coffin of the serotonin theory of depression; Lucy Johnstone, a clinical psychologist who helped launch the Power Threat Meaning Framework, a non-diagnostic alternative to the DSM; Jo Watson, a psychotherapist who founded Drop the Disorder; psychologist Peter Kinderman; Luke Montagu, who joined Davies to co-found the CEP; and Sam Everington, who was knighted and received the OBE for his work in improving primary care. The article also featured psychiatrists, general practitioners, members of parliament, and advocates with lived experience.

We Must Reduce Antidepressant Use

Clinical practice guidelines outside the US, such as the NICE guidelines in the UK, already suggest that antidepressants are not the best first-line intervention for mild to moderate depression. The NICE guidelines suggest watchful waiting, guided self-help, various psychotherapies, exercise, and mindfulness/meditation as better options for less severe depression since they have equal effectiveness but much lower risk of adverse effects. Take, for instance, a recent meta-analysis finding that exercise is just as good as antidepressants at treating mild to moderate depression—and that adding drugs to the regimen does not improve outcomes.

The World Health Organization (WHO) guidelines on depression treatment are even more firm: “Antidepressant medications are not needed for mild depression,” according to the WHO.

Even for severe depression, multiple studies have found that adding antidepressants to cognitive behavioral therapy does not result in better outcomes—psychotherapy alone is just as good in the short term. And therapy alone beats the drugs when it comes to long-term outcomes.

Moreover, psychotherapy doesn’t have the harmful effects of antidepressant drugs, which include sexual dysfunction for up to 88% of those taking them, weight gain and metabolic problems, emotional numbing, and more. Likewise, withdrawal is common after someone stops taking antidepressants and can be severe and last for years. Withdrawal effects of the drugs can include anxiety, depression, brain zaps, fatigue, and even stroke-like symptoms.

Nonetheless, prescriptions for the drugs keep rising. Davies and his co-authors note that antidepressant prescription rates have nearly doubled in the UK over the past decade.

Most people still receive a pill if they present with mild depression—or even undiagnosable, vague malaise. One study in the US found that only 2% of those taking antidepressants actually had severe depression—with more than half failing to meet the criteria for depression. Similarly, a UK study found that more than half of the people on antidepressants don’t meet the criteria for any psychiatric diagnosis. A 2015 study found that more than two-thirds (69%) of those prescribed an antidepressant do not meet the criteria for the diagnosis of depression.

Davies and his co-authors add that the people who disproportionately receive antidepressants are those living in impoverished areas, women, and the elderly—raising questions, they write, “about the extent to which we are wrongly medicalizing and medicating the effects of disadvantage and deprivation.”

The authors write that the prescription of antidepressants for mild depression and non-psychiatric distress must stop. Also, centers focused on withdrawal must be funded to help people struggling to discontinue the drugs. Finally, funding should be diverted to social prescribing, which focuses on the isolation, poverty, and marginalization most associated with the symptoms of depression and which is supported by the WHO.

As James Davies said in a speech to the UK Parliament:

Is There Evidence for Antidepressant Efficacy?

Countless studies have challenged the efficacy of antidepressant drugs for decades. One analysis in 2010 found that the benefit of antidepressant medications “may be minimal or nonexistent, on average, in patients with mild or moderate symptoms”; this leaves open the possibility that for severe depression, the drugs do provide a benefit, however.

Yet researchers in 2008 found that although antidepressants appear slightly more efficacious for severe depression, the difference is “relatively small even for severely depressed patients.” The researchers go on to state that this benefit is attributable to the placebo effect becoming less powerful for patients with severe depression rather than an increase in the efficacy of the drug.

Worse, in another study, researchers found that those with more severe depression, those with comorbid anxiety, and those who were suicidal were least likely to benefit from the drugs.

The drugs are known to make people feel suicidal rather than protect against suicide: A recent study found that antidepressants increased suicidality threefold in children and adolescents and doubled the risk in those 18-24, and didn’t reduce suicidality even for older patients.

That’s consistent with previous studies, which have repeatedly shown that antidepressants increase suicide risk, particularly for children and adolescents, with some studies finding more than doubling the risk of suicide and at least one analysis finding a sixfold increase.

Since the 1990s, researchers have warned of the danger that antidepressant treatment worsens outcomes by disrupting the brain’s natural functioning. These warnings have been borne out in multiple studies: Researchers have indeed repeatedly found that those taking the drugs have worse outcomes in the long term, even after controlling for the baseline level of depression severity.

And even all these negative findings and warnings can be considered optimistic because of publication bias—negative studies are much less likely to be published. For instance, a study in the New England Journal of Medicine in 2008 examined both published and unpublished studies of antidepressant efficacy. They found that half of the antidepressant trials found no beneficial effect for antidepressants compared with placebo. The only problem: almost none of the negative studies were ever published, and those that were ended up “spun” to appear positive.

But depression—in its natural state—is self-limiting. If you don’t receive treatment, you are actually quite likely to recover on your own. An NIMH study in 2006 found that 85% of untreated depressed patients recovered spontaneously within one year.

