Research and planning

Internal working document

This document is for internal use only. It contains analysis, gap identification, and response strategy for Item 3b of the BSI Clinical Review Round 1. It will not be included in the final response to BSI.

1. What BSI is asking

Item 3b says: "Please provide justification that sufficient data in quantity and quality has been analyzed in order to support the clinical benefit, safety, and performance of the device as compared to SotA in its intended use, including for all of the relevant patient populations and indications."

Where Item 3a asks us to identify and analyse all clinical data, Item 3b asks us to justify that the data is sufficient. This is a distinct regulatory obligation under:

• Annex XIV (2): The clinical evaluation shall be "thorough and objective" and its "depth and extent shall be proportionate and appropriate to the nature, classification, intended purpose and risks of the device."
• Article 61(1): The manufacturer shall "specify and justify the level of clinical evidence necessary."
• MDCG 2020-6 Appendix III: Hierarchy of clinical evidence types and considerations for sufficiency.

The word "sufficient" has three dimensions BSI will evaluate:

1. Quantity: Enough subjects, enough studies, enough statistical power
2. Quality: Study designs, methodological rigour, appraisal scores
3. Coverage: All clinical benefits, all indications, all relevant patient populations, all intended users, safety endpoints

2. Current state of the sufficiency argument in the CER

What the CER claims (R-TF-015-003)

Line 840: "The adequacy of the number of observations, gathered from over 800 patients across eight pivotal studies, is justified for both performance and safety. Regarding performance, the sample size was formally calculated to ensure sufficient statistical power to validate the primary performance endpoints, based on detecting an effect size exceeding the 80% performance goal..."

Line 873: "The current body of evidence is sufficient to demonstrate the conformity of Legit.Health Plus with the General Safety and Performance Requirements (GSPRs) of the MDR 2017/745."

Why BSI finds this insufficient

The CER makes a top-level sufficiency claim but does not provide the structured, granular justification BSI expects. Specifically:

1. No mapping from each clinical benefit → supporting studies → evidence adequacy
2. No mapping from each indication → coverage across studies → gaps identified
3. No patient population breakdown showing demographic representativeness
4. No explicit comparison of evidence strength vs SotA for each claim
5. The MDCG 2020-6 evidence hierarchy table in the CEP (lines 692–710) marks "No" for Rank 5 (equivalence data), Rank 7 (complaints/vigilance), and Rank 8 (PMS data) — despite claiming equivalence and having PMS data available. This directly contradicts the CER's own narrative.

3. Inventory of clinical evidence

3.1. Study portfolio

Study	Design	N	Population	Indications	Key domains	User group
AIHS4 2025	Retrospective, longitudinal	2 patients (16 assessments)	HS patients	Hidradenitis suppurativa	Severity assessment	Dermatologists
BI 2024	Prospective, cross-sectional	100 images, 15 practitioners	Mixed conditions	GPP, HS, multiple	Diagnostic accuracy, rare diseases	PCPs + dermatologists
COVIDX 2022	Prospective, cross-sectional	160 patients, 6 dermatologists	Chronic dermatological conditions	Multiple chronic conditions	Clinical utility, remote monitoring, severity assessment	Dermatologists
DAO_O 2022	Prospective, longitudinal	117 patients (127 enrolled, 10 excluded)	Primary care referrals	Multiple conditions	Referral adequacy, malignancy detection	PCPs
DAO_PH 2022	Prospective, longitudinal	131 patients	Primary care referrals	Multiple conditions	Diagnostic accuracy, referral adequacy	PCPs + dermatologists
IDEI 2023	Prospective + retrospective	202 patients	Pigmented lesions + alopecia	Melanoma suspicion, androgenetic alopecia	Diagnostic accuracy, malignancy detection, severity assessment	Dermatologists
MC_EVCDAO 2019	Prospective, cross-sectional	105 patients	Melanoma-suspected lesions	Melanoma	Malignancy detection	Dermatologists
PH 2024	Prospective, cross-sectional	30 images, 9 PCPs	Multiple conditions	Multiple conditions	Diagnostic accuracy, remote consultation	PCPs
SAN 2024	Prospective, cross-sectional	29 images, 16 practitioners	Multiple conditions	Multiple conditions	Diagnostic accuracy, remote consultation	PCPs + dermatologists

Total: 9 studies (8 with frozen MDR version + 1 with legacy device), 800+ patients, 60+ practitioners.

