In clinical trials, why is the size of the treatment (experimental) group often greater than that of the placebo or control group?

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I’m confused why at times this difference can even be an order of magnitude or greater. (I.e 1000 patients receiving the new treatment vs 100 receiving nothing or a placebo.) What am I missing?

Wouldn’t this just lend a more favorable outcome for the drug being studied and help a manufacturer meet the statistical criteria for clinical significance? This, if true, seems unethical. Why not just make them as equal as possible from a representative sample?

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Anonymous 0 Comments

There is no reason that having more people would lead to a more favorable result. More people just leads to a more accurate result (smaller variation). So yeah more people does not mean your result will be better.

But the big reason this is done is because the “treatment” is often not just one thing. Typically they are testing many different treatments at once. In the example you gave it might be something like:

* 100 got a placebo

* 100 got a 5mg dose once a day

* 100 got a 20 mg does once a day

* 100 got a 5mg dose twice a day

* 100 got a 10mg dose twice a day

* and on and on…

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