Compare that to outcomes for treated depression: in a study where over a thousand people with depression were treated with an intense program, beginning with antidepressant drugs (more than half on multiple drugs) and also including psychotherapy and hospitalization, less than 25% even responded to treatment, much less recovered. Unfortunately, this study had no placebo group to which we could compare this effect, but in clinical trials, the placebo effect averages about 31%—meaning that more people would be expected to benefit from a placebo than benefited from aggressive drug treatment in the study.

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Davies, J., Read, J., Kruger, D., Crisp, N., Lamb, N., Dixon, M., . . . & Marshall-Andrews, M. (2023). Reversing the rate of antidepressant prescribing: Politicians, experts, and patient representatives call for the UK government to reverse the rate of antidepressant prescribing. BMJ, 383, 2730. doi: https://doi.org/10.1136/bmj.p2730 (Link)

The post Stop Using Antidepressants Except for “the Most Severe Depression,” Experts Say appeared first on Mad In America.

“Our findings do not indicate any advantage of adding antipsychotics as adjunctive to antidepressants as maintenance treatment. Considering the wide use, known side effects, and the current lack of evidence supporting the benefit, further studies on the effect of antipsychotics in the maintenance phase of psychotic unipolar depression are urgently warranted,” the researchers write.

The research was conducted by Ahmed Al-Wandi and Axel Nordenskjöld at Örebro University, Sweden, and Mikael Landén at Gothenberg University and the Karolinska Institutet, Sweden. The study was published in Acta Psychiatrica Scandinavica.

The researchers note that it is common practice to give antipsychotic drugs (in addition to antidepressants) to those with psychotic depression, and their results bear this out; in their study, twice as many people got combination therapy. Indeed, the American Psychiatric Association guidelines for treatment of psychotic depression list combination therapy as a first-line intervention, along with electroconvulsive therapy (ECT). Sounds good on the surface, right? If people have “psychosis,” add an “antipsychotic.”

But sometimes things that sound good on the surface are actually harmful. The results speak for themselves: after two years, 42.3% of those in the combination group were either readmitted or died by suicide, while slightly fewer (36.6%) in the antidepressants-alone group met this outcome. That is, adding antipsychotics didn’t help prevent this outcome, it increased the risk.

The researchers used Swedish national registries to identify patients who were hospitalized with a diagnosis of psychotic unipolar depression between 2007 and 2016. There were two groups: 1,419 people received antidepressants alone, while 2,972 people got both antidepressants and antipsychotic drugs.

Because the argument could be made that these results were confounded by other factors, including baseline severity, the researchers controlled for a variety of factors that could have influenced the results. Moreover, the researchers noted that at baseline, the two groups were similar in all ways, except that the antidepressants-alone group was more likely to have received ECT during the initial hospitalization (36.4% versus 26.7%). Therefore, in further analyses, the researchers controlled for ECT, as well as other possible confounds including sex, age, prior admissions, comorbidity, and other pharmacological treatments. This did not change their results.

In terms of specific outcomes, significantly more in the combined treatment group ended up rehospitalized: 41.8% versus 35.9% in the antidepressants-alone group. This puts to rest the notion that antipsychotics prevent relapses. Instead, it seems that they make relapse more likely.

People in the combined group were also more likely to die of any cause (other than suicide): 3.5% versus 2.4% in the antidepressants-alone group. There was no difference in deaths by suicide between the two groups.

In another analysis, the researchers searched for any subgroup of patients for whom combination therapy was actually helpful. They did not find any.

They did, however, learn that for young people (18-30 years old) combination therapy was even more dangerous than for older people. Young people on combination therapy were about twice as likely to reach the main outcome of rehospitalization or death by suicide.

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Al-Wandi, A., Landén, A. M., &  Nordenskjöld, A. (2023). Antipsychotics in the maintenance phase for psychotic depression. Acta Psychiatrica Scandinavica. Published online November 6, 2023. https://doi.org/10.1111/acps.13628 (Full Text)

The post Adding Antipsychotics Worsens Outcomes in Psychotic Depression appeared first on Mad In America.

Xanax is the most widely-prescribed benzodiazepine in the United States, according to the researchers. It is also the most commonly abused benzodiazepine.

The article was written by Rose Ahn-Horst at Harvard Medical School, Massachusetts General Hospital, and McLean Hospital, and former FDA reviewer Erick Turner at Oregon Health & Science University and the Veterans Affairs Portland Health Care System. It was published in Psychological Medicine.

Turner has used FDA data to illuminate the influence of publication bias and lack of efficacy of other drugs as well, including antidepressants and esketamine.

Because the FDA requires that pharmaceutical companies submit data on all trials that will be used for regulatory approval, it is possible to examine the data from all the pivotal studies conducted rather than just the ones that end up published.

In this case, the researchers found that the FDA received data on five Phase 2 or Phase 3 trials of Xanax extended release—alprazolam XR—for panic disorder. The FDA considered four of the studies to be negative—showing that the drug did not beat placebo on all primary endpoints. They approved the drug on the strength of the fifth study, which was considered positive.

