Class III evidence strategy
Clinical evidence strategy informed by first-hand Notified Body review experience.
Design and run VNS clinical investigations in Europe with an endpoint justified for your indication, feasibility built on the specialist pathway your participants are already in, ISO 14155:2026 clinical operations, patient-generated data capture structured for long-term follow-up, and a post-market route planned from the start.
From titration and treatment exposure to diary adherence, device events and long-term follow-up.
Clinical evidence strategy informed by first-hand Notified Body review experience.
Specialist-center qualification, activation and monitoring under ISO 14155:2026.
Treatment settings, programming history and patient-reported data captured as structured, queryable data.
Long-term follow-up designed to feed the clinical evaluation it has to support.
Depending on the indication and device, the VNS intervention may not be fixed at a single moment. Output settings may be titrated over weeks or months, exposure accumulates between visits rather than during them, and part of the endpoint data may be generated by the participant at home. Four properties can materially affect whether the resulting dataset can answer the question it was designed to address.
Where the clinical effect emerges over repeated assessments rather than at an implantation or a first use, the architecture has to carry baseline burden, exposure accumulated after activation, the follow-up trajectory, whatever responder status the protocol adopts, and durability. Not every VNS study is built this way, and the structure has to be justified from the indication rather than inherited from a neighboring therapy.
Where part or all of the endpoint comes from diaries, event counts or patient-reported instruments, completion burden, adherence, retrospective entry and time-stamping become data-quality variables, and site follow-up becomes an operational workstream rather than an administrative one.
Where the system is programmable, the dataset has to connect the settings in force, each change with its date and reason, the exposure accumulated between changes, and the outcome measured against it. If clinically relevant programming history is captured only as unstructured free text, it may be difficult to reconstruct consistently, query and incorporate into analysis.
Post-market evidence may need to describe therapy continuation, device deficiencies, revision or replacement where relevant, discontinuation and its reasons, and how many participants remained in follow-up.
Vagus nerve stimulation covers implanted systems delivering therapy on programmed settings and non-invasive or transcutaneous systems that may be self-administered or used outside the study site, depending on the device and protocol. The therapy name is shared. The operating model is not, and many practical study decisions follow from this split rather than from the therapy area.
The site model, the monitoring plan and the data model follow from the delivery route.
The value is not in supplying each part. It is in the endpoint, the electronic case report form, the monitoring plan and the clinical evaluation being designed against each other rather than in sequence by different suppliers.
Indication, claim, population, treatment pathway, visit schedule, endpoints and follow-up duration, each traceable to the claim it supports.
Endpoint hierarchy, responder definitions, longitudinal models, sample size and the missing-data strategy.
Participant pool in your defined population, investigator and device experience, research capacity and competing studies.
Country-specific regulatory and ethics preparation, contracting, essential documents, training and activation tracked against real approval durations.
Site management, enrollment oversight, governance, deviation handling and retention.
A risk-based model covering exposure, device accountability, endpoint source data and completion of patient-generated data.
Device and treatment data, clinical outcomes, diaries, device deficiencies and follow-up status, with edit checks built for the endpoint.
Clinical Investigation Report, clinical evaluation report input and PMCF documentation.
An endpoint defensible for one VNS indication may be inappropriate for another. The instrument, the timepoint and the difference considered clinically meaningful should be justified using the relevant clinical literature, accepted outcome-measure methodology, the available validation evidence for the instrument in that population, and the intended clinical claim. Endpoint architecture is generally driven by the indication, the intended clinical benefit, the treatment duration, the study phase, the population and the regulatory objective the data has to serve.
Three questions can carry substantial design risk: what counts as a response and on what published basis, how long a baseline is needed before an effect can reasonably be attributed to the therapy, and whether the instrument has validation evidence in the population you are actually enrolling. Each has direct consequences for sample size, so they are worth settling before the synopsis is fixed rather than after.
No endpoint is mandatory across all VNS studies. Endpoint selection, responder thresholds and participant-selection criteria are described here in general terms only, and study-specific wording is set with the sponsor and reviewed by the investigator team and, where required by the program, appropriately qualified independent specialists.
Review your VNS endpoint strategy with our biostatistics team
If the primary endpoint is a count the participant records at home, a missed week is not an administrative issue. It may represent missing endpoint data that cannot be reliably recovered later as contemporaneous patient-generated data.
Digital tools do not eliminate missing data and no completion rate is promised. What a well-built instrument does is make completion gaps visible early enough for protocol-permitted follow-up and corrective action, without retrospectively reconstructing missing endpoint observations, and make the missing-data assumptions in the statistical analysis plan defensible rather than convenient.
See how our clinical data management and eCOA services are built
Access to European sites is not a feasibility answer. The question is whether a center sees the population your protocol defines, treats it through the pathway your protocol assumes, and has the capacity to carry a study alongside routine care. Eclevar centrally manages the feasibility questionnaire, the qualification process and activation tracking, working with the appropriate local delivery model for the countries selected.