3.2. Evidence hierarchy assessment (MDCG 2020-6)

The CEP's evidence hierarchy table (lines 692–710) needs correction. Current vs. what we actually have:

Rank	Evidence type	CEP says	Actual status
1	High quality CIs covering all variants	Yes	Yes — 8 pivotal studies
5	Equivalence data	No	Should be Yes — equivalence claimed with legacy device, full access to design data
6	SotA evaluation	Yes	Yes — 64 articles in R-TF-015-011
7	Complaints and vigilance data	No	Should be Yes — 7 non-serious incidents documented in PSUR/PMS Report
8	Proactive PMS data (surveys)	No	Should be Yes — COVIDX included CUS/DUQ/SUS questionnaires; PMCF surveys conducted

Critical inconsistency

The CEP explicitly marks equivalence data, vigilance data, and PMS survey data as "Not used" in the evidence hierarchy, while the CER simultaneously claims equivalence with the legacy device and references its market experience. This inconsistency must be corrected in both documents.

3.3. Appraisal quality scores (CER lines 722–734)

Study	Relevance (/6)	Quality (/4)	Weight (/10)	Level of evidence (/10)
MC_EVCDAO 2019	0.5	3.5	6.5	5
AIHS4 2025	0.5	3.5	8.5	5
BI 2024	0.5	3.5	8.5	6
COVIDX 2022	0.5	2.5	6.5	5
DAO_O 2022	0.5	3.5	9.5	5
DAO_PH 2022	0.5	3.5	9.5	5
IDEI 2023	0.5	3.5	8.5	5
PH 2024	0.5	3.5	8.5	5
SAN 2024	0.5	3.5	8.5	5
Mean	—	—	8.3	5.1

Mean weight 8.3/10 is strong. Level of evidence 5/10 reflects primarily observational designs (no RCTs), which is standard for SaMD diagnostic aids.

4. Coverage analysis

4.1. Clinical benefit coverage

Mapping the 3 claimed clinical benefits (consolidated from 7) to supporting studies:

Benefit	Code	Sub-criteria	Supporting studies	Coverage assessment
Diagnostic accuracy — all presentations	7GH	(a) General; (b) Rare diseases; (c) Malignancy	BI 2024, DAO_PH 2022, IDEI 2023, SAN 2024, PH 2024, MC_EVCDAO 2019, DAO_O 2022	(a) Strong — 5 studies, 500+ subjects; (b) Moderate — BI 2024, SAN 2024, PH 2024; (c) Strong — 4 studies, 555+ patients, melanoma-specific cohort (MC_EVCDAO 2019)
Objective severity assessment	5RB	—	AIHS4 2025, COVIDX 2022, IDEI 2023	Weak-to-moderate — AIHS4 has only 2 patients (16 assessments); COVIDX uses CUS rather than direct severity measurement; IDEI covers androgenetic alopecia severity. Gap identified in CER (Gap 2) for atopic dermatitis, acne, and FFA
Care pathway optimisation (waiting times, referral adequacy, remote care)	3KX	(a) Waiting times; (b) Referral; (c) Remote care	DAO_O 2022, DAO_PH 2022, COVIDX 2022, PH 2024, SAN 2024	(a) Moderate — 3 studies; (b) Moderate — 2 studies, 248 patients in primary care; (c) Moderate — COVIDX remote, PH/SAN remote consultation feasibility

Key weakness: Benefit 5RB (severity assessment) has the thinnest evidence base. AIHS4 with 2 patients is extremely small, and the CER itself acknowledges this as Gap 2 for PMCF.

