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Antidepressant Trials May Exclude Over 82% of People with Depression

A recent publication in the Journal of Psychiatric Practice documented that nearly 4/5 individuals diagnosed with major depression are considered ineligible to participate in clinical trials for new antidepressant drugs.  This means that for every 5 individuals with depression that attempt to join an antidepressant clinical trial, only one will meet inclusion criteria for registration.  Oddly enough, many people suffering from refractory depression are likely to be the people that really want to participate in new clinical trials.

While newer isn’t always better in terms of therapeutic value, many individuals fail to respond to current-market treatments, resulting in diagnosis of “refractory” depression.  In some cases of refractory depression, engaging in clinical trials may be a way to maintain “hope” that something will provide temporary symptomatic relief.  If they’ve tried every clinically recommended intervention (drug, supplement, therapy, etc.) only to derive no benefit, chances are they want to participate in the research of something new.

Majority of People with Depression (82%) Excluded from Antidepressant Trials

When it comes to testing the efficacy of any medication in clinical trials, the pharmaceutical companies want the best chances of not only getting their drug approved, but of understanding the true effects of their antidepressant.  In order to understand the true effects of their new antidepressant with a high degree of accuracy, a pharmaceutical company must set stringent inclusion criteria.  This criteria generally restricts registration to those with a specific set of characteristics.

It just so happens that a majority of individuals with depression end up getting excluded from antidepressant registration trials.  This is related to the fact that the criteria is organized to accomplish the following primary goals:

  1. Detect accurate drug effects: The goal of conducting antidepressant research is to accurately assess the effects of the drug in a target audience. If you are testing a drug in a non-target audience and/or in a population of individuals with other secondary (and/or tertiary) major health conditions, it may skew the results. Therefore strict inclusion criteria is necessary to accurately understand a new drug in clinical trials.
  2. Reduce false signals: False signals are considered effects that are wrongfully purported as being associated with and/or derived from the antidepressant. False signals may be high when working with: populations that have numerous health conditions, those of old age, pregnant women, and/or those who don’t have a condition that the drug is attempting to treat. An example of a false signal could be someone with old age who reports a particular side effect associated with the drug that in actuality is stemming old age.

Who are the people with depression excluded? (Specifics)

Researchers determined that the people most likely to get excluded from antidepressant registration trials (ARTs) compared to those who were included in the STAR*D study.  The four biggest exclusion factors included: general medical conditions, women not taking birth control, those with mild depression, and the elderly.  The total percentage of individuals excluded from antidepressant trials is thought to be around 82%.

  • General medical conditions (20%): It is estimated that approximately 1/5 people with depression are excluded from antidepressant registration due to the fact that they have a significant and/or unstable medical condition. Should pharmaceutical companies allow individuals with medical conditions to participate in trials, it muddies the system – making it tougher to determine whether something was caused by the new drug or the medical condition.  Further, general medical conditions may increase likelihood of dropping out and new drugs may exacerbate these symptoms and/or compromise safety of these individuals.
  • Elderly 65+ (14%): It was suggested that just under 1/7 people with depression who are older than 65 years of age would be declined from participating in a clinical trial. This is for a variety of reasons including increased safety risks of testing a new compound and potential exacerbation of certain side effects in the elderly.  In addition, many effects resulting from old age may be difficult to distinguish from effects of the antidepressant in trial.
  • Females not taking birth control (21%): Another 1/5 individuals with depression that were included in STAR*D research would not be included in antidepressant clinical trials due to the fact that they aren’t taking birth control. Not taking birth control increases likelihood of having a baby, and it is well-known that pregnancy and unestablished drugs don’t mix; they may cause birth defects.  Moreover, pregnancy causes a variety of neurophysiological changes that may create false signals.  Many women who get pregnant would be at increased risk for dropping out of the trials as well.
  • Milder depression (15%): There are generally specific “cutoff” markers in regards to the severity of your depression. Someone with mild depressive symptoms may be excluded from the study if severe depression is required to participate.  It is estimated that over 1/7 individuals that participated in the STAR*D study would not be eligible for pharmaceutical clinical trials due to the fact that their depression lacks in severity.

Study (2015): Antidepressant Trials Exclude those with Depression

To determine how inclusion criteria influences participant selection in antidepressant registration trials, researchers assessed over 4,000 individuals from the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) study.  The STAR*D study is considered the longest and largest study of depression ever published.  In the STAR*D study, it was noted that inclusion criteria was considered “minimal.”

Results indicated that over 82% of individuals within the STAR*D study would not fit inclusion criteria for antidepressant registration trials.  Statistically, it was noted that 14% of all individuals would be excluded from antidepressant trials solely on the factor of age; this is due to the fact that individuals over the age of 65 are often excluded.  Further, an additional 15% of individuals would not meet inclusion criteria due to the fact that their depression wasn’t considered to be of sufficient severity.

There appears to be a cutoff marker in which those with severe depression are included in the research, yet those who have milder forms of depression are excluded.  It is estimated that over 20% of STAR*D participants would be ineligible to participate in standard antidepressant trials due to the fact that they have a “clinically significant” or “unstable” general medical condition.  In addition, an estimated 21% of all females aren’t able to participate in research due to the fact that they were not using birth control; this increases the chance of pregnancy which leads to increases in number of research dropouts.

