Clinical data derived from the clinical investigation, post-market activities, and literature must be evaluated.
A well-defined appraisal plan is important as per MEDDEV 2.7.1 Rev.4
Clinical Appraisal
Plan and record appraisal of favorable and unfavorable clinical data in terms of its suitability, scientific validity and data contribution
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Conduct of the Appraisal
The evaluators should:
- Stick to the pre-determined appraisal plan and its criteria throughout the appraisal of each clinical data set;
- Review all of the contents, the methodology used, the reporting of results, the validity of conclusions drawn from the investigation or report, and evaluate any limitations and potential sources of error in the data using the full text of publications and other documents (not abstracts or summaries);
How to Evaluate Methodological Quality and Scientific Validity
The evaluators should look at the methods used to generate and collect clinical data and determine the level of evidence based on the appraisal plan’s criteria. Clinical data from the clinical trial, as well as literature searches and post-market surveillance activities, should all be included. It is necessary to determine the level of methodological quality and scientific validity.
Examples of aspects that can be taken into consideration for evaluating the methodological quality and the scientific validity
- Study design of pre-market and post-market clinical investigations
- Additional aspects for appraisal of the quality of clinical investigations
- Information derived from vigilance data, device registry data, case series, patient dossiers, and other use data
- Data Processing and Statistics
- Quality Assurance
- Report Quality
- Conditions under which a study is considered to lack scientific validity for demonstration of adequate clinical performance and/or clinical safety
How to Determine the Relevance of a Data Set for the Clinical Evaluation
The data set is determined as pivotal data and other data based on data relevancy.
a. Pivotal data
- Pivotal data must have the data quality required to demonstrate adequate clinical performance and clinical safety of the device under evaluation;
- Generated using the device under evaluation or an equivalent device used for the same purpose.
b. Other data
- Data that are not pivotal should generally be appraised and weighted for their contribution for purposes such as:
- Identifying and defining current knowledge and state-of-the-art in the relevant medical field in order to establish acceptability criteria for assessing the risk-benefit profile and specific side-effects of the device under consideration;
- Individual case reports should be used to identify new and previously unknown hazards associated with the device (including hazards due to substances and technologies).
- Demonstrating the validity of the criteria used to demonstrate equivalence (if equivalence is claimed);
- Demonstrating the validity of surrogate endpoints (if surrogate endpoints are used).
- Contributing to the design of pivotal studies.
When determining the relevance of each data set, a variety of factors should be considered. The table below illustrates some of the factors that could be considered when determining whether or not data is relevant to the clinical evaluation.
Listen, What experts say!
Clinical data, when generated through a well-designed and monitored randomized controlled clinical investigation conducted with the device under evaluation in its intended purpose, with patients and users who are representative of the target population, should typically receive the highest weighting.
Note: It is recognized that randomized clinical trials are not always feasible or appropriate and that alternative study designs can provide relevant clinical data with adequate weighting.
The reasons for rejecting evidence should be documented by the evaluators.
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