Study 1, conducted between 1986 and 1989, was presented as a positive result in its published version. However, it was considered negative by the FDA statistician because it only achieved statistical significance on five of the seven primary endpoints. The published version omitted the negative results, spinning the study as positive.

Study 2, conducted between 1988 and 1990, was published as a positive study, and the FDA agreed—all seven endpoints were statistically significant. However, data from one of the three study sites was destroyed before the FDA analysis by the study investigator, and the FDA reported that the “validity of the data reported could not be verified.” This was the positive study used by the FDA to approve the drug. Notably, the FDA had initially required the usual two positive studies, but according to the researchers, it relaxed this requirement in this case.

Study 3, conducted between 1990 and 1991, was a complete failure, finding the drug to be no better than placebo on any of its primary outcome measures. All five outcomes were nonsignificant. Yet this study was published as a positive trial after the researchers omitted the primary endpoint and presented only “preliminary results” using a different statistical method than they had used in the FDA’s records.

Study 4, conducted between 1990 and 1991, was nonsignificant on all five primary outcome measures. The study was never published.

Study 5, conducted between 1994 and 1995, was considered a negative trial by the FDA, and they did not include more information about their statistics in this case. The study was never published.

When analyzing the published literature, the researchers found an effect size of 0.47 in favor of Xanax (alprazolam). However, when they added the unpublished data, they found that the effect size shrank to 0.33.

According to the researchers:

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Ahn-Horst, R. Y., & Turner, E. H. (2023). Unpublished trials of alprazolam XR and their influence on its apparent efficacy for panic disorder. Psychological Medicine, 1-8. https://doi.org/10.1017/S0033291723002830 (Link)

The post Only One of Five Key Xanax Trials Deemed Positive by F.D.A. appeared first on Mad In America.

The findings were sex-dependent, with male rats exhibiting anhedonia and female rats exhibiting cognitive deficits and impulsivity (anhedonia is a term for the inability to feel pleasure or joy). The impact on male rats was worse if their mothers received Prozac during pregnancy, while the impact on female rats was worse if their mothers received Prozac during breastfeeding.

Moreover, mothers who received Prozac had fewer babies and babies with lower birth weights. Mothers who received Prozac while breastfeeding, specifically, found their children continued to have lower body weight into adulthood.

The researchers also found that rats born of mothers given Prozac ended up with many differences in terms of brain development and gene expression compared with rats whose mothers did not receive the drug.

The study was conducted by researchers at the Department of Pharmacological and Biomolecular Sciences “Rodolfo Paoletti,” Universita Degli Studi di Milano, Milan, Italy. It was published in the journal Brain, Behavior, and Immunity.

The researchers used the sucrose preference test to assess anhedonia, the novel objects recognition test to evaluate cognitive functioning, and the elevated plus maze test to assess impulsivity. Whether these tests serve as an exact enough map of human experiences is an open question, but they are standard for assessing such responses in animal studies.

The researchers do not address the implications of their study for human mothers using antidepressants or the potential impacts on their children. Instead, the researchers frame their study as somehow exploring the natural role of serotonin—even though their study was explicitly about using an antidepressant to disrupt the serotonin system:

Despite this oversight, there is plenty of research on the adverse impacts of antidepressant drugs used in pregnancy.

Researchers have argued that antidepressants should be discontinued in pregnancy because of the risk of neonatal withdrawal syndrome. Studies have consistently found antidepressant use in pregnancy to be associated with numerous risks to neonatal health, including neonatal withdrawal syndrome, preterm birth, birth defects, developmental problems, cardiopulmonary problems, and even death.

Some studies have even accounted for preexisting factors like depression severity by comparing women who continued using antidepressants during pregnancy with women who had the same indication and did use antidepressants initially—but stopped after becoming pregnant. Those who continued to use antidepressants had an increased risk of neonatal health complications, including preterm birth, low birth weight, and hospitalizations in their newborns, compared with mothers who stopped using the drugs during pregnancy.

Antidepressant use during pregnancy has also been found to alter brain development in the fetus, cause speech disorders, and impair neurological functioning.

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Gallo, M. T., Brivio, P., Dolci, B., Fumagalli, F., & Calabrese, F. (2023). Perinatal serotonergic manipulation shapes anhedonic and cognitive behaviors in a sex- and age-dependent manner: Identification of related biological functions at central and peripheral level. Brain, Behavior, and Immunity, 114, 118-130. https://doi.org/10.1016/j.bbi.2023.08.016 (Link)

The post Animal Study Shows Impact of Prozac in Pregnancy on the Child appeared first on Mad In America.

The researchers were led by Dogukan Koc at Erasmus University Rotterdam, the Netherlands. This was part of Generation R, a population-based study in Rotterdam. The study included 3,198 mothers with a delivery date between April 1, 2002, and January 31, 2006, and the children were followed with three brain scans over time, the last of which occurred when they were 15.

To account for factors such as the effect of underlying maternal depression and when, specifically, the mothers used antidepressants, the researchers split the cohort into five groups. There were 41 with SSRI use during pregnancy, 77 who only used SSRIs before pregnancy, 257 who did not use SSRIs but had depressive symptoms during pregnancy, 74 who had depressive symptoms only after giving birth, and 2,749 controls who had neither depressive symptoms nor SSRI use.