4.2. Indication coverage

The device covers ICD-11 Chapter 14 skin conditions. Key condition groups and their study coverage:

Condition category	Studies providing evidence	N (approx.)	Assessment
Melanoma / malignant lesions	MC_EVCDAO, IDEI, DAO_O, DAO_PH	400+	Good
Pigmented lesions (benign)	MC_EVCDAO, IDEI	200+	Good
Psoriasis	COVIDX	Part of 160	Limited — single study
Acne	COVIDX	Part of 160	Limited — single study; Gap 2
Atopic dermatitis	COVIDX	Part of 160	Limited — single study; Gap 2
Hidradenitis suppurativa	AIHS4, BI	2 + images	Weak — AIHS4 has 2 patients
GPP (Generalised Pustular Psoriasis)	BI	Image-based	Limited — single study, image assessment only
Androgenetic alopecia	IDEI	96	Moderate — single study but adequate N
Urticaria	COVIDX (PMS data)	—	Minimal — mentioned in usage patterns only
Other rare conditions	BI, SAN, PH	Image sets	Variable — depends on condition

Key weakness: The device claims coverage of all ICD-11 Chapter 14 conditions but most individual conditions (beyond melanoma and pigmented lesions) are covered by only 1–2 studies. The CER must either justify why limited per-condition coverage is acceptable (uniform algorithm architecture argument) or narrow the claims.

4.3. Patient population coverage

Demographic factor	Available data	Gap
Age	Studies specify "adult patients (≥18)" but no age distribution breakdown provided	Need to compile available age ranges from study data
Sex	Not reported per study	GDPR data minimisation limits collection; must be justified
Fitzpatrick skin type	Some studies have data (confirmed by user) — need to identify which and compile	Critical for AI dermatology — must present whatever data exists
Geographic diversity	Studies conducted in Spain (Basque Country, Madrid, other regions)	Limited geographic diversity; must justify representativeness
Comorbidities	Not systematically reported	Standard for SaMD observational studies; justify

4.4. User group coverage

User group	Studies	N practitioners	Assessment
Primary care physicians (PCPs)	DAO_O, DAO_PH, BI, PH, SAN	30+	Good
Dermatologists	MC_EVCDAO, IDEI, COVIDX, BI, SAN	30+	Good
IT professionals (deployment)	None	0	Not applicable — IT professionals deploy the device, they don't generate clinical data

4.5. Safety coverage

Safety aspect	Evidence	Assessment
Adverse events in CIs	0 across all 9 studies	Strong — consistent "no adverse events" across 800+ patients
Device deficiencies in CIs	0 reported	Strong
Legacy market experience	7 non-serious incidents, 0 serious, 0 FSCAs (4+ years, 4,500+ reports)	Strong — but NOT included in CER (see Item 3a)
Vigilance database search	EUDAMED/MAUDE searches referenced	Need to confirm this is documented
Similar device safety	SotA identified no direct patient harm from similar devices	Adequate

