Specific rules for medical devices
New rules apply from 26 May 2021 - but some are delayed (preliminary) until 15 July 2021. Updates regarding the rules from 15 July will be published early autumn.
The principles for data management and analysis presented in the section above also apply for studies involving medical devices. Specific for clinical investigations of medical devices is that the standard for good clinical practice, ISO 14155:2020, shall apply. This means, among other things, that there are a number of statistical considerations to be described in the clinical investigation plan, see Annex A of the standard. For clinical investigations of medical devices, the question must also be based on the information provided by the risk management process and the clinical evaluation with regard to the clinical data that need to be produced in order to prove the safety and performance of the product. Read more about this in the Step Idea. Any deviations from the investigation plan regarding the statistical aspects of the study must be evaluated with regard to whether they are to be regarded as significant changes that must be approved by the Ethical Review Authority and the Swedish Medical Products Agency before they can be implemented.
Confirmatory studies of the safety and performance of medical devices are often based on the product being compared with an existing method or therapy, and in this way it can be shown that the device works equally well or better. This type of study should be randomised and blinded, to avoid bias. For studies involving medical devices, it can be difficult to design the study based on these criteria, for example because it may be impossible to develop an identical placebo or comparison device, and it may also be unsuitable to use a prospective control group for various reasons. Some of the differing ways of handling the challenges involved in medical device studies are presented below.
Medical device with a therapeutic purpose
Control group: If it is possible to use a prospective control group that is treated with a standard therapy, then this is to be preferred. Otherwise, it may be possible to use a historical control, where you know that a certain therapy or lack of therapy has a certain outcome, which can then be compared with the outcome of the study.
Randomising and blinding: If you use a historical control, then you do of course lose the opportunity of randomising and blinding the therapy. But if you use a prospective control group, it can still be difficult to keep patients and the physicians providing treatment blinded, if it has not been possible to develop a placebo therapy. In this case, an independent evaluating physician may conduct a follow-up evaluation of the therapy result in a blinded way (that is to say, without knowing what therapy the patient has been randomised to).
Medical device with a diagnostic purpose
Control group: Often there is a standard method for making a diagnosis in the area. This method has a known ability to make a specific diagnosis (known as sensitivity and specificity, which can be used for comparison with the results of the trial device.
Randomising and blinding: In some cases, patients in diagnostic studies can be their own control, that is to say that they are subjected to two types of investigation, where one is an investigation using the standard method, and one is an investigation using the trial device. To increase safety for the study participant, the patient is diagnosed using the standard method. An independent physician can, however, make a diagnosis using the standard method and the trial device in a blinded and randomised way, to see whether the diagnoses generated by each method correspond.
As for all clinical studies, it is recomended that the study design, data management and analysis are discussed with a statistician as necessary. ICH E9 Statistical Principles for Clinical Trials is a document primarily produced for clinical medicine studies, but the statistical principles can be applied for medical device studies as well.
ECRIN has produced a database of outcome measurements that have been used in studies of different types of medical devices. Here you can get tips of how others have chosen to measure the effect and performance of medical devices. Harmonisation of outcome measurements can also facilitate future meta-analyses and summaries of the evidence situation for devices that have been evaluated in the same way.