So, could this be explained by the mother’s depression? No, write the researchers. For mothers who were depressed but did not take SSRIs, the children were almost no different from the healthy controls. Prenatal depression was associated with a smaller volume in one area, the rostral anterior cingulate gyrus. Similarly, postnatal depression was associated with a smaller volume in one area, the fusiform gyrus.

Those differences in one area each should be compared to the large, brain-wide reduction in volume in numerous areas experienced by kids whose mothers took SSRIs. Moreover, even in the fusiform gyrus, kids whose mothers took SSRIs had larger reductions in volume than kids whose mothers had depression but didn’t take SSRIs.

The good news is that some of these brain volume reductions appeared to have a catch-up effect: for instance, amygdala volumes had increased by age 15, so kids who were exposed to SSRIs were not any different from controls.

Unfortunately, many of the brain volume differences didn’t catch up. Moreover, it’s unclear what effect these volume differences throughout all of childhood would have on a kid’s development, even if it catches up by their late teenage years.

Previous Research

Studies have consistently found antidepressant use in pregnancy to be associated with myriad risks to neonatal health, including neonatal withdrawal syndrome, preterm birth, congenital disabilities, developmental problems, cardiopulmonary problems, and even death.

In one study, researchers found a sixfold increase in neonatal withdrawal syndrome when mothers took antidepressants. In another study, researchers found that 30% of babies born to mothers who used antidepressants experienced neonatal withdrawal syndrome. None of the babies whose mothers did not use antidepressants had this complication. And yet another study found that over half (56%) of babies exposed to SSRIs had this problem.

Researchers have argued that antidepressants should be discontinued in pregnancy because of this risk, which includes symptoms of hypoglycemia, tremors, hypotonia, hypertonia, tachycardia, rapid breathing, and respiratory distress in babies born to mothers who use antidepressants.

Studies have also accounted for preexisting factors like depression severity by comparing women who continued using antidepressants during pregnancy with women who had the same indication and did use antidepressants initially—but stopped after becoming pregnant. That study found that those who continued to use antidepressants increased the risk of neonatal health complications in their newborns, including preterm birth, low birth weight, and hospitalizations.

Other research has found that antidepressant use during pregnancy alters brain development in the fetus. These findings have appeared in top journals, too: A study in JAMA Psychiatry found that antidepressant use during pregnancy increased the risk of infants with speech disorders, while a study in the American Journal of Psychiatry found that antidepressant use during pregnancy increased the risk of impaired neurological functioning in infants.

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Koc, D., Tiemeier, H., Stricker, B. H., Muetzel, R. L., Hillegers, M., & El Marroun, H. (2023). Prenatal antidepressant exposure and offspring brain morphologic trajectory. JAMA Psychiatry. Published online August 30, 2023. doi:10.1001/jamapsychiatry.2023.3161 (Link)

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The study was conducted by Martin Plöderl at Paracelsus Medical University in Salzburg, Austria, and Simone Amendola and Michael P. Hengartner at the Zurich University of Applied Sciences, Switzerland. In keeping with their findings, the study was published in a prestigious—but non-psychiatric—journal, the Journal of Clinical Epidemiology.

Critics sometimes argue that study quality is the main factor in publication—that it just so happens that all the favorable studies conducted by pharma are of good quality, while all the unfavorable studies by independent researchers are of poor quality.

However, the researchers found that study quality did not explain the selective publication they identified. Instead, it appears that top psychiatric journals tend to publish researchers who are funded by pharma, and thus find favorable results, whether the study is of good quality or not—and good quality studies by independent researchers, who are more likely to find unfavorable results, end up in the bin.

Hengartner sums it up succinctly on X:

“Studies of authors with fCOI were NOT of higher quality than studies of industry-independent lead-authors.”

3) Within psychiatric journals, lead-authors with fCOI published in journals with higher impact factor and journal ranking. Note that studies of authors with fCOI were NOT of higher quality than studies of industry-independent lead-authors

— Michael P. Hengartner, PhD (@HengartnerMP) August 6, 2023

The researchers warn that this creates a false image of the safety and efficacy of antidepressant drugs. If industry-funded studies, which find favorable results for antidepressants, are published in the top psychiatric journals, while studies of the same quality that are independent but find unfavorable outcomes are shunted into non-psychiatric and low-ranking journals, then the evidence base in the top journals of the specialty is biased and misleading.

Positive studies in top journals in the specialty are more likely to receive media coverage and be taken seriously by journalists, academics, and psychiatrists themselves. Thus, beginning with a biased set of studies creates an exponentially expanding bubble of misleading information.

In this particular study, Plöderl, Amendola, and Hengartner focused on observational studies of the link between antidepressants and suicide. Because death by suicide is a rare event, it is difficult to study in small, randomized controlled trials (RCTs), so observational studies—which follow larger groups of people over time—are our main source of information about this outcome.

