Bias in surgical research.
OBJECTIVE
The aim is to discuss the various forms of bias in surgical research, including how it impacts validity and how to recognize and avoid it.


METHODS
The various factors affecting bias in surgical research's design, execution, and reporting were explored. The impact of these factors on internal and external validity in both observational and randomized controlled trials was examined, and recommendations were made for ameliorating the various biases.


RESULTS
Identifying bias when interpreting a trial enables surgeons to assess surgical research's internal and external validity. Avoiding bias and/or using methods that minimize bias helps surgeons design and conduct trials with enhanced validity, which can be reliably translated into practice. To accomplish this, surgeons need to be cognizant of susceptibility bias, the applicability of surrogate endpoints, and the use of inappropriate comparators in trial design. They must also be aware of detection, ascertainment, performance and transfer bias in trial execution, and of citation bias in trial reporting.


CONCLUSIONS
Familiarity with clinical trials' potential biases helps surgeons assess the believability and applicability of research results. Though these biases may sometimes be ameliorated by randomization, blinding, and intervention standardization, these remedies can present distinctive problems to surgical research. This poses a unique need and opportunity for innovation in surgical research design and evaluation. It necessitates that further research be done on methods to improve not only the internal and external validity of surgical trials but also their assessment.
Paradis
Carmen
C
Bioethics Department, Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA. paradic@ccf.org
D015982:Bias; D035843:Biomedical Research / Q000592:standards* / Q000706:statistics & numerical data; D002986:Clinical Trials as Topic / Q000592:standards* / Q000639:trends; D013502:General Surgery / Q000592:standards* / Q000639:trends; D006801:Humans; D018579:Patient Selection; D015203:Reproducibility of Results; D012107:Research Design / Q000592:standards / Q000706:statistics & numerical data; D017749:Total Quality Management