Contribution of Methodologies Adapted to Clinical Trials Focusing
on High Risk Medical Devices
C. Vidal
1
, R. Beuscart
2
and T. Chevallier
3
1
INSERM-CIC 1431, Besançon University Hospital, Besançon, France
2
INSERM-CIC 1403, Lille University Hospital, Lille, France
3
IDIL, Nîmes University Hospital, Nîmes, France
Keywords: High Risk Medical Device, Evaluation, Clinical Trial, Adaptive Trial, Bayesian Statistics, Methodology.
Abstract: High risk medical devices clinical trials are complicated, expensive, time-consuming and need an improved
clinical evaluation with better scientific evidence throughout the European Union. The purpose of this study
is to identify methodologies whose use could facilitate the evaluation of the medical device. Adaptive methods
and Bayesian approaches are expert tools that can accelerate access to innovation providing more flexibility
but they are insufficiently used because of a lack of expertise and training in the trial community (clinicians,
statisticians and regulation authorities). Involving stakeholders (regulation authorities, industrial, clinicians,
biostatisticians, end-users) early in the conceptualization of the adaptive design improve adoption,
implementation, feasibility and overall quality of that trial.
1 INTRODUCTION
The clinical evaluation of a new medical device is an
essential stage in the industrialists’ pathway towards
market access. The new European regulation (MDR
2017/745) will be fully in force in May 2020 and
requires clinical investigation particularly for high-
risk medical devices (HRMDs).
Randomized controlled trials (RCTs) have long
been recognized as the gold standard for evaluating
the effectiveness of drugs. Conducting an RCT takes
a great deal of time and financial resources, and great
rigour in trying to isolate the specific effect of the
intervention under study. Compared with drugs,
HRMDs have specific features such as long-term use
and unknown interactions with the human body, the
means of explanting and replacing implantable
devices, the user's skills, the human-machine
interface, the management of data-flow generated,
etc. These specificities require specific evaluation
methods to generate better clinical evidence.
Adaptive methodologies have been developed as an
alternative to the traditional RCT design.
Even though the legislation, particularly
American legislation with the Food and Drug
Administration (FDA), qualifies adaptive
methodologies as “modern” and “new” methods, a
large number of these concepts are old and have
remained unused for many years faced with the
hegemony of RCTs.
The use of adaptive methods in designing clinical
studies has become a major challenge to the
evaluation of the safety and efficacy of a medical
device, faced with the specificities of the field and the
significant financial and temporal restrictions of this
industry composed mainly of start-ups and SMEs. To
do this it is necessary to find methods that take the
specificities of the medical device into account.
Several types of clinical studies may be carried out
according to the different phases of the device’s
development.
The clinical phase is generally split into two
stages, a first stage of collecting information about
safety and performances of the device. This
information is collected during feasibility studies or
clarifications (implantation technique, patient
characteristics, judgement criteria) and a second stage
to evaluate the device’s clinical efficacy in pivotal
evaluation studies to demonstrate the risk-benefit
ratio.
This work consists of reviewing methods that may
be used in the clinical evaluation of high risk medical
devices.
Vidal, C., Beuscart, R. and Chevallier, T.
Contribution of Methodologies Adapted to Clinical Trials Focusing on High Risk Medical Devices.
DOI: 10.5220/0009374503370343
In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 1: BIODEVICES, pages 337-343
ISBN: 978-989-758-398-8; ISSN: 2184-4305
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
337
2 CLINICAL INVESTIGATION
Rather than “clinical trial”, the term “clinical
investigation” is generally used in Europe in
reference to research on medical devices. The
expression “clinical investigation” is thus defined in
the ISO 14155 norm, “Clinical investigation on
medical devices for human subjects”, as being “... any
study systematically designed and planned for use on
human subjects, undertaken to check the safety and /
or performance of a specific device.” The term
“clinical investigation” is defined in a slightly broader
way in the American regulations (42 USCS § 1320a-
7h (e)) as being “any experiment involving one or
several human subjects, or products arising from the
human body, and in which a drug or medical device
is administered, dispensed or used.”
Clinical investigations are subject to scientific and
ethical examination. The protocol for clinical
investigation includes justification, objectives,
design, methodologies, control, how to conduct the
clinical investigation and the documentation relative
to results and the analysis method concerning it. The
level of evidence of a study is characterized by its
capacity to answer the question being asked. The
randomised controlled trial is the experimental plan
that offers the highest level of evidence to
demonstrate the efficacy of a device relative to a gold-
standard therapy. However, certain specificities of
medical devices make this type of trial difficult to
perform.