Thus, in this context, studies that were considered “favorable” to industry were those that found no link between antidepressants and suicide, while “unfavorable” studies were those that did find such a link. (There were no studies that found antidepressants actually reduced suicide.)

The researchers identified 27 studies that met these criteria published between 1990 and 2020.

Studies that were published in psychiatric journals (typically by researchers with financial ties to pharma) found, on average, no link between antidepressants and suicide. Studies that were published in non-psychiatric journals (typically by independent researchers) found, on average, that antidepressants increased suicide. This was true for both death by suicide and suicide attempts:

Yet the quality of the studies in both psychiatric and non-psychiatric journals was about the same, and when the researchers accounted for quality in their analysis, it actually increased the selective publication effect they found rather than mitigating it:

The results for journal prestige were less powerful—higher-ranked journals were more likely to publish favorable studies, but once study quality was included in the analysis, this effect was no longer significant. However, higher-ranked journals were also more likely to publish researchers with financial ties to pharma—and this remained significant after adjusting for study quality.

Antidepressant drugs have been consistently linked to increased suicide attempts and deaths. Studies have repeatedly shown that antidepressants increase suicide risk, particularly for children and adolescents, with some studies finding more than doubling the risk of suicide and at least one analysis finding a sixfold increase.

Studies have also found that antidepressant drugs worsen outcomes in the long term, even after controlling for the baseline level of depression severity.

Indeed, Plöderl, Amendola, and Hengartner were unable to find even a single study that supported the idea that antidepressants reduce suicide, with the “favorable” studies in their research being those that found the drugs simply don’t increase suicide. Yet, as they write, antidepressants are often given to those with severe depression and those at the highest risk for suicide, with the reasoning that the drugs will somehow reduce this risk—despite the lack of evidence for any such effect.

They add that in this context, antidepressant use is based on “unsubstantiated claims” of suicide reduction, despite the possibility that the drugs actually increase it, making the use of these drugs a public health issue that needs to be addressed:

Plöderl, Amendola, and Hengartner conclude that the research base from psychiatric journals is biased, with selective publication of favorable results by researchers with financial ties to pharma, which has nothing to do with study quality. They write that researchers and clinicians need to read studies about antidepressants and suicide risk in non-psychiatric journals to obtain an unbiased view of the evidence.

Ultimately, Plöderl, Amendola, and Hengartner write that independent researchers conclude that the drugs increase suicide risk. Psychiatry’s denial of this fact through selective publication of favorable industry-sponsored studies has led to the current public health crisis of increased suicide deaths due to antidepressant use.

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Plöderl, M., Amendola, S., Hengartner, M. P. (2023). Observational studies of antidepressant use and suicide risk are selectively published in psychiatric journals. Journal of Clinical Epidemiology. Published online August 04, 2023. DOI:https://doi.org/10.1016/j.jclinepi.2023.07.015 (Link)

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The study was led by Tyra Lagerberg at the Karolinska Institutet and was published in Neuropsychopharmacology.

The data came from a Swedish registry, including 162,267 people who received a diagnosis of depression. Of these, 52,917 people began treatment with an SSRI antidepressant within 28 days, while 109,350 did not. The outcome of interest was suicide attempts as recorded in the registry (thus, attempts serious enough to result in an encounter with the medical profession). The researchers analyzed data at a three-month follow-up and at one year (the results were similar at both time points).

The researchers included both the intention-to-treat analysis and the per-protocol analysis, two different ways of handling the outcome data. The gold standard is to include both so that the reader can see all the data.

In this case, both the intention-to-treat analysis and the per-protocol analysis showed that SSRI use was associated with increased suicide attempts in those under 25. The only difference was the magnitude of the effect.

In the intention-to-treat analysis, 6-17-year-olds were 2.9 times more likely to attempt suicide on SSRIs. In the per-protocol analysis, they were 3.34 times more likely.

Those 18-24 were 1.59 times more likely to attempt suicide in the intention-to-treat analysis and 2.01 times as likely in the per-protocol analysis.

Those over 25, however, were not more likely to attempt suicide if they received an antidepressant, based on either analysis.

However, this null finding also means that antidepressants did not have a preventative effect—they did not reduce the likelihood of suicide for those over 25, either.

The main limitation of this study is that the researchers couldn’t account for baseline severity. That is, people who had more severe depression—and thus, increased suicide risk—may have been more likely to take an antidepressant. This is especially true since the researchers note that psychotherapy is the first-line treatment for mild-to-moderate depression in Sweden.

However, the researchers accounted for suicide risk in another way: they were able to account for those who had a history of suicidal behavior (which is a good proxy for those at the highest risk of future suicide attempts).

Those who had previous attempts were more likely to attempt again—whether or not they took antidepressants. That is, antidepressants seemed to neither worsen the problem nor help at all.

Thus, probably the best way to interpret the results of the study is as follows:

For those younger than 25, with no history of suicidal behavior, taking an antidepressant makes you up to three times more likely to attempt suicide, with that likelihood decreasing as you age. For those 25 or older, taking an antidepressant doesn’t help reduce suicide. Similarly, for those at high risk for suicide, taking an antidepressant doesn’t reduce the risk.

