Research tips:

Drug companies present information about medications based on clinical trials. When drug companies present this information, many of the assumptions and details of the study are omitted and you are only presented with a result. Based upon this result you are expected to make a sound judgement on the best medication for you.

This section gives you some of the knowledge and the skills that you need to investigate the study results and research the medications for yourself. This section is based on the things I have learnt from my career as a scientist over the last 9 years, and as a consumer of anti-psychotic and anti-depressant medications for 5 years.

Assumptions and Conclusions:

The first, and probably most important point about clinical trials is that assumptions and conclusions are made about the entire population based on a very small sample size. Most trials involve perhaps 100 to 200 people and based on the information gathered from these 100 to 200 people blanket conclusions are drawn about how the drug will affect everybody who takes it. 100 to 200 people in a study doesn't sound like a lot, a trial of 10 000 perhaps maybe sounds a bit better. But even if the study did have 10 000 participants, conclusive statements about the whole population cannot be made. Regardless of the number of participants, the company cannot make accurate statements about the entire population because the company has not tested the entire population. The only accurate statement that can be made about the medication tested in a clinical study is that “in this study of 10 000 people the drug X had no side effects”. For a company to claim that there are no side effects from drug X, for anyone in the population, based on clinical trials is misleading, inaccurate and wrong.

Ok, I'm not trying to paint a picture of mad scientists in their labs plotting death and destruction, these are the conventions that are used for all biological experiments and trials. In biological sciences statistics are applied to the results of a small trial, to decide if the differences in the results are ‘significant' and can therefore be applied to the broader population. In most cases (other than human medication trials), when used responsibly and accurately, this technique is appropriate.

For example, one experiment that I conducted when working in Costa Rica investigated the development of leatherback seaturtle eggs. It was not possible for me (or anyone for that matter) to go and sample every nest of leatherback eggs on the planet, so I took a sample of 20 nests and based on those results I drew conclusions about all leatherback nests. However, at no point could I say that those results apply, absolutely, to all leatherback nests anywhere in the world. All I could say for sure was that the results I gathered applied to the 20 nests that I tested, because they were the only nests that I had gathered information from. I could only make suggestions about the rest of the population, like ‘based on the results gathered from 20 nests on a beach in Costa Rica it is likely that….' Or ‘ 16 of the 20 nests that I sampled had…' I could not state that ‘in all leatherback nests….' because I had not measured every leatherback nest on the planet.

Making assumptions about the whole population of leatherback turtles, based on my sample of 20, is appropriate, and being wrong isn't going to have catastrophic consequences. But, the consequences of making assumptions about the human population based on a small sample of subjects, could be, and often are, catastrophic. To state that a company has shown that ‘this antipsychotic medication does not cause weight gain' is wrong and irresponsible. The company can only state that ‘in clinical trial X we demonstrated that 40 of the 50 subjects did not gain weight'. They have not tested the drug on everyone that is going to take it and cannot make conclusive statements on how it will effect you.

Clinical trial results are the best guide that we have but that is all they are, a guide based on a small sample of people.

The Lesson:

Read the side effects of your medications carefully. The side effects that are listed on the medication (or lack of side effects) are based on the clinical trials, therefore, they do not apply to everyone. Monitor your health closely and regularly. If you do experience, side effects, or changes in your health or wellbeing consult a medical professional. Even if the changes are not listed as side effects of the medication. The side effects of each medication will differ based on the individual that is taking them.

Background and experimental Conditions:

The next thing that is omitted from these results are the conditions under which the trial was conducted and the background of the patients.

The results from a trial of 50 single people that live on Huntington Beach in California, which was conducted in the middle of summer, after the patients had been on holidays for 2 weeks, are not going to apply to a single mother in her thirties, that works full time whilst raising two kids, who lives in Melbourne and hasn't had a holiday in 5 years. Lets be honest, they won't, and they don't.

Like my turtle experiment in Costa Rica , it was completed in a hatchery, under controlled conditions, on the west coast of Costa Rica . The results from these 20 nests in Costa Rica do not apply to 20 nests, on a beach, in Northern Queensland .

The backgrounds of the patients in the trial and the conditions of the trial need to be explained in detail. Each person is an individual with an individual set of circumstances, both physical and environmental, therefore the effects of the medications are also individual.