5. Gap analysis specific to sufficiency

#	Sufficiency dimension	What we have	What's missing for BSI	Priority
1	Benefit-to-study mapping	3 benefits (7GH, 5RB, 3KX) with sub-criteria, 9 studies — mapping is implicit in filter criteria code	Explicit narrative in CER mapping each benefit to its supporting studies, with per-benefit sufficiency conclusion	High
2	Indication coverage justification	Studies cover melanoma, pigmented lesions, multiple chronic conditions, HS, GPP, alopecia	Explanation of how 9 studies covering ~15 conditions justify claims across all ICD-11 Ch.14 (~346 conditions). The uniform algorithm architecture argument needs to be made explicit	High
3	Population demographics	"Over 800 patients" — no demographic breakdown	Compile Fitzpatrick data from studies that have it; present available age/sex data; justify gaps via GDPR and study design	High
4	Per-study sample size justification	Formal calculations exist in CIPs (80% power, alpha 0.05 for IDEI; melanoma ratio for MC_DAO; target sample for others)	CER must summarise the sample size rationale for each study, not just claim "over 800 patients"	Medium
5	Evidence hierarchy correction	CEP table marks equivalence, vigilance, and PMS as "Not used"	Correct the table to reflect actual data used; align with CER narrative	High
6	Quality methodology	Studies appraised with mean weight 8.3/10	CER needs a brief discussion of why observational Level 5 evidence is appropriate for SaMD (no surgical intervention, no randomisation needed for diagnostic accuracy studies)	Medium
7	SotA comparison narrative	acceptanceCriteriaStateOfTheArtValue exists per claim	CER lacks an explicit "device vs SotA" comparison section with aggregate conclusions. Individual claim-level comparisons exist but no synthesis	High
8	Severity assessment evidence weakness	AIHS4 has 2 patients; acknowledged as Gap 2	Must explicitly acknowledge this limitation and justify that PMCF activities will address it; argue that current evidence is sufficient for initial CE mark with planned post-market data collection	Medium

6. Cross-NC connections

Item 3a — Clinical data analysis

Item 3a research covers the factual gaps (missing PMS data, CI regulatory details, acceptance criteria reconciliation, etc.). Item 3b builds on those findings to construct the sufficiency argument. The fixes are coordinated:

• Item 3a Fix 1 (integrate PMS data) → feeds into Item 3b's safety sufficiency argument
• Item 3a Fix 3 (acceptance criteria reconciliation) → feeds into Item 3b's performance sufficiency argument
• Item 3a Fix 4 (data pooling methodology) → feeds into Item 3b's quantity justification

Item 2b — Clinical benefits, performance, safety vs SotA

Item 2b research addresses the SotA traceability chain. Item 3b's gap #7 (SotA comparison narrative) depends on the same fix: establishing provenance from SotA articles → baselines → acceptance criteria → achieved values.

Technical Review M1.Q1 — IFU performance claims

M1.Q1 research shares the concern about whether all IFU claims are backed by sufficient evidence, and the 239 vs 346 ICD-11 category reconciliation.

7. Response strategy

Structure of the sufficiency justification

The response should present a structured sufficiency argument organised along the three dimensions BSI expects:

A. Quantity of data

1. Total evidence base: 9 studies, 800+ patients, 60+ practitioners, 4+ years of market experience with legacy device
2. Per-study sample size: Summarise each study's sample size calculation, target, and actual enrollment
3. Per-benefit evidence: Map each of the 3 clinical benefits (7GH with sub-criteria, 5RB, 3KX with sub-criteria) to supporting studies and total subjects contributing
4. Statistical power: All studies designed for ≥80% power at alpha 0.05 (except AIHS4, which uses repeated measures design)

B. Quality of data

1. Study designs: All prospective or mixed prospective/retrospective; observational designs appropriate for SaMD diagnostic accuracy (no surgical intervention; reference standard available)
2. Appraisal scores: Mean weight 8.3/10 across the portfolio; no study below 6.5/10
3. Level of evidence: Level 5 (observational) is appropriate for SaMD — cite MDCG 2020-1 (clinical evaluation of MDSW) which acknowledges that RCTs may not be appropriate or feasible for SaMD
4. Data quality controls: DIQA algorithm validates image quality in real-time; this mirrors real-world use because the device itself rejects poor quality images

C. Coverage

1. Clinical benefits: Table mapping 3 benefits (7GH, 5RB, 3KX) with sub-criteria → studies → subjects → sufficiency conclusion
2. Indications: Justify coverage through the uniform algorithm architecture argument — the device processes all skin images through the same pipeline; condition-specific performance is validated for the highest-risk conditions (melanoma, malignant lesions) and representative chronic conditions; full ICD-11 coverage is monitored through PMCF
3. Patient populations: Present available demographic data (Fitzpatrick from studies that have it; age ranges; geographic distribution); justify gaps via GDPR data minimisation and argue that skin condition diagnosis is less demographically sensitive than pharmacological interventions
4. User groups: PCPs and dermatologists both well-represented across multiple studies
5. Safety: Zero adverse events across 800+ patients in CIs + zero serious incidents across 4,500+ reports in market use; discuss why this is sufficient given the device's risk profile (SaMD, human-in-the-loop, no direct patient contact)
6. Comparison to SotA: Device performance meets or exceeds SotA baselines derived from 64 articles; present the comparison at the clinical benefit level, not just the individual claim level