The main limits of resorting to a randomised
controlled trial for medical devices are the
impossibility to randomise patients, the device’s short
life-cycle, the small size of the target population, the
difficulty of double-blinding, the low acceptability of
patients and practitioners, the choice of comparator
and the operator-dependent nature of the medical
device.
Besides, classical trials are often long, which is
incompatible with the evaluation of the medical
device whose life-cycle is short and this can hinder
access to innovation. When the trial is non-
conclusive, this leads to the inclusion of lots of
patients in a pointless trial with inefficient treatment.
When the trial is conclusive with a very effective
device being tested, this poses the problem of patients
in the comparator group not having the chance of
access to progress and delayed access to progress.
For medical devices designed to compensate for
handicap, there is a potential loss of quality of life for
the patients who might be able to benefit from them.
Clinical trials may be expensive and this deters
certain small and medium-sized medical device
companies which, in turn, delays or prevents access
to new technologies and medical progress for patients
and users. It is therefore essential to find new methods
of clinical investigation centred around all these
issues.
3 ADAPTIVE METHODS
3.1 Guides
The first part of this work consisted of gathering all
the available guides in the field of clinical evaluation
of medical devices, and publications on that theme.
The following works were used:
Methodological choices for the clinical
development of medical devices; HAS evaluation
report dated October 4
th
, 2013.
Methodological specificities of the clinical
evaluation of a connected medical device (CMD);
HAS report on the elaboration of the guide on the
specificities of clinical evaluation, in view of its
access to reimbursement dated January 29
th
, 2019.
Bernard A, Vaneau M, Fournel I, Galmiche H,
Nony P, Dubernard JM. Methodological choices
for the clinical development of medical devices.
Med Devices (Auckl). 2014 Sep 23;7:325-34.
Guideline on clinical Trials in small populations;
Committee for medicinal products for human use
on 27 july 2006.
Guidance for the use of Bayesian Statistics in
Medical Device Clinical Trials; Guidance for
industry and FDA Staff on February 5, 2010.
Adaptive Designs for Medical Device Clinical
Studies, Guidance for Industry and Food and Drug
Administration Staff, Document issued on July
27, 2016.
3.2 Improve Acceptability by Doctors
and Take into Account the
Operator-dependent Nature
When one arm in the study is less attractive than the
other, studies may be carried out according to a Zelen
plan or according to a complete cohort pattern. These
types of trials introduce flexibility in the attribution
of treatments and allow better acceptability of the
randomisation by the patients and also give us the
possibility of adjusting the results to the
randomisation.
Zelen Plan (Zelen et al., 1983, Zelen et al. 1990):
The patient’s consent is only requested for the new
treatment and not for the gold-standard treatment
ClinMed 2020 - Special Session on Designing Future Health Innovations as Needed
338
(simple consent). It is also possible to ask the patient
randomised to the experimental group what treatment
he/she wants to receive and to give him/her that
treatment, or even in each arm of the randomization,
ask which treatment the patient would like and to give
the patient the treatment he/she wants to have (double
consent).
The patients are analysed in the groups to which
they were initially randomised and not in the arms of
the treatment being received. This plan is only valid
if there is not too great an imbalance between groups;
that is to say, few patients leaving the study (if these
are not related to the treatment) and if the changes of
are not very frequent (fewer than 10% of patients
changing arms).
This type of pattern might be useful in the high
risk medical device area particularly when the target
population is small and you think the recruitment is
going to be very difficult as in the case of studies
focusing on an implantable device (implanted for a
more or less long duration, possible withdrawal /
difficult withdrawal / very difficult withdrawal /
impossible withdrawal) or an invasive surgical
technique with a less invasive or less restrictive
reference arm (with a drug alternative for example).
Comprehensive Cohort Study (Kearney et al.,
2011, Torgerson et al., 1998): the pattern consists of
randomising all patients eligible for research and, at a
second stage, given the patients who refuse
randomisation the treatment they refer. In
methodological terms the main pitfall concerns the
absence of group comparability. However, it is
possible to adjust the results on the randomisation.
3.3 Improve Acceptability of Doctors
and Take into Account the
Operator-dependent Nature
When certain centres only use one of the two
techniques under study and do not know the other
technique or only master the one technique and the
result is operator-dependent, it is possible to use a
trial based on expertise or a cluster trial (or a Stepped
Wedge Cluster trial) to increase the participation of
doctors and the reliability of the evaluation.