The company that made the first antipsychotic I was on, Respiridone, made the claim that taking Respiridone does not cause weight gain. I gained 27 kgs in 6 months whilst on Respiridone. When I changed medications to Zyprexa the weight gain stopped and, combined with a lot of exercise and hard work, I was able to lose most of the weight. Respiridone was sold as not causing weight gain, and in the clinical trials it probably didn't, but I wasn't in the clinical trials and my individual circumstances were different to those that were in the trial. Zyprexa was sold as causing weight gain, which it probably did in the clinical trials, but again, I wasn't in the trials and my individual circumstances were different to those in the clinical trials. To further emphasise this point, I know a guy who had the opposite experience. He gained a lot of weight on Zyprexa and lost it when he changed to Respiridone. Again, we are both individuals and both reacted differently to the medications.

The lesson:

Find the published results of the trials and try and obtain the backgrounds of the people that were in them. Also read the conditions under which the trials took place, where, when, for how long, what time of the year etc.

Definition of terms:

When a clinical trial is conducted the terms that are used in the experiment are defined. Weight gain is defined, side effect is defined and no side effect is defined. How these terms are defined determines the results of the clinical trial.

If I conduct an clinical trial and I define ‘weight gain' as gaining more than 20kgs and none of the patients in the trial gained more than 20kgs then, by definition, no one gained weight. Every person in the trial could have gained 19.5kgs, but, because ‘weight gain' was defined as gaining more than 20kgs, no one gained weight.

It is important to determine what the various terms in clinical trial mean and what thresholds have been set. Weight gain is not always weight gain. If I was to experiment on mice, weight gain in mice is not the same as ‘weight gain' in humans, or elephants or whales. ‘Weight gain' in mice could be 10 gms, ‘weight gain' in a human 10kgs and ‘weight gain' in an elephant 100 kgs.

This also applies to side effects. A side effect is not always a side effect, and when does this side effect become an adverse side effect, and what is defined as adverse. Where the threshold for adverse is set defines whether or not a side effect is adverse.

This also applies to the results, in the sense of the desired effects of the medication. How things like ‘significant reduction in psychotic symptoms' are defined, and how that is measured, determines the results of the experiment. The most extreme example of this is that in the USA a patient is deemed to be recovered from schizophrenia if they have stopped committing criminal activity.

Someone else's idea of a reduction in their psychotic symptoms could be radically different to yours, as could their definition of loss of motivation or lethargy. How this is measured is also key to the result. You need to find out how the significant reduction in psychotic symptoms was measured, did they ask the patients, or measure behaviour.

The lesson:

Find out how the terms are defined. In the trial what was defined as ‘weight gain' or ‘side effect'. Find out what was classed as reduction in symptoms, or lethargy, or loss of motivation and so on.

Then relate these definitions to your current situation.

Selling a product:

The drug companies that make and sell medications, make and sell medications. That is what they do, the product that they produce is the medication that you take. Keep this in mind at all times when sifting through the mountains of company information designed to help you make an informed choice about the most appropriate medication for you.

Drug companies sell medication, therefore, if more people take the medication they are selling, they will make more money.

If a company can do a clinical trial that demonstrates that the anti-depressant they sell doesn't cause weight gain, they will sell a lot more product. In fact, the first company that did this made billions, literally overnight.

The Lesson:

Try and find independent research about the medications that have been completed by universities or research institutions, rather than the drug company themselves. Experiments that have compared a range of medications (made by a range of companies) are also good because they are not focused on the merits of one specific medication or biased by a company.

Individuals, individuals and individuals:

Remember, you are an individual and your circumstances, your body and your life are unlike anyone else. So you need to find what is right for you. Experiments, trials and the experiences of others are a great guide and resource to draw off, but at the end of the day you are unique and need to find the right balance for your life.

Some good resources to find all of this info:

Google scholar is good place to start. If you enter the name of the medication is will point you in the right direction. But, make sure you use the tips above when looking at this info.

http://www.clinicalstudyresults.org is a web based resource that publishes the results of company experiments and trials. This site contains the results of clinical trials completed after October 1, 2002, for drugs approved for use in the USA .

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