Fixes required in the CER

Fix 1: Add a "Sufficiency of clinical evidence" section

New section in the CER containing:

• The benefit-to-study mapping table
• The indication coverage analysis with justification
• Available demographic data and gap justification
• Per-study sample size summary
• Aggregate safety conclusion incorporating both CI data and legacy PMS data

Fix 2: Correct the MDCG 2020-6 evidence hierarchy table

In the CEP (R-TF-015-001, lines 692–710):

• Change Rank 5 (equivalence) from "No" to "Yes" — reference the equivalence assessment
• Change Rank 7 (complaints/vigilance) from "No" to "Yes" — reference PSUR/PMS Report
• Change Rank 8 (proactive PMS/surveys) from "No" to "Yes" — reference COVIDX CUS/SUS and PMCF surveys

Fix 3: Add device vs SotA synthesis

The CER currently presents individual performance claims with SotA values but no synthesis. Add a section that:

• Groups performance by clinical benefit
• Compares aggregate device performance vs SotA baselines
• Draws per-benefit conclusions on whether the device meets, exceeds, or falls below SotA
• Acknowledges limitations and how PMCF addresses them

Fix 4: Acknowledge and justify evidence limitations

Proactively address known weaknesses:

• AIHS4 small sample (2 patients) — justified by repeated measures design; Gap 2 in PMCF
• Limited per-condition coverage beyond melanoma — justified by uniform architecture; PMCF monitoring
• Limited geographic diversity (Spain only) — justified by skin condition universality; planned international PMCF
• Observational designs only — justified by MDCG 2020-1 guidance on MDSW evidence requirements

8. Risk assessment

Risk	Impact	Mitigation
BSI concludes evidence is insufficient for all claimed indications	Could require narrowing claims to only validated conditions, which would impact IFU and intended purpose	Present the uniform architecture argument clearly; show that high-risk conditions (melanoma) have strongest coverage; acknowledge monitoring gaps addressed by PMCF
AIHS4's 2-patient study undermines severity assessment benefit	BSI may require additional pre-market data for severity claims	Frame as "initial validation with confirmatory PMCF" per MDCG 2020-7; emphasise that COVIDX provides additional severity data for chronic conditions
Demographic coverage gaps (no age/sex breakdown) undermine population claim	BSI may question whether results generalise across demographics	Compile Fitzpatrick data from studies that have it; present geographic diversity of study sites; cite GDPR data minimisation as legitimate constraint
Evidence hierarchy inconsistency triggers a secondary finding	Could generate a new NC about CEP quality	Fix the table proactively in both CEP and CER before responding

9. Open items

Most open items for Item 3b are the same as Item 3a (see question-for-jordi.mdx). One additional item:

1. Which studies have Fitzpatrick data? — User confirmed some studies have Fitzpatrick skin type data. Need to identify which ones and compile the data for the population coverage analysis. This may require reading each study's CIR in detail.

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Regulatory framework: what the BSI meeting revealed

Severity warning

Nick stated during the BSI meeting (2026-03-25) that refusal is extremely likely if the data sufficiency argument is not resolved. Item 3b is a blocking item: BSI cannot certify a device unless the manufacturer has explicitly justified — in the CER — that sufficient clinical evidence exists for all claims across all populations and indications. Nick's condition for CE mark approval was explicit: the pre-market evidence base must be demonstrably sufficient NOW, with robust PMCF as confirmation — not as a substitute for missing pre-market data.

