Table 2.
Potential sources of bias in clinical trials
| Bias type | Definition and examples | Identifiable | Quantifiable |
| Academic bias | The investigators leading study are advocates for the intervention. | Y | Y |
| Ascertainment bias | Un-blinded study design in which the outcome evaluations are susceptible to unmasked observer detection bias. Open-label studies, such as imaging and device trials (without a sham) are susceptible to ascertainment bias | Y | Y/N |
| Comparison group bias | If incorrect control/sham group is chosen, the intervention may appear to be more, or less, effective | Y | N |
| Fraud bias | Intentional fraud (rare) | Y | Y |
| Funding availability bias | Focus of studies on questions more readily funded (commercial interest) | Y/N | Y/N |
| Hidden agenda bias | Study designed to demonstrate a prerequired answer. | Y/N | Y/N |
| Intervention bias | Effects of a learning curve when investigating a new technology | Y/N | Y/N |
| Measurement bias | Measurement influences the respondent’s behaviour and responses, reflecting ‘response shift’ and relatedly a Hawthorne effect. This becomes relevant if there is an interaction between the intervention and the measurement tool (eg, a training effect) | Y/N | Y/N |
| Observer bias | Patients allocated to treatment arm followed more intensely/more favourably | Y/N | Y/N |
| Publication bias | Positive results are more likely to get published | Y | Y/N |
| Regulation bias | Overly restrictive or permissive review boards confounding the path to first-patient in | Y/N | Y/N |
| Sample choice bias | Exclusion of minority groups (recruitment bias), older groups (age bias) and women (sex bias) | Y | Y/N |
| Selection bias | Exclusion of potentially eligible patients | Y | Y/N |
| Selective reporting bias | Selective reporting of positive results | Y | Y |
| Withdrawal bias | Handling missing data: Are the number of withdrawals and their reasons stated in the report? Are the number of withdrawals similar in each of the groups, or not? Is the overall number of withdrawals comparable to the number of patients that contribute to a difference in the primary outcome? | Y | Y/ |
| Wrong design bias | Incorrect study design to answer a question (eg, a randomised study rather than post-approval outcome research) | Y | Y/N |