Bias in performing clinical studies

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Bias in performing clinical studies

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A clinical trial is conducted to determine the efficacy of ginkgo biloba in the treatment of Parkinson disease. A change in the Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS) score is used as the primary endpoint for the study. While the trial is being conducted, the patients' demographics and their allocated treatment groups are disclosed to the investigators, but not to the participants or data analysts. The study concludes there is a significant decrease in MDS-UPDRS scores in patients treated with ginkgo biloba. Which of the following is most likely to have affected the validity of this study?  


Clinical studies are a type of scientific research study performed on human volunteers, or participants, to help determine the safety and effectiveness of a therapeutic intervention, such as a new medication, vaccine, device, or procedure.

Now, systematic errors due to inaccuracy in clinical studies might result in bias, which refers to an incorrect conclusion about the effects of the therapeutic intervention.

This conclusion may result in an inaccurate representation of the relationship between an exposure and an outcome, which means that the clinical study lacks internal validity.

In addition, these results can’t be applied to the general population, which means that they lack external validity.

There are different types of biases that can occur while performing clinical studies, including the recall bias, measurement bias, Hawthorne effect, procedure bias and observer- expectancy bias.

Starting with recall bias, which is common in case control studies. These are a type of retrospective clinical study that compares the history of two groups of people.

One group includes those that have a certain outcome, called cases, and the other group includes those that don’t have a certain outcome, called controls; to see if they’ve been exposed to different things that may have led to or protected from the outcome.

Now, recall bias means there can be a difference in the accuracy or completeness of the data retrieved between the cases versus the controls, and this could lead to an over- or underestimation of the exposure.

One reason for recall bias is that individuals in the case group remember exposures differently than those that are in the control group.

For example, individuals with skin cancer might be more likely to recall using a tanning bed multiple times, since they know that tanning beds are a risk factor for skin cancer.

On the other hand, individuals without skin cancer might recall using a tanning bed fewer times than they actually did, simply because each visit blurs into the next and can be forgotten.

In this example, the case group might be over reporting their tanning bed use, whereas the control group might be underreporting their tanning bed use, which will make it seem like tanning beds are more harmful than they actually are.

To help reduce recall bias, researchers often use written records, like medical records, to verify the information collected from individual interviews, or they can study exposures that happened in the recent past.

It’s also important to distinguish recall bias from poor recall, which is when people have trouble remembering events because a long time has passed between the exposure and the outcome.


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