The finding here is consistent with previous studies, which have repeatedly shown that antidepressants increase suicide risk, particularly for children and adolescents, with some studies finding more than doubling the risk of suicide and at least one analysis finding a sixfold increase.

Studies have also found that antidepressant drugs worsen outcomes in the long term, even after controlling for the baseline level of depression severity.

And one study found that those with more severe depression, those with comorbid anxiety, and those who were suicidal were the least likely to benefit from antidepressant drugs.

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Lagerberg, T., Matthews, A. A., Zhu, N., Fazel, S., Carrero, J. J., & Chang, Z. (2023). Effect of selective serotonin reuptake inhibitor treatment following diagnosis of depression on suicidal behaviour risk: A target trial emulation. Neuropsychopharmacology. Published online July 28, 2023. https://doi.org/10.1038/s41386-023-01676-3 (Link)

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The study was led by Reinhard Maß Kerstin Backhaus, Katharina Lohrer, Michael Szelies, and Bodo K. Unkelbach at the Center for Mental Health Marienheide, Germany. It was published in the journal Psychopharmacology.

Their participants came from the Aaron T. Beck inpatient unit at the Center for Mental Health Marienheide. The Beck unit is focused on providing CBT to all patients but also offers pharmacological intervention as needed, following a medical model of psychiatric treatment.

Several years ago, the Beck unit operated following the German guidelines, which recommend combining antidepressants with psychotherapy for severe, chronic, or recurrent depression. However, after a 2019 study revealed that the patients who received antidepressants did no better than those who did not, the unit’s policy changed—only those who specifically requested antidepressants were considered for those drugs. (All patients continue to receive CBT.)

Thus, the researchers were able to conduct this study by comparing outcomes from the previous years (Phase A, in which 60.3% of patients were prescribed antidepressants by the time they left the unit) with more recent outcomes (Phase B, in which only 27.9% of patients were prescribed antidepressants).

Unlike clinical trials, which typically have stringent criteria for participants—often excluding those with suicidal thoughts, those with severe or recurrent depression, and those with other mental health problems—the current study included a much more realistic group of patients. That’s because the participants comprised the actual patients treated in the Beck unit during this time. All the participants had depression severe enough to require hospitalization, with features such as a high risk of suicide, inability to work, and having had ineffective outpatient treatment already. Many patients had comorbid conditions, such as anxiety (about 20%), personality disorders (about 20%), OCD, eating disorders, psychosis, or PTSD (about 16% combined).

Thus, this study tells us what treatment works for real-life patients who are being treated in an inpatient hospital setting.

To measure depression severity, the researchers compared scores on the Beck Depression Inventory (BDI-II). The average score on the BDI was the same for both groups, as was the number of people who “responded” to treatment (their BDI score decreased by at least 50%) and the number of people who “remitted” (BDI score of 12 points or less). This was true both at the time the patients left the inpatient unit, as well as at the six-month follow-up.

In both groups—whether patients received an antidepressant plus CBT or CBT alone—a little more than 70% found the treatment to be effective (responded or remitted by the time they left treatment). After six months, this number dropped somewhat—closer to 50%—but remained similar in both groups.

And again, this is for patients hospitalized with the highest depression severity, suicidality, and other mental health problems at the same time.

The researchers sum up their results:

Four patients died by suicide during Phase A. All four were taking antidepressant drugs. No patients died by suicide during Phase B.

These outcomes demonstrate that whether patients received an antidepressant or not, they generally improved with CBT, and most of them maintained that improvement at six months. Some further analyses added preliminary evidence that the CBT-alone condition was slightly better than the combined condition: In the CBT-alone condition, treatment time was shorter, there were fewer dropouts, and the effect size for the decreased depression scores was higher.

The researchers write that their finding is consistent with other studies, including a large 2023 meta-analysis that found CBT alone was just as good as combined therapy.

One limitation of the study may involve the expectation effect: Patients who decide to go to the Aaron T. Beck inpatient unit know that they will receive psychotherapy and are likely to believe that it will help them. This may differ from patients in other units, who may not have that belief. It may also vary by country—it’s possible that patients in the US don’t have as high an opinion of CBT and thus wouldn’t get the boost from having positive expectations. It’s also possible that a hospital inexperienced in CBT might do a worse job at psychotherapy than the Beck unit, which specializes in that approach.

However, the researchers also mention that the slight benefit of antidepressants over placebo seen in clinical trials may be due to the methodological flaws of those studies. They cite the recent finding that only about 15% of patients may experience a unique benefit from antidepressant drugs—and note that even that could be due to the breaking of the blind in drug trials.

CBT alone has been found to be just as effective as antidepressants in the short term and better than drugs in the long term. Moreover, psychotherapy avoids the harmful effects of antidepressant drugs, including sexual dysfunction for up to 88% of those taking them, weight gain and metabolic problems, emotional numbing, and more. Psychotherapy also doesn’t cause withdrawal, which is common after stopping antidepressants and can be long-lasting and severe.

Studies have found that antidepressant drugs may actually worsen outcomes in the long term, even after controlling for the baseline level of depression severity.

