Читать книгу Interventional Cardiology - Группа авторов - Страница 155

One needs a fair (unbiased) comparison between new treatment and control, and randomization is the key requirement in this regard. That is, each patient has an equal chance of being randomly assigned to new or standard treatment. Furthermore, an adequate method of handling random assignments is such that no one should be able to predict in advance what each next patient will be assigned to. Hence, randomization based on days of the week, or years of birth, should be definitely avoided. Thus, adequate randomization ensures there is no selection bias in deciding which patients get new or standard treatment. Such selection bias is a serious problem in any observational (non‐randomized) studies comparing treatments, making them notoriously unreliable in their conclusions.

As a consequence, randomization minimizes the possibility that treatment groups will significantly differ in baseline characteristics. However, the possibility for chance variation can never be completely eliminated, even in a randomized study design. To further guarantee that key baseline features will not influence the treatment effect, randomization can also be stratified, a common approach in large multicenter studies.

In addition, randomization helps to ensure that all other aspects of patient care, and also the evaluation of patient outcome, is identical in both treatment groups. In this respect it is often important to make the trial double blind, whereby neither patients nor those treating them and evaluating their response know which treatment each individual patient is receiving.

If a trial cannot be made double blind – a relevant issue in interventional cardiology trials unless sham procedure are not considered – one can nevertheless require blinded evaluation of outcome by people not aware of which treatment each patient is on.