In the indication and population the protocol defines.
In that population rather than in the therapy area generally.
With the system class under study.
The coordinator, the specialist staff and the committed time.
Across the full follow-up period, not the first year.
Including who follows up on completion.
And their claim on the same population and staff.
Expressed against your criteria over a study-defined assessment period.
Where the system is implanted, implantation and programming capability are assessed as well. When revision, replacement or explant is performed outside the recruiting center, the referral pathway and the data-return process should be mapped during feasibility, so clinically important device events remain traceable in the study dataset. Where the system is non-invasive, the questions shift to participant training capacity, device issue and return handling, and the center’s ability to run remote follow-up contacts.
The design question is whether the database can reconstruct, for any participant at any timepoint, what therapy was in force and what outcome was measured against it. Four domains have to share a participant and timepoint key for that to be possible: device and treatment, clinical, patient-reported, and safety and follow-up.
Edit checks are written against the endpoint, validation rules are agreed before first participant in, and where the device or its programmer can export a configuration record, that export is reconciled against the study record rather than transcribed.
In a study where important endpoint data is generated between visits, targeted source review alone is not sufficient. The model may also need centralized review of completion, exposure and longitudinal data patterns, so a site whose diary completion is drifting is identified during the study rather than at close-out. Depending on the risk assessment it combines centralized review, remote monitoring, targeted on-site visits and risk-based effort concentrated on the variables the endpoint depends on.
The analytical strategy determines what the protocol has to collect. Written afterwards, it can only work with what happened to be captured. The considerations that typically apply to a VNS program are baseline event burden and the baseline length needed to establish it, change over time, responder analyses and how sensitive the conclusion is to the threshold chosen, repeated-measures models, the missing-data mechanism assumed and the analyses that test it, and attrition over long follow-up.
There is no universal VNS analysis. The approach is set against the indication, the endpoint and the design, and documented before it is needed.
Attrition accumulates from missed visits nobody followed up, a schedule that was never realistic for the population, and site staff turnover. Retention planning means expectations set at consent, a schedule built around what the population can attend, remote contacts where the protocol allows, missed visits identified inside the window, and a periodic retention-risk review at program level.
No retention rate is promised. Retention is planned for, measured and reported, and the analysis plan is written to survive the attrition that does occur.
Post-market evidence may need to describe durability of benefit, therapy persistence and discontinuation, device safety in routine use, device deficiencies, revision or replacement where relevant, and performance in the real-world population rather than the enrolled one.
Choosing the model is a judgment about the question, not a default. The post-market evidence model depends on the clinical question and the methodology needed to answer it.
A registry may be appropriate for questions such as long-term outcomes, therapy persistence, device survival, revision, replacement, explant and performance across a defined real-world population. A prospective registry can itself include scheduled follow-up, patient-reported outcomes, standardized clinical assessments, imaging, trained assessors and structured treatment data where its design requires them.
A dedicated PMCF clinical investigation may be more appropriate where a specific hypothesis, clinical claim, intervention, comparator or tightly controlled assessment framework requires protocol-driven evaluation. Some programs may use both, with a registry extending or complementing a prospective investigation where that combination fits the evidence question.
Where applicable, the PMCF plan and evaluation report can be structured in line with MDR Annex XIV Part B and the MDCG 2020-7 and MDCG 2020-8 templates. MDCG 2025-10 provides current European guidance on post-market surveillance. PMCF should therefore be planned as part of the broader post-market surveillance and clinical-evaluation lifecycle rather than as an isolated evidence activity.
PMCF studies under EU MDR · Medical device registries and real-world evidence
When endpoint strategy, data capture, monitoring and reporting are designed in isolation, inconsistencies at their interfaces can create avoidable evidence and data-integrity risks: an endpoint not reflected in the electronic case report form, diary completion not monitored, a follow-up dataset not usable for the intended clinical evaluation.
Eclevar’s VNS delivery model combines Class III neurostimulation evidence work, specialist medical-device clinical operations, longitudinal data architecture and indication-specific oversight. The examples below demonstrate the capabilities that transfer directly to VNS study design and execution.
Eclevar supports multicountry European clinical investigations through a combination of in-house clinical operations and qualified local coverage where appropriate, with central program governance, data, biometrics and medical writing. Eclevar leads and coordinates regulatory and ethics start-up, using in-house delivery or qualified local support according to the country, authority and applicable submission pathway.
The delivery reference is a randomized post-market clinical follow-up program of 160 participants across 14 clinical sites in a multicountry European program, run on Eclevar’s clinical data platform from protocol design through final study report. It is in a different therapeutic area, and it demonstrates European study delivery: participant follow-up, clinical data architecture and protocol-to-report delivery.
Eclevar leads clinical evidence strategy, European study delivery, biometrics and regulatory integration. Indication-specific medical oversight is defined according to program needs and may involve sponsor investigators and appropriately qualified independent specialists. Eclevar retains the CRO safety and medical review responsibilities defined in the contract. That does not replace the investigator’s clinical judgment, and the investigator’s role does not replace CRO medical monitoring.
