Topic outline

Bias in Clinical Trials

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Performing a clinical trial is a very complex and challenging activity. Bias may come in at different levels before, during and after the trial. Therefore, it is important for researchers to be able to interpret the trial results and to be able to identify potential bias in the design, conduct and analysis of a trial which could invalidate the trial analysis and ultimately the validity of the clinical trial itself.

In research, bias occurs when systematic error is introduced into data sampling or hypothesis testing by selecting or encouraging one outcome or answer over others. Of note, bias is not always introduced intentionally. It can also be caused unintentionally: for example by calibration error or unknown confounding variables. Bias may affect the results of a clinical trial by causing a deviation between the observed effect and its true value: estimates of association can be systematically larger or smaller than the true association. Bias may also take the form of systematic favouritism in the way results are reported or in the way they are interpreted in the discussion and conclusion on clinical trial results.

Fraud and Misconduct in Biomedical Research and Clinical Development

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Validity of a Clinical Trial

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Interpretation of Clinical Trial Measurements and Results

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Reporting and Critical Review of Trial Results

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What are clinical trials results?

The results of a clinical study or trial are all the data and statistical analyses generated during that clinical trial or study. Results include the following elements: 

  • Description of trial population: the number of participants per treatment arm who started, completed, or dropped out of the trial.
  • Baseline data: data collected at the beginning of a clinical trial. These data include demographics such as age and gender, participant characteristics such as height, weight, performance status, blood pressure, etc., and trial-specific measures such as disease characteristics, previous treatment, etc.
  • Measures capturing the effect of the treatment on participants. For example, medicine activity in a Phase II trial, participant survival, changes in variables indicative of disease status and/or quality of life in Phase III and Phase IV trials

  • Adverse events experienced by the trial participants related or not to the tested treatment e.g. pain, nausea and other untoward effects.

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