It was suggested that antidepressant registration trials use very strict inclusion criteria to the extent that researchers estimate that approximately 90% of participants in the STAR*D study would be excluded.  It was also theorized that many individuals with depression may sign up for antidepressant registration trials, and even if they are accepted to participate, many may decline the offer to participate as a result of changes in the status of their mood.

  • Source: http://www.ncbi.nlm.nih.gov/pubmed/26164052

Implications of this research…

There are many implications from the newly published study suggesting that 82% of individuals with depression are likely excluded from antidepressant registration trials.  The exclusion rate indicates that certain antidepressants may be ineffective for a more diverse sample and other antidepressants deemed ineffective in trials may have legitimate efficacy.  Moreover, it appears that the pharmaceutical companies are wasting efforts in terms of time and financial resources as a result of their inclusion criteria.

  • Questionable antidepressants: The fact that many individuals with depression are excluded from antidepressant registration trials, it means that certain antidepressants may have been found effective in only a restrictive subset of the population with depression.  This means that there could potentially be drugs on the market that may only be effective in the highly-specified demographic of the antidepressant registration trials.  Meaning that if the inclusion criteria for the trials were expanded to include more people, certain already-approved drugs may have never been approved.  (An example: Paxil’s efficacy is now under question as a result of unpublished data).
  • Unnecessary drug failures: Although certain antidepressants may have been approved that cater to a specific subset of the depressed populace, others may have failed to meet clinical trial endpoints as a result of a restricted participant sample.  By including the estimated 82% of individuals (that engaged in the STAR*D study) in legitimate antidepressant registration trials, certain drugs that were discontinued may have been therapeutically effective.
  • Pharmaceutical companies: Authors believe that this research may provide insight to pharmaceutical developers in regards to how their inclusion criteria may alter ART (antidepressant registration trial) enrollment.  Knowing who is most likely to end up in a clinical trial allows pharmaceutical companies to tailor their recruitment efforts and finances by targeting only the individuals that are most likely to be included.  In addition, it may help certain companies make more accurate estimates of study timelines rather than creating overly-ambitious, short timelines that often skew trial outcomes.
    • Time: Having the data about individuals that are most likely to get excluded from trials can save pharmaceutical companies a lot of time and effort.  They spend a significant amount of time designing their trials, and then more time with recruitment.  Generally, the design and recruitment take more time than expected, and when companies try to rush the process, the results may be unsatisfactory and/or altered.
    • Money: Reviewing inclusion criteria can not only save pharmaceutical companies time, but it can save them a lot of money.  Drug developers often lack the data to determine how inclusion criteria affects the pool of potentially eligible individuals for their trials.  With more research like this study, they’ll be able to factor in the impact of certain criteria when designing a new trial and planning the estimated timeline of completion.
    • Recruitment: Another element that is critical to a an antidepressant registration trial is recruitment.  Since many pharmaceutical companies do not accurately know the effort necessary for optimal recruitment, the process ends up taking longer and requiring more money than expected.  This can mean drugs are delayed (potentially by months or years) in making their way to market.  In some cases, poor recruitment even leads to discontinued drug development.

Final thoughts: Antidepressant and drug trial designs need to improve

Most medical professionals tout the benefits of antidepressants, but some critics question whether antidepressants really work.  With the release of this research, we now know that antidepressants may be considered therapeutic for a subset of the population with depression, but not all individuals.  An estimated 82% of those with depression aren’t allowed to participate in clinical trials, potentially tainting the suggested real-world application of new drugs.

Of the 18% that are permitted to participate in trials, it is thought that many aren’t actually selected to participate.  Decline in participation further narrows among this 18% when considering the fact that those selected to participate often decline as a result of mood changes, remission, and/or a worsening of depression.  This means that less than 10% of those with depression likely end up participating in the study.

Study authors noted that the greater the percentage of individuals with depression excluded from trial participation, the more questionable the efficacy of antidepressants in a generalized population and/or under standard clinical care.  This may be why doctors often overstate the efficacy and benefits associated with antidepressant treatment among the general population, despite the fact that the clinical trial population is anything but “general;” this is another big problem in psychiatry.  It is hoped that this study can provide pharmaceutical developers with information to improve upon their existing antidepressant trial methodologies.

It is my hope that within the next several decades, that the clinical trial process (for all drugs) undergoes radical transformation.  This transformation should involve medication development for a subset of depressed individuals based on specific biomarkers (both genetic and neurophysiological), rather than (often) subjectively interpreted diagnostic criteria for depression.  Depression is currently measured by rating scales and evaluation protocols that fail to differentiate one specific type of depressive footprint from another.

This is a problem in that drugs are being designed and approved to universally treat depression rather than target each depressive footprint individually, which is likely necessary for real-world efficacy.  In addition, it is unclear as to whether those with milder forms of depression derive as much benefit from current-market pharmaceuticals as individuals with mild depression are often excluded from the trials.  Of the drugs that survive clinical trials and make it to market, many people fail to get relief.

Although services like GeneSight may increase likelihood of finding an (approved) antidepressant that provides significant symptomatic reduction, clearly many drugs are developed with suboptimal designs.  They are highly-restrictive in regards to participants, yet are overly generalized in that depression isn’t evaluated based on specific biomarkers.  All of that said, current antidepressant trials can be improved in terms of speed, accuracy, and cost with this new information.

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