4. General principles — Introduction and Pillar 1 (Valid Clinical Association)

Source: MDCG 2020-1 (March 2020), pages 9-11, covering Section 4 opener + 4.1 Introduction + 4.2 Determination of the valid clinical association / scientific validity

4. General principles of the MDSW Clinical Evaluation (MDR) / Performance Evaluation (IVDR) process

4.1 Introduction

CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR) is an ongoing process, conducted throughout the life cycle of a MDSW. It is a structured, transparent, iterative and continuous process which is part of the quality management system for a device. Software that qualifies as a MD or an IVD is subject to the same general CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR) principles, laid down in the applicable guidelines and regulatory documents, as other MDs/ IVDs, such as:

• Establishing and maintaining a CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR) plan and criteria applied to generate the necessary CLINICAL EVIDENCE based on the characteristics of the device;

• Identification of the relevant data pertaining to performance and/ or safety of the device and any remaining unaddressed issues or gaps in the data;

• Appraisal of the relevant data in terms of quality and its contribution to the CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR);

• Analysis of the available data and its relevance with regard to demonstrating conformity with the relevant General Safety and Performance Requirements (GSPRs);

• Documenting the relevant data, their assessment and the CLINICAL EVIDENCE derived therefrom, in the CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR) report;

• Updating the CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR) and its documentation throughout the life cycle of the MDSW concerned with data obtained from implementation of the manufacturer's Post Market Clinical Follow-up / Post Market Performance Follow-up (PMCF /PMPF) plan.

These methodological principles are depicted in Figure 1.

Figure 1 — Overview of the stages of the CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR)

A cyclical process diagram centred on a grey diamond labelled Clinical Evaluation (MDR) / Performance Evaluation (IVDR). Four stages surround the diamond in a clockwise loop, connected by arrows:

• Planning (top)
• Data (right) — containing three bullets:
  • Technical Performance (MDR) / Analytical Performance (IVDR)
  • Valid Clinical Association (MDR) / Scientific Validity (IVDR)
  • Clinical Performance
• Appraisal (bottom-right)
• Analysis (bottom-left)
• Documentation (left) — containing two bullets:
  • Clinical Evaluation Report (MDR)
  • Performance Evaluation Report (IVDR)

Arrows flow Planning → Data → Appraisal → Analysis → Documentation → back to Planning, illustrating the iterative nature of the evaluation process.

The requirements for CLINICAL EVALUATION and PERFORMANCE EVALUATION are outlined in Article 61 of the MDR (including Annex XIV) and Article 56 of the IVDR (including Annex XIII), respectively.

While the definition of CLINICAL EVALUATION in the MDR and PERFORMANCE EVALUATION in the IVDR are not identical (see section 0), there is a shared expectation for providing sufficient CLINICAL EVIDENCE to demonstrate conformity with relevant GSPRs under the normal conditions of the device's intended use. CLINICAL EVIDENCE should be sufficient and appropriate in view of the characteristics of the device, clinical risks and its intended purpose. The level of CLINICAL EVIDENCE necessary should be specified and justified by the manufacturer.

Three key components should be taken into account when compiling CLINICAL EVIDENCE for every MDSW (Figure 1), and each is described below in further detail.

VALID CLINICAL ASSOCIATION / SCIENTIFIC VALIDITY is understood as the extent to which, the MDSW's output (e.g. concept, conclusion, calculations) based on the inputs and algorithms selected, is associated with the targeted physiological state or clinical condition. This association should be well founded or clinically accepted (e.g. existence of a scientific framework or sufficient level of evidence as further elaborated in section 4.2 of this document). The VALID CLINICAL ASSOCIATION / SCIENTIFIC VALIDITY of a MDSW should demonstrate that it corresponds to the clinical situation, condition, indication or parameter defined in the intended purpose of the MDSW.

NOTE: The VALID CLINICAL ASSOCIATION / SCIENTIFIC VALIDITY seeks to establish that there are sound scientific principles underpinning the use of the MDSW in question. The information provided for the establishment of the VALID CLINICAL ASSOCIATION / SCIENTIFIC VALIDITY should put forward the case that the MDSW has an association with a clinical condition or physiological state. This association may not always be readily established. Thus, the CLINICAL PERFORMANCE can serve as an additional input to the VALID CLINICAL ASSOCIATION/ SCIENTIFIC VALIDITY from a clinical perspective for the specific intended purpose (see Annex I).

Example: MDSW that detects heart arrhythmia by analysing auscultation sound obtained by a digital stethoscope requires demonstrating VALID CLINICAL ASSOCIATION of the association between abnormal cardiac sounds and heart arrhythmia.