Chief Operating Officer
Clinical evidence strategy informed by first-hand Notified Body review experience, applied to how a Class III clinical evidence dossier is structured and defended.
Chief Data Officer · Head of Biometry
Data capture design for treatment settings and device configuration, eCOA architecture, database governance, statistics and the analysis-ready dataset.
Clinical Operations Director
European clinical-study delivery, site management and operational governance across the clinical, data, writing and quality workstreams.
Head of Medical Writing
Clinical Investigation Reports, clinical evaluation reports and PMCF evaluation reports, plus Notified Body response handling.
Former positions are stated for biographical context only. Eclevar MedTech is an independent contract research organization. It is not affiliated with, accredited by or endorsed by any Notified Body, and Notified Body names referred to on this site are the trade marks of their respective owners.
For sponsors with a synopsis or protocol in development. We review the endpoint, the exposure and titration capture, the diary and eCOA architecture, the statistical approach, European feasibility and the long-term evidence implications of the design as it stands.
For sponsors entering European execution. Site landscape, participant pathway, investigator qualification, start-up planning and recruitment assumptions tested against real approval durations.
From protocol to Clinical Investigation Report under one Eclevar program-governance model: strategy, feasibility, start-up, monitoring, data management, eCOA, biostatistics, medical writing and long-term evidence planning.
Scope in each option is indicative and set by the contracted scope of work.
Clinical evidence strategy and the clinical investigation plan, endpoint and statistical strategy, European site feasibility and activation, clinical operations and monitoring, electronic data capture including patient-reported outcomes, biostatistics, and the medical writing that produces the Clinical Investigation Report. What matters is whether those are designed against each other. One avoidable failure mode is an endpoint the data-capture model was never built to support.
From the population your protocol defines rather than from the center’s reputation or annual procedure count. How many matching participants did that center see over a study-defined assessment period, does the multidisciplinary team your protocol assumes exist there with capacity, who follows up on diary completion between visits, and what else is already open competing for the same population and staff.
From the indication and the intended claim, justified using the relevant clinical literature, accepted outcome-measure methodology and the available validation evidence for the instrument in that population. Where a responder definition is used, the candidate definitions, their basis and their consequences for sample size should be set out so the sponsor and investigators choose on the record.
By treating completion as a study variable rather than a site administrative task: an instrument sized to the endpoint, completion windows and reminders defined in the protocol, dashboards showing completion by participant, checks flagging implausible entry patterns as well as missing ones, and a protocol-defined escalation when completion falls below a stated threshold. Electronic capture gives time-stamped entries and completion visibility during the study. Where some participants cannot use a digital instrument, a hybrid or site-assisted workflow may be more defensible than a uniform digital one.
Prevention first, then a prespecified analysis strategy. The missing-data mechanism assumed should be stated in the statistical analysis plan before the data exists, with sensitivity analyses testing whether the conclusion survives a different assumption. No statistical method recovers the actual contemporaneous endpoint observations that were never collected, which is why completion monitoring and the missing-data strategy are designed together.
In structured fields rather than free text. Where applicable to the system under investigation, the parameters in force, the program identifier, and the date and reason for each change should be queryable, so the analysis can describe what was delivered. Where the device or programmer can export a configuration record, that export is reconciled against the study record.
Yes, both delivered by Eclevar teams. Monitoring combines centralized review, remote monitoring and targeted on-site visits under a risk-based plan, focused on exposure, device accountability, endpoint source data and completion of patient-generated data. Biostatistics covers sample size and its assumptions, the statistical analysis plan, longitudinal and repeated-measures models, responder analyses, the missing-data strategy and the analysis-ready dataset, set before enrollment because it determines what the protocol has to collect.
A clinical investigation can contribute to the post-market evidence strategy where the follow-up, variables, event definitions and analytical approach are prospectively designed to address the relevant PMCF questions. Long-term follow-up built into the investigation, an event taxonomy consistent with the manufacturer’s vigilance terminology, and a dataset the clinical evaluation can use directly are what make that contribution possible.
Yes. Eclevar supports multicountry European VNS studies through a combination of in-house clinical operations and qualified local coverage where appropriate, with central program governance, data management, biometrics and medical writing. The specific country and site model is defined during feasibility according to the indication, device, recruitment pathway and applicable submission requirements.
The horizon should be justified against the device, the intended use, the residual risks, the clinical endpoint and the evidence gap. For implanted systems, expected device service life may be one important input. Retention has to be planned from the outset, because a long follow-up without a retention plan produces a dataset too incomplete to answer the durability question.
Bring us the device, the intended indication, the current evidence, the proposed endpoints and the target markets. We will review the study architecture, the European site strategy, the participant-data model, the statistical approach and the long-term evidence route with your team.
Confidentiality and non-disclosure arrangements can be agreed before program materials are reviewed.