Sunday, May 22, 2016

Placebo Effect and The Choice of Placebo

Recently, NPR had a discussion about the influence of Placebo effect on consumer product purchases.  While the concept of the placebo effect comes from clinical trials in medical contexts, the placebo effect also have impact in non-medical research fields. For example, just by telling the people it is a brand name product (even though it is not), it affects the results of using the product.

Placebo effect is also called the placebo response. It is a remarkable phenomenon in which a placebo -- a fake treatment, an inactive substance like sugar, distilled water, or saline solution -- can sometimes improve a patient's condition simply because the person has the expectation that it will be helpful. Expectation to plays a potent role in the placebo effect. The more a person believes they are going to benefit from a treatment, the more likely it is that they will experience a benefit.”

Placebos have to be identical in all respects to the active drug, except that the active drug is absent. This means for oral placebos that they are not distinguishable by color, size, shape, taste, or texture. For oral therapy there are several modes of application available: capsules, tablets, or liquids. Since many active drugs have a distinctive taste, the use of capsules is most often feasible.

Sometimes, it is not so easy to make the placebo that are not distinguishable from the active drug. For example, liquids containing therapeutic protein generate foam but the placebo using buffer solutions do not. The treatment can be differentiated by observing the foam by shaking the test products. In this case, the ideal placebo will contain also an inactive protein in low concentrations such as human albumin. Some clinicians are very clever in breaking the code; they not only shake or identify the drugs by taste and smell but even photometers were used to determine differences between active drug and placebo. For such reasons it is sometimes very difficult to guarantee blinding.

While majority of the placebos used in the clinical trials are true inactive substance (at least we think so), there are times that the placebos may not be true inactive substance. This is especially true in the clinical trials using the protein therapies, for example, the therapeutic proteins derived from human plasma.

Table below listed several randomized, placebo controlled clinical trials using the therapeutic proteins derived from human plasma. Various concentrations of albumin (also protein) were used as the placebo assuming that the low dose of albumin has no therapeutic effect.

Experimental Treatment
Choice of Placebo
Biological: 0.25% human albumin solution (Placebo)
Biological: Placebo solution: Human Albumin 0.25% - 4 mL/kg
Biological: Placebo solution: Human Albumin 0.25% - 2 mL/kg
2% human albumin administered by weekly SC infusions during the SC treatment period of the study
Albumin (Human) 20%, United States Pharmacopeia (USP)
Placebo will be supplied as 20% or 25% Albumin and diluted with glucose 5% to a final concentration of 0.1%

If the results of these clinical trials are positive (statistically significant), people will not question the use of albumin as the placebo. If the results of these clinical trials are negative (not statistically significant) or the placebo group perform much better than expected, people may question the adequacy of the use of albumin as the placebo. This happened in one of the clinical trials in relapse-remitting multiple sclerosis (RRMS).  

Prior to the clinical trial below, previous studies had shown that the benefit of IGIV in treating the RRMS. The expected response rate in placebo group is about 50%.

Randomized, Double-Blind, Placebo-Controlled Study to Compare the Effects of Different Dose Regimens of IGIV Chromatography (IGIV-C), 10% Treatment on Relapses in Patients With Relapsing Remitting Multiple Sclerosis
The study results were published in Fazekas et al (2009) “Intravenous immunoglobulin in relapsing-remitting multiple sclerosis: a dose-finding trial”. For the primary efficacy endpoint, after 1 year, the proportion of relapse-free patients did not differ statistically according to treatment (IVIG 0.2 g/kg: 57%; IVIG 0.4 g/kg: 60%; placebo: 68%). Surprisingly, the response rate in placebo group is much higher than expected and than what was assumed when the study was designed. This prompted the discussion of the potential therapeutic effect of albumin used as the placebo. The article by Hommes et alIVIG trials in MS. Is albumin a placebo?” argued that albumin may have properties that make it unsuitable as placebo.

Since using the albumin as the placebo may have therapeutic effects, something other than albumin (for example, saline with Polysorbate) may be an option as the placebo in clinical trials with these therapeutic proteins. Polysorbete is added to mimic the foam created by the therapeutic protein.  However, the blinding may still remain as a concern when saline is used as the placebo because of the difference in foaming. In clinical trials using the therapeutic proteins, we need to balance the risks of potential unblinding of using Saline as placebo versus potential placebo effect of using albumin as placebo. 

For blinded studies, we always assume that the blinding is maintained during the course of the study. However, this can be wrong in many trials where the investigators and/or patients can tell which treatment group the patients are on by the distinguishable features between the actual product and the placebo, by the different adverse event profiles, and others. It is important to assess the potential unblinding by asking the investigators or patients to guess the treatment assignments – a practice seems to be reasonable, but pretty much nobody wants to do. If the assessment indicates the potential unblinding or high percentages of guess-it-right, there is no easy way to mitigate the impact and make it difficult to interpret the results from the clinical trial.

After the study, it is a good practice to compare the results from placebo group back to the original assumptions. During the design stage of the clinical trial, we usually make assumptions about the response rate or mean/standard deviation in placebo group. After the study, it will be interesting to compare the actual results from the placebo group with the assumptions in the protocol sample size calculation section. I see the situations where the final results are way different from the assumptions in the protocol sample size calculation – in this case, we must have some further investigation what goes wrong and why this happens. 

1 comment:

Chih-Lin Chiang said...

A very insightful post. Thanks for your sharing.