And one study found that those with more severe depression, those with comorbid anxiety, and those who were suicidal were least likely to benefit from antidepressant drugs.

The researchers in the current study write that clinical practice guidelines should be updated to reflect the lack of benefit for add-on antidepressant treatment. However, they note that this is unlikely because authors with financial ties to the pharmaceutical industry craft the guidelines.

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Maß, R,. Backhaus, K., Lohrer, K., Szelies, M., & Unkelbach, B. K. (2023). No benefit of antidepressants in inpatient treatment of depression. A longitudinal, quasi‑experimental field study. Psychopharmacology. https://doi.org/10.1007/s00213-023-06417-4 (Link)

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Since the 2008 publication of the STAR*D results in the American Journal of Psychiatry (AJP), however, those researchers have been criticized for misleading the public about the true remission rates in the study.

Now, in a new study, researchers were able to obtain the patient-level data used in the STAR*D. Based on their analysis, the true remission rate—over the year-long trial—was a little more than one-third.

STAR*D was an open-label, real-world trial of antidepressants conducted at 41 different treatment centers. The study was meant to show outcomes after one year. There was no placebo control group with which to compare the results.

The study included 4,041 patients with major depressive disorder. They were started on the SSRI citalopram (Celexa), but if they did not respond to that drug, there were three more treatment levels, individualized for each patient. There were 11 drug combinations offered in the study. This was meant to reflect real-world practice, in which patients who don’t respond to a drug are (theoretically) given a different drug until they find something that works.

The 2010 Reanalysis

In a 2010 study, researchers H. Edmund Pigott, Allan M. Leventhal, Gregory S. Alter, and John J. Boren reanalyzed the published results of STAR*D—combining data from various tables and other data reporting—to discover that the original publication had misled the public.

The STAR*D researchers submitted a protocol before conducting the study, which outlines exactly what measures will be used and how they will be reported. In that protocol, remission on the Hamilton Rating Scale for Depression (HRSD) was listed as the primary outcome measure—the main way to tell whether the treatment was successful or not.

However, in their AJP publication of the STAR*D results, the researchers did not include the primary outcome of remission on the HRSD. They simply left this out of the publication entirely. Instead, they reported on a different measure, one that they themselves created: the Quick Inventory of Depressive Symptomatology—Self Report (QIDS-SR).

Crucially, the HRSD was delivered by a third party to ensure that the researchers were blinded to the outcomes, which guards against their biases and the placebo effect. Unlike the HRSD, though, the QIDS-SR was unblinded, meaning that researcher biases and the placebo effect likely enhanced the scores.

However, without access to the original patient-level data, it was not possible to see exactly how much this outcome switching affected the results. That’s why the new study—with its finding that only 35% counted as “remitted” on the HRSD—is so important.

In 2010, Pigott, Levantal, Alter, and Boren documented that 607 of the STAR*D had an HRSD score of less than 14 and thus were ineligible to be in the trial because they weren’t very depressed to begin with. Yet, many in this group subsequently scored as remitted during one of the four stages of active treatment, inflating the remission rates.

Moreover, for those that remitted and entered into the year-long follow-up, they would not be scored as having “relapsed” during the follow-up unless their scores rose back up to 14 or higher on the HRSD scale. Thus, patients in this group of 607 who weren’t eligible for the trial in the first place could be counted as remitted and non-relapsed at the end of one year, even though, at that point, they were worse than when they entered the study.

And finally, Pigott, Leventhal, Alter, and Boren found that the actual number of people who stayed remitted and continued to the end of the trial was dismal—108 of the 4,041 in the trial, or about 2.7%.

A huge percentage of the STAR*D participants dropped out of the trial. Almost 10% dropped out within two weeks, and over a thousand participants dropped out during their first trial of antidepressants—many of them counted as having “remitted,” despite the fact that it’s usually people who do poorly or have adverse effects that drop out of studies.

The 2018 Reanalysis

In 2018, Pigott and other researchers—led by renowned Harvard researcher in placebo studies Irving Kirsch, along with Tania B. Huedo-Medina, and Blair T. Johnson—were able to access the patient-level data. They analyzed this data, focusing on just the first antidepressant trial in STAR*D.

Kirsch, Huedo-Medina, Pigott, and Johnson juxtaposed these outcomes to comparator trials of antidepressants (studies that compare antidepressant drugs against one another, rather than against a placebo, since STAR*D did not have a placebo group).

In comparator trials, the average improvement in HRSD score is 14.8 points. In the STAR*D, it was 6.6 points.

In comparator trials, the average remission rate is 48.4%. In STAR*D, it was 25.6%.

In comparator trials, the average response rate is 65.2%. In STAR*D, it was 32.5%.

They add that the antidepressants in STAR*D performed worse than what is typically seen from a placebo group in clinical trials.

The New Reanalysis

In this context, the new reanalysis of patient-level data, which shows that the original STAR*D publication used outcome switching to double the efficacy of antidepressant drugs (from 35% to 67%), is a confirmation of the way the original study results misled the public.

The reanalysis was conducted by Pigott and Kirsch, along with Thomas Kim, Colin Xu, and Jay Amsterdam.