Trial based on Expertise (Devereaux et al.,
2005
): in this case the patients are randomised to the
doctor or team that masters the intervention or
technique (for example, prosthetic hip implant
surgery). The doctor only performs the procedure he
fully masters. In this case, the doctor is device user
and he is directly involved in evaluating this. For each
study arm, the doctors master the technique that they
are going to use and have reached the technical
plateau, which avoids any imbalance between the two
groups of the trial during the evaluation and is also
more ethical. This type of trial is still little used. It is
very pertinent when the techniques are different and
complex.
Cluster Trials and SWCs (stepped wedge
cluster) trials (Barker et al., 2016): With this type of
trial, groups of individuals are randomised (hospitals,
services, care units, doctors) and not individuals.
SWC trials are suitable when you want to gradually
implement a new strategy or a new technique without
going back to the previous one.
Centres start with the gold-standard technique and
the time when each centre switches over to the new
technique is randomised. The group experimenting
the new technique can be compared both to itself
based on the initial measures performed on that group
and with the measures from the other patients who are
using the gold-standard technique (independent,
homogeneous control group).
This type of design may be useful when
evaluating a new device, a new technology which is
to be gradually introduced (for example a new device
which is too expensive to use over several centres in
the same area) but the number of clusters must be
sufficient to ensure sufficient statistical power and the
participation of centres/ services/ doctors must be
good especially as these trials may be long
(monitoring of inclusions and motivational strategy to
be established on the scale of the cluster).
3.4 Compensate for a Small Target
Population
When the target population is small, it is important to
optimise and maximise the information collected on
the patients in the study. In some cases, it is possible
to test several strategies on the same patients.
Cross-over Trial (Fuehner et al., 2016,
Haddad et
al., 2010): In this type of trial, each patient receives
two study treatments (or more according to a factorial
design). A weaning period is provided for after the
patient has been given the first treatment. It is the
order of administering the sequences of treatment that
is randomised. This type of design is suitable for
stable pathologies and when judgement criteria can be
read independently over the two periods. The interest
of this type of design is divide by at least two the
numbers planned for the trial and therefore reduce the
duration of the trial. This type of trial may be
proposed in cases of evaluating high risk devices
whose installation and use are not operator-dependent
or if the technical plateau has been reached for all the
investigators before setting up the trial.
Contribution of Methodologies Adapted to Clinical Trials Focusing on High Risk Medical Devices
339
SnSMART Trial (Small n Sequential Multiple
Assignment Randomized Trial) (Tamura et al., 2016,
Wei et al., 2018, Meurer et al., 2017): This type of
trial can be used when a patient is likely to receive
several therapeutic sequences until he/he achieves the
treatment aim (complete recovery, remission, etc).
The sequences are predetermined beforehand and at
the end of each sequence the randomisation is adapted
to orient patients either to pursue their ongoing
treatment if the response is favourable or to use one
of the alternatives being tested in the event of non-
response. The number of arms being tested may be
adapted, if an arm turns out to be ineffective, it can be
removed. These trials potentiate the numbers and may
be used in cases of pathologies focusing on small
target populations (SnSMART). This type of trial is
interesting because it uses the information from the
different sequences to compare therapeutic strategies
and leads to the inclusion of fewer patients.
3.5 Introduce Flexibility to Take
Technological Evolution into
Account and Accelerate and
Optimise Clinical Development
In order to take technological evolution into account
and accelerate clinical development and product
launching whilst allowing early terminations
(futility/efficacy) or protocol adjustments
(evolution/suppression of an arm), it is possible to use
tracker design trials, sequential trials, MAMS trials
and adaptive trials (detailed further on).
These trials rely on planned intermediate analyses
which allow the investigator to glean information
which is useful for adapting the development
strategy. They are particularly interesting in the
context of clinical evaluating medical devices.
Tracker Trial Design (Lilford, et al., 2000): This
type of trial was proposed to evaluate new
technologies. The principle consists of following the
evolution of the technology in the trials based on
flexible protocols without a duration of numbers fixed
beforehand and based on information obtained during
intermediate analyses. It is therefore possible to
interrupt a trial early on if the technique is efficient,
detect poor performances and guide new
developments.
Sequential Trials (Hamilton et al., 2012): The
principle of sequential trials consists of planning
intermediate analyses in order to be able to conclude
early on. The conclusion focuses either on the very
high efficacy/tolerance of the experimental arm
compared with the control arm if the results observed
on the first patients are very promising, that is to say,
beyond what was initially expected, or on its
inefficacity (futility) if the results observed are below
what was initially expected. With this type of trial, it
is possible to quickly conclude on the main criterion.
Multi-Arm Multi-Stage trials (MAMS) (Simon
et al., 1985): MAMS trials are used in the context of
a medical device’s accelerated development plan. In
fact in this type of trial, sequential trials are gathered
into one single protocol (Redman et al., 2015) (e.g.:
several competitive devices with one control arm).
