I hope in time we can help millions of people around the world conduct their very own “clinical trial”. I believe that lives depend on it.
Let’s first discuss what traditional Clinical Trials do well – examination of any noticeable effect (positive or negative) when introducing a single variable (e.g. a drug or a device) to an experimental group and comparing the outcome to a corresponding control group.
Leaving aside increasing concerns about the validity of Clinical Trial research presented by Big Pharma Show 997: Big Pharma and Health Care. and the difficulty that regulatory agencies have in keeping up with the research put in front of them regardless of quality, measuring for a single variable falls far short of finding out what works and what doesn’t work for a person in their own life.
If you have a condition(s) you are trying to measure and control, or even understand what exacerbates that condition for you as an individual, Clinical Trial research and its measurement of a single variable change applied to several thousand people is useless for your needs. A single new drug is unlikely to be a silver bullet that returns you to your former self. On the contrary, it can set off what turns into a series of unintended consequences that have to be continually compensated for with more interventions.
To understand what works for you, carry out what we call an “ABA test” on yourself. (Researchers have various names for similar types of trial, such as “within subjects design” or “quasi-experimental design”. Let’s use ABA for its simplicity and descriptiveness). The concept is simple; you watch a comprehensive set of health markers in period “A”, then introduce an intervention (a drug, diet, new health regimen or anything) called period “B”. Then, come off intervention “B” returning to your circumstances during period “A”. Hence A-B-A.
Having done that you can be proud that you have a richer data set for yourself than Pharma gets from each of its expensive Clinical Trial subjects! Why? Because Clinical Trials just measure subjects at the start, during, and at the end of the intervention itself. They rarely measure you for a period either before or after the intervention. This can cause many data errors, such as erroneously attributing as a side-effect what was a pre-existing condition. By doing a full ABA test you will have a good view of how an intervention affects your life.
There are real world examples of this testing being successfully done. For example the Life Raft group of GIST (gastrointestinal stromal tumor) cancer sufferers Life Raft Group. , who create their own placebo by taking detailed notes before, during and after an intervention so that post-outcomes and side effects can be parsed out from pre-existing conditions and circumstances.
For those who want to read more about how the Life Raft Group works, see the online PDF “e-Patients – how they can help us heal healthcare” Patients White Paper. and read from P64, Chapter 5: e-Patients as Medical Researchers.
Here are highlighted sentences…
“One of the great benefits of patient-initiated research is its speed…bypassing the “lethal time-lag” that clinical data usually takes (several years).
“Publishing own research studies…. developed a methodology by which patients, could, in effect, serve as their own control group.
“To account for no control group, participants ranked their side effects from the quarter prior to starting….. this allowed some side effects to be actually be documented as pre-existing conditions…. and that actual side effects got better over time…
“Has provided a unique kind of data bank that cannot be replicated anywhere else, not even in patient trials”
To undertake a meaningful ABA test, you need to track changes in data that cover a range of areas of your life:
- medical data (e.g. drugs, labs and diagnoses)
- then, ideally compare results to genetic markers, as these tests become more available to consumers as comprehensive and useful.
Undertaking meaningful ABA tests can be a lot to do, but the interplay of all these factors are likely to increase the significant potential of discovering correlations or precursors for your condition(s).
I have met many people with chronic conditions who assiduously do this using spreadsheets in which they collect all kinds of data up to multiple times a day. The problem is finding time to enter the data and then the difficulty of trying to spot correlations in what soon becomes a complex spreadsheet of disparate data points.
For a long time one of our missions as a company has been to help people ABA test and create their own experiment & control for their very own Clinical Trial of N=1. The essence of a “Lifetime Health Diary” should be twofold:
First to enable somebody to measure various interventions over time. No more spreadsheets!
Secondly, the key output of having the system receive your data is then being able to visualize it in a single, simple page. A page where you can correlate all factors against each other by any length of time, e.g. days, weeks, months or even many years. This makes it far easier to spot potential causation or correlations that otherwise be missed in traditional data tracking methodologies. A popular mantra for us has always been, “Find out what works, and what doesn’t!
If you have a condition hard to fathom or control, isn’t it time to find out what works for you, and what doesn’t? We hope to help millions of people do exactly this.