Evidence supporting VALID CLINICAL ASSOCIATION / SCIENTIFIC VALIDITY can be generated e.g. through literature research, professional guidelines, proof of concept studies, or manufacturer's own clinical investigations/clinical performance studies.

Validation of the TECHNICAL PERFORMANCE / ANALYTICAL PERFORMANCE is the demonstration of the MDSW's ability to accurately, reliably and precisely generate the intended output, from the input data.

Evidence supporting TECHNICAL PERFORMANCE / ANALYTICAL PERFORMANCE can be generated through verification and validation activities, e.g. unit-level, integration, and system testing or by generating new evidence through use of curated databases, curated registries, reference databases or use of previously collected patient data.

Validation of the CLINICAL PERFORMANCE is the demonstration of a MDSW's ability to yield clinically relevant output in accordance with the intended purpose. The clinical relevance of a MDSW's output is a positive impact

• on the health of an individual expressed in terms of measurable, patient-relevant clinical outcome(s), including outcome(s) related to diagnosis, prediction of risk, prediction of treatment response(s), or

• related to its function, such as that of screening, monitoring, diagnosis or aid to diagnosis of patients, or

• on patient management or public health.

Evidence supporting CLINICAL PERFORMANCE can be generated by testing the MDSW under evaluation, or an equivalent device, in the target population and for the intended use. The applied methodology should be appropriate in light of the device characteristics and intended purpose and may include pre-clinical testing, a clinical investigation or a clinical performance study.

Specifically, for MDSW not claiming CLINICAL BENEFITS that can be specified through measurable, patient-relevant clinical outcome(s), clinically relevant outputs are achieved through demonstrated predictable and reliable use and USABILITY (please refer to section 4.2 of this document).

In addition, CLINICAL EVALUATION or PERFORMANCE EVALUATION of MDSW must consider the benefit-risk ratio in light of the STATE-OF-THE-ART related to practice of medicine for diagnosis, treatment or patient management. It is further expected that the assessment of MDSW considers all components of the CLINICAL EVALUATION (MDR) / PERFORMANCE EVALUATION (IVDR) (see Figure 1 and Annex 0).

The three components described above do not represent a distinct stepwise approach but rather portray a methodological principle for the generation of CLINICAL EVIDENCE.

To determine and justify the level of CLINICAL EVIDENCE, both amount and quality of supporting data should be evaluated. This assessment may be guided by the following non-exhaustive questions:

Sufficient amount

• Does the data support the intended use, indications, target groups, clinical claims and contraindications?
• Have the clinical risks and analytical performance/ clinical performance been investigated?
• Have relevant MDSW's characteristics, such as the data input and output, the applied algorithms or type of interconnection been considered when generating the data to support the performance of the device?
• What is the grade of innovation/ history on the market (how big is the body of scientific evidence)?
• Other, as applicable.

Sufficient quality

• Were the type and the design of the study/ test appropriate to meet the research objectives?
• Was the data set appropriate and actual (state of the art)?
• Was the statistical approach appropriate to reach a valid conclusion?
• Were all ethical, legal and regulatory considerations/ requirements taken into account?
• Is there any conflict of interest?

• Other, as applicable.

4.2 Determination of the valid clinical association / scientific validity

In the first step, the manufacturer should verify the association between the output of the MDSW (based on the inputs and algorithms selected) and the targeted physiological/ clinical condition, clinical situation or clinical parameter, as defined in the intended purpose of the MDSW. MDSW may include a multitude of clinical features governed by its intended purpose which require individual assessment.

This association should be clinically accepted or well founded, which means accepted by the broad medical community and/or described in scientific (peer-reviewed) literature.

VALID CLINICAL ASSOCIATION/ SCIENTIFIC VALIDITY can be demonstrated through the use of existing CLINICAL PERFORMANCE DATA while taking into account the generally acknowledged STATE-OF-THE-ART.

VALID CLINICAL ASSOCIATION / SCIENTIFIC VALIDITY may further be demonstrated by the creation of new CLINICAL PERFORMANCE DATA in the cases where existing data is not sufficient. For example, as a result of a gap analysis, the manufacturer could conclude that additional data may be required.

Examples of existing data (in no particular order)

• Technical standards
• Professional medical society guidelines
• Systematic scientific literature review
• CLINICAL INVESTIGATIONS/ CLINICAL PERFORMANCE STUDIES
• Published CLINICAL DATA (e.g. Summary of Safety and Clinical Performance (SSCP) / Summary of Safety and Performance (SSP), Registries and databases from authorities)

Examples of generating new evidence (in no particular order)

• Secondary data analysis (Analysis of real-world data)
• Perform CLINICAL INVESTIGATION / CLINICAL PERFORMANCE STUDY