The four applicable guidance documents

Document	Role for Item 3b
MDR Article 61(1) and Annex XIV (2)	The binding regulatory basis for the sufficiency obligation. Article 61(1) requires the manufacturer to "specify and justify the level of clinical evidence necessary." Annex XIV (2) requires the clinical evaluation to be "thorough and objective" and proportionate to "the nature, classification, intended purpose and risks of the device." These are not aspirational goals — they are conditions for CE mark validity. A CER that states "over 800 patients" without a structured justification per each benefit, indication, and population does NOT satisfy Article 61(1). The justification must be explicit and traceable, not asserted.
MDCG 2020-6, § 6.4 and Appendix III	Two distinct obligations apply here. First, § 6.4: "No reliance on future PMCF to fill pre-certification gaps: sufficient clinical evidence must exist PRIOR to MDR certification. PMCF under MDR can confirm conclusions already supported by evidence." This means the current 9-study evidence base must be argued as sufficient on its own merits — PMCF cannot rescue claims that the pre-market data cannot support. Second, Appendix III provides the 12-level evidence quality hierarchy. MRMC studies (simulated use, multi-reader multi-case) map to Rank 11 — they are explicitly classified as NOT clinical data. Any sufficiency argument that relies on MRMC studies as clinical evidence is invalidated by this hierarchy. The CEP's evidence hierarchy table must be corrected to use this framework accurately, not the uncorrected "Rank 1 and 2" claim the CER currently makes.
MEDDEV 2.7.1 Rev 4, Annex A7.3 and A7.4	Annex A7.3 requires per-indication performance data for the major clinical indications, not just pooled aggregate metrics. A claim that the device diagnoses "all ICD-11 Chapter 14 conditions" with "AUC >0.8" is insufficient — BSI will expect to see individual performance data for the major claimed conditions (melanoma, pigmented lesions, inflammatory, hidradenitis suppurativa, etc.) with condition-specific sensitivity, specificity, and comparison to SotA baselines. Annex A7.4 is non-negotiable: "If clinical data is lacking, conformity with the relevant GSPRs is NOT fulfilled." This applies directly to the declared evidence weaknesses for severity assessment (AIHS4 with 2 patients) and limited per-condition coverage. These weaknesses cannot be glossed over — they must either be resolved with pre-market data or explicitly declared as remaining gaps with PMCF activities specified per MDCG 2020-6 § 6.5(e).
MDCG 2020-1, three-pillar framework	For MDSW, MDCG 2020-1 requires the clinical evaluation to address three distinct pillars: Valid Clinical Association (VCA), Technical Performance, and Clinical Performance. The VCA pillar is foundational — it must be established for each claimed output BEFORE the Technical and Clinical Performance evidence is assessed. The device produces two distinct outputs: (1) an ICD-11 probability distribution and (2) a clinical sign severity measurement. Each output requires its own VCA establishing the scientific basis for why the algorithm output correlates with the relevant clinical condition or severity state. The sufficiency argument must be organised around these three pillars — not around study counts or patient numbers — to demonstrate that the evidence is sufficient per the MDSW-specific framework BSI uses.

What the meeting revealed: sufficiency is not about quantity, it is about structured justification

Nick's critique during the meeting was not that the device has insufficient data — it is that the CER fails to narrate the justification. The "over 800 patients" claim is a quantity assertion, not a sufficiency justification. BSI applies the MEDDEV 2.7.1 Rev 4 framework at Stage 3 (data analysis), which requires a structured argument mapping evidence → claims → populations → conclusions.

Per MEDDEV 2.7.1 Rev 4 Section 10 (Stage 3), the clinical evaluation analysis must explicitly:

1. Examine how all identified clinical data relates to each claim
2. Assess whether the body of evidence as a whole demonstrates device safety and performance
3. Identify any remaining clinical gaps and how they will be addressed

Nick's statement that "work done, not narrated, fails" applies directly to Item 3b: all the evidence exists, but the CER does not structure it as a Stage 3 analysis per MEDDEV 2.7.1 Rev 4 Section 10.

