2.5 - Conduct2.5 - Conduct
Although it is vital to enroll enough subjects to answer the study questions adequately, recruitment must also follow ethical norms. Coercion should be avoided. For this reason, any financial compensation for the subject's time and travel will reflect actual expenses or small amounts that would not entice a person to enroll in the study for financial gain; study personnel other the primary investigator or the patient's doctor may be designated to ask for informed consent.
During the course of a comparative trial, evidence may become available that one treatment is superior. Interim statistical analyses may be incorporated into the study design to provide periodic investigations of treatment superiority prior to study completion without sacrificing the statistical integrity of the trial. (discussed later in this course). Should patients receiving an inferior treatment continue in this manner? If there is evidence that a particular type of patient is unlikely to respond to therapy, should entrance criteria be modified? Is the adverse experience profile markedly worse for one therapy? Investigators are required to report such circumstances to their IRB.
Most multi-center clinical trials involve an independent board of scientists to monitor the trial results and render decisions as to whether the trial should continue or be modified in some manner. Safety monitoring is required. These committees have various names, such as Data and Safety Monitoring Board, External Advisory Committee, etc.
Early Termination for other than scientific or safety reasons
Related to planning, studies should only be conducted if resources are adequate to complete the study. Early termination for reasons other than science or safety reflect a lack of ethical concern. Subjects agreed to participate so an important question could be answered. There should be an answer.
Data falsification must not be tolerated in any manner. Central statistical monitoring and other procedures may help detect potential fraud. See George and Buyse, (2015) Data Fraud in Clinical Trials