According to Pigott, Kim, Xu, Kirsch, and Amsterdam, the highly publicized inflated outcomes presented in the original STAR*D publication have left the public with the incorrect assumption that antidepressant drugs are effective for over 15 years. They argue that this misleading data has led to a failure to search for better interventions that could be more effective.

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Pigott, H. E., Kim, T., Xu, C., Kirsch, I., & Amsterdam, J. (2023). What are the treatment remission, response and extent of improvement rates after up to four trials of antidepressant therapies in real-world depressed patients? A reanalysis of the STAR*D study’s patient-level data with fidelity to the original research protocol. BMJ Open, 0, e063095. doi:10.1136/bmjopen-2022-063095 (Link)

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The researchers randomly assigned 275 kids aged 7-17 with a diagnosis of generalized anxiety disorder (GAD) to either receive Lexapro or a placebo. The trial lasted for eight weeks.

The findings were mixed. On the 30-point PARS-GAD anxiety measure, there was a mean difference of 1.42 points between the drug and placebo group (statistically significant at p <0.05, but not significant at p <0.01). This is the finding that supports the FDA’s approval.

However, the researchers also found that there was no difference between groups in response to the drug, remission from anxiety, and overall functioning. That is, about the same number of kids, whether on the drug or on placebo, experienced clinical improvement (“response”) or no longer had anxiety (“remission”). Nor did the drug improve overall functioning.

Concerningly, Lexapro also increased suicidality sixfold. In the escitalopram group, 9.5% of the kids became suicidal—compared with 1.5% in the placebo group. One patient actually attempted suicide in the escitalopram group (versus none in the placebo group).

This is especially notable since having a depression diagnosis or suicidal ideation were exclusion criteria for the study, meaning that the kids were not depressed or suicidal when they started the drug trial.

The researchers’ conclusions? Despite the same number of kids improving whether they received the drug or placebo and suicidality increasing sixfold in those who took the drug, they write:

SSRIs (like Lexapro), despite often being prescribed for people at risk of suicide, have been repeatedly shown to increase suicide risk, particularly for children and adolescents. That’s why the FDA has required a “black box warning” on SSRIs to let consumers know that the drugs make kids and teens suicidal.

Forest Labs (which was since bought by Allergan, which then merged with AbbVie) paid $313 million in 2010 for obstruction of justice, illegal marketing, kickbacks, and false insurance claims related to Lexapro and other drugs.

Among other controversies, AbbVie was forced to pay $24 million in 2018 and another $25 million in 2020 to settle lawsuits about illegal kickback practices and illegal marketing for its various drugs. Additionally, Allergan was one of the main firms accused of creating the opioid crisis by illegally marketing opioids. Last year, AbbVie agreed to pay $2.37 billion to settle these allegations.

The current study was published in the Journal of Child and Adolescent Psychopharmacology. Like most published reports of clinical trials of drugs today, the pharmaceutical company’s own employees were listed as authors, and it paid a medical writing company, Prescott Medical Communications Group, to write the article. Indeed, AbbVie made it clear that it controlled all aspects of the trial, writing that it “funded this study and participated in the study design, research, analysis, data collection, interpretation of data, and reviewing and approval of publication.”

The first author was Jeffrey R. Strawn at the University of Cincinnati Medical Center. While he is not an employee of AbbVie or the companies AbbVie paid to conduct the study, the paper’s disclosures state he has received research funds from Abbvie.

Authors Edward Greenberg, Chengcheng Liu, and Mallika Gopalkrishnan are direct AbbVie employees. Authors Leslie Moldauer, Rebekah D. Hahn, Alexandria Wise, Kristina Bertzos, and Beth Eisenberg are all employees of Syneos Health, a company funded by AbbVie to conduct the study. James A. Knutson, the paper’s last author, owns Core Clinical Research, another such company. Author Molly McVoy received a grant from The Hartwell Foundation, which focuses on expanding biomedical interventions in children.

Carol Brown, the Prescott Medical Communications employee who wrote the article, is not listed as an author. As is now usual for such “ghost authors,” she is instead acknowledged for her “writing and editorial assistance.”

It’s usually required for an article to specify what work each individual listed author did on the study and the article writing. Here’s that paragraph in this study:

As can be seen by this acknowledgment, there is no assertion that the named authors designed and conducted the study or that they wrote the article. The published article is AbbVie’s report of its trial, and not surprisingly, the article draws a conclusion that escitalopram is safe and effective in children, even though—in the same article—the published data tells of a drug treatment that is ineffective in children and increases the likelihood they will become suicidal. It is, of course, the conclusion that AbbVie will now use to market escitalopram for use in children.

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Strawn, J. R., Moldauer, L., Hahn, R. D., Wise, A., Bertzos, K., Eisenberg, B., & Knutson, J. A. (2023). A multicenter double-blind, placebo-controlled trial of escitalopram in children and adolescents with generalized anxiety disorder. Journal of Child and Adolescent Psychopharmacology, 33(3), 91-100. http://doi.org/10.1089/cap.2023.0004 (Link)

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