The X-3 three-tier evidence structure as the sufficiency architecture

The disease categorisation decision in X-3 resolves how the sufficiency argument is constructed for the 346 ICD-11 Chapter 14 categories:

Tier	Condition type	Evidence standard	Sufficiency basis
Tier 1	Malignant conditions (5% prevalence)	Individual per-condition analysis	MC_EVCDAO 2019, IDEI 2023, DAO_O 2022, DAO_PH 2022 — specific melanoma and malignancy data; meets MEDDEV A7.3 per-indication requirement
Tier 2	Rare diseases — autoimmune (3%) and genodermatoses (1%)	Grouped analysis with declared acceptable gaps A and B	Gap A and Gap B are declared under MDCG 2020-6 § 6.5(e); D.1 and D.2 PMCF activities are mandatory; sufficiency for these tiers depends on the D.1/D.2 commitment being explicit
Tier 3	General conditions — infectious (57%), inflammatory (15%), other (19%), vascular (1%)	Pooled analysis with architecture-based justification	Justified by uniform algorithm architecture; COVIDX, DAO_O, DAO_PH, BI, SAN, PH provide representative evidence; this argument must be made explicit, not assumed

The critical implication of this structure: the "uniform algorithm architecture" argument is NOT a blanket excuse. It is a proportionality argument per Annex XIV (2) that must be explicitly constructed and limited to Tier 3 conditions. For Tier 1 conditions, per-indication data from MEDDEV A7.3 is required and exists. For Tier 2 conditions (Gaps A and B), PMCF activities D.1 and D.2 are the regulatory basis — without them, conformity is not fulfilled per MEDDEV A7.4.

The declared acceptable gap strategy — what MDCG 2020-6 § 6.5(e) requires

MDCG 2020-6 § 6.5(e) permits acknowledging gaps in the evidence base, but requires:

1. Explicit identification of each gap
2. Clinical justification for why the remaining evidence is still sufficient for the overall claim
3. Specific PMCF activities designed to address the acknowledged gap

Gap A (autoimmune, 3%) and Gap B (genodermatoses, 1%) were declared under this framework. The sufficiency argument for these gaps is: (a) they represent 4% of the clinical indication space by prevalence; (b) the underlying algorithm processes all ICD-11 Chapter 14 conditions uniformly; (c) PMCF Activities D.1 and D.2 are committed as confirmatory activities. If any of these three elements is absent from the CER, the declared gap strategy fails and conformity is not demonstrated.

The evidence hierarchy correction is mandatory, not optional

The CEP's evidence hierarchy table (lines 692–710) currently marks equivalence data, vigilance data, and PMS survey data as "Not used." This is factually incorrect, and BSI will detect the inconsistency:

• The CER simultaneously claims equivalence with the legacy device while the CEP denies using equivalence data
• The CER mentions PMS experience while the CEP denies using PMS data

MDCG 2020-6 Appendix III Rank 5 (equivalence data), Rank 7 (complaints and vigilance), and Rank 8 (proactive PMS) are all used and must be marked accordingly. Failure to correct this creates a second finding about the internal consistency of the clinical evaluation documentation — BSI will not overlook it.

Nick's CE marking condition: what "robust PMCF" means in regulatory terms

Nick stated that CE mark approval is conditional on a "robust PMCF." In regulatory terms, this means the PMCF Plan must be assessed as credible and capable of confirming the pre-market evidence — not as a placeholder. For Item 3b, this has a direct implication: the sufficiency argument must be written in a way that is forward-compatible with the PMCF plan.

Specifically: where the sufficiency argument acknowledges a weakness (e.g., AIHS4 with 2 patients for severity assessment; limited per-condition coverage beyond melanoma), the argument must explicitly cross-reference the PMCF activity that will address it and state that the limitation is accepted under MDCG 2020-6 § 6.5(e) with a specific confirmatory activity. A weakness acknowledged without a named PMCF activity is a gap — not a declared limitation.