The control group is not obligatory but it is
recommended. The attribution of patients to each arm
is randomised. The arms which do not fulfil the
conditions for minimum efficacy (futility) during the
intermediate analyses are removed and only the most
efficient arms are retained. The first phase is not
directly comparative, the second phase gives us the
probability of selecting the best treatment compared
with the others and the control arm is used to
“estimate” the size of the effect.
4 ADAPTIVE TRIALS
4.1 Principle
With adaptive trials it is possible to modify items in
the protocol during the study, based on data collected
during the planned intermediate analyses without
compromising the integrity and the validity of the
study.
With adaptive methods it is also possible to
strengthen the clinical evaluation of medical devices
by authorising the analysis of lots of evaluation
criteria, carrying out several intermediate analyses,
early terminations in the event of inefficacity,
allocating patients to the most promising arms, re-
evaluating the sample-size and, more especially,
redefining the target population.
These methods also make it possible to combine
the early exploratory phases with the demonstrative
phases which may make it possible to accelerate and
optimise the development and implementation of
innovative devices.
It is also possible with these methods to optimise
the feasibility phases and confirmatory phases by,
proposing much broader, adaptive feasibility trials
leading to better-sized pivot trials or by proposing
adaptive confirmatory trials testing several
hypotheses as required, which would reduce the
number of feasibility studies throughout the course of
the product’s development.
Group sequential design and adaptive sample-size
adjustment were used frequently to make study
ClinMed 2020 - Special Session on Designing Future Health Innovations as Needed
340
durations shorter and include a smaller number of
subjects.
These methods may therefore make it possible to
reduce the requirements in terms of resources, time
necessary to finish the studies and increase the
chances of the study’s success.
There are several possible types of adaptation.
4.2 Response-adaptive Randomization
Trials
The aim of this type of pattern is to treat a maximum
number of patients with the best treatment under trial
and to minimize the number of subjects necessary in
the trial by introducing the possibility of an
anticipated stop.
It may also be used in trials with several arms. It
involves first randomising the patients with a
balanced ratio then, gradually and throughout the
trial, based on information gathered during the
intermediate analyses it is possible to modify the
affectation ratio in order to orient more patients
towards the most effective treatment (Jiang, F, et al.,
2013).
This type of design is an alternative to the multi-
stage multi-arm (MAMS) trials seen above (Wason et
al., 2014, Wathen et al., 2017).
4.3 Sample Size Reassessment Trial
At the time of the intermediate analyses it is possible
to re-evaluate the number subjects necessary for the
rest of the trial if the effect observed seems less than
what was expected at the beginning of the trial
(Magirr et al., 2016).
A misspecification of the expected treatment
effect may result in an underpowered or overpowered
trial. In the flexible framework, the remainder of a
design can be modified at an interim analysis.
In an adaptive trial it is therefore possible to
recalculate the number of participants and to increase
the power of the trial based on new hypotheses
without compromising the validity of the study.
4.4 Seamless Trials
These are trials for which the feasibility and pivot
phases follow on from each other in the same trial
(Thall, 2008). The two phases are based on
complementary criteria (for example: survival
without progression and overall survival).
Certain arms can be removed due to inefficacity
and only the most powerful arms are pursued in the
pivot study.
One control group may be included at the
beginning of the pivot phase or before it.
4.5 Adaptive Enrichment
These are trials for which we observe, during an
intermediate analysis, a better response to treatment
in one of the sub-groups of patients (Simon et al.,
2013, Lai TL et al., 2019).
The underlying idea is therefore to study the effect
of the treatment in the sub-group whose size is not
suitable for analysis beforehand. The eligibility
criteria for the trial are modified and the sample-size
is recalculated so that the size of the sub-group is
sufficient in each arm.
5 BAYESIAN METHODS
5.1 Principle
Bayesian approaches may be used to implement and
analyse clinical trials. They are used because they
give the possibility of combining information
obtained before the trial “prior information”
(previous studies, expert opinion, literature…) and
information obtained during the trial “current
information” to formulate or reformulate a rule for
decision-making.
In a Bayesian clinical trial, any uncertainty about
a parameter is described according to probabilities,
which are then updated during data-collection for the
trial. The probabilities are set beforehand based on
previous data and the probabilities are estimated a
posteriori from the data obtained during the trial.
There are no statistical tests but the probability of the
treatment under experimentation being effective has
a 95% credibility interval. However, it is very
important that the a priori information used does not
influence the final result too much (sensitivity
analysis required). The quality of information
supplied a priori is therefore a key element in the
credibility of results.
5.2 Bayesian Medical Device Trials
Bayesian methods has been supported by the US
Food and Drug Administrations (FDA) Center for
Devices and Radiological Health for medical
device clinical trials and are used in trials on
medical devices (Pennello et al., 2008, Campbell et
al., 2011, Campbell et al., 2016).
Pennello et al. 2008, explain how these analyses
are particularly suitable in this case: “Device trials
Contribution of Methodologies Adapted to Clinical Trials Focusing on High Risk Medical Devices
341
can be particularly suitable for Bayesian analysis. For
example, if a therapeutic device has evolved in
relatively small increments from previous
generations of the same type of device, then prior
information from the trials of the previous devices
can be predictive of the safety and effectiveness
profile of the new device (Allocco et al., 2010). The
reason the previous trials can be predictive is that the
mechanism of action of a therapeutic device is often
physical, implying a local effect that is often
predictable. In contrast, the mechanism of action of
pharmaceuticals is pharmacokinetic, implying
systemic effects from similar but not identical
formulations, which are often unpredictable. Other
potentially reliable sources of prior information for
device trials include clinical trials of the device
conducted overseas, patient registries, pilot studies,
studies of the device on similar patient populations,
and perhaps nonclinical studies. Historical controls
can also represent prior information for the control
arm of a randomized controlled trial”.
The information collected beforehand is generally
based on previous studies on the same device or on a
similar device ideally under similar conditions of use
(same technique used, training of similar doctors with
the same experience), on the same target population
with the same type of management; it comes
especially from designers (engineers), users
(clinicians, patients) and the academic world
(experts).
They are a more flexible alternative to classical
methods (frequentist approach). They are used to
adapt the randomisation according to the responses
observed (see Bayesian adaptive randomisation).
These methods also make it possible to compare
several sub-groups of patients, several criteria,
several time sequences because multiplicity is
managed better Bayesian statistics. It is also possible
to take missing data into account and to predict an
event depending on what has been observed in other
patients throughout the trial. The underlying
hypothesis is that the patients of a same centre, a same
trial or a same group of trials focused on the same
device or on a similar device are interchangeable.
Meta-analyses also use Bayesian methods to take into
account the heterogeneity between trials and between
groups of trials (for example several versions of the
same device).
6 DISCUSSION
In this review, we noted that there have been many
adaptive methods for decades, but their use is recent
and mainly in the pharmacological area. Adaptive
methodologies have most often been used in
oncology.
Adaptive methods may respond to the
specificities of clinical investigations on high risk
medical devices. Nevertheless, so far they have been
very little used in that area (Ribouleau et al., 2011)
even though a few published examples can be found
in the literature. This observation may also come from
a more general situation concerning medical devices
which most of the time are released without having
undergone a proper clinical investigation. And even
though since 1993 the European ruling has mentioned
the obligation for each new medical device, whatever
its risk category, to undergo a clinical evaluation to
obtain CE marking, few clinical studies are indexed
before they obtain the CE mark in Europe.
These “new” methods have encountered many
suspicions, and the regulatory authorities in charge
evoke methodological failings or data-collection
problems specific to adaptive designs, which delay
the process of product approval. The FDA and the
EMA have had mixed experiences with adaptive
designs (Collignon et al. 2018, Elsäßer et al., 2014).
Experiences have shown that applicants need to
meet early and often with regulators. Adaptive design
and Bayesian clinical trials need to be prospectively
designed and require extensive pre-planning and
model-building from the prior information to
mathematical modeling.
Involving regulation authorities early in the
conceptualization of the adaptive design improve
adoption and implementation of that trial.
Adaptive design and Bayesian clinical trials
require highly technically trained statisticians and
programmers. A particular pedagogical attention
should therefore be paid to accustom all the
stakeholders, and particularly the scientists in charge
of regulation before and during these trials, to these
new uses of new methodologies.
7 CONCLUSION
Overcoming methodological difficulties in
conducting clinical trials is a major challenge.
Barriers encountered in the field of medical devices
lead stakeholders to use new methodologies.
Adaptive methods could be used and has been the
subject of several recent reviews (Bothwell et al.,
2018).
Besides, various studies explored specific aspects
of adaptive trials (Guetterman et al., 2017), including
attitudes and opinions regarding confirmatory
ClinMed 2020 - Special Session on Designing Future Health Innovations as Needed
342
adaptive clinical trials and obstacles to using them
(Meurer et al., 2016, Guetterman et al., 2015).
ACKNOWLEDGMENTS
We wish to thank Teresa Sawyers, Medical Writer at
the B.E.S.P.I.M. for translating this work into
English.
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