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Approach for reporting master protocol study designs on ClinicalTrials.gov: qualitative analysis

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Objective: To describe an approach for reporting master protocol research programs (MPRPs) that is consistent with existing good reporting practices and that uses structured information to convey the overall master protocol and design of each substudy. Design: Qualitative analysis. Data sources: ClinicalTrials.gov trial registry. Main outcome measures: Established goals and related practices of the trial reporting system were outlined, examples and key characteristics of MPRPs were reviewed, and specific challenges in registering and reporting summary results to databases designed for traditional clinical trial designs that rely on a model of one study per protocol were identified. Results: A reporting approach is proposed that accommodates the complex study design of MPRPs and their results. This approach involves the use of separate registration records for each substudy within one MPRP protocol (with potential exceptions noted). Conclusions: How the proposed approach allows for clear, descriptive, structured information about each substudy's prespecified design and supports timely reporting of results after completion of each substudy is described and illustrated. Although the focus is on reporting to ClinicalTrials.gov, the approach supports broader application across trial registries and results databases. This paper is intended to stimulate further discussion of this approach among stakeholders, build awareness about the need to improve reporting of MPRPs, and encourage harmonization across trial registries globally.
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RESEARCH
thebmj
BMJ
2022;377:e067745 | doi: 10.1136/bmj-2021-067745 1
Approach for reporting master protocol study designs on
ClinicalTrials.gov: qualitative analysis
Rebecca J Williams,1 Heather D Dobbins,1 Tony Tse,1 Sandy D Chon,2 David Loose,2
Gisele A Sarosy,3 Sheila A Prindiville,3 Frank W Rockhold,4 Deborah A Zarin5
ABSTRACT
OBJECTIVE
To describe an approach for reporting master protocol
research programs (MPRPs) that is consistent with
existing good reporting practices and that uses
structured information to convey the overall master
protocol and design of each substudy.
DESIGN
Qualitative analysis.
DATA SOURCES
ClinicalTrials.gov trial registry.
MAIN OUTCOME MEASURES
Established goals and related practices of the trial
reporting system were outlined, examples and key
characteristics of MPRPs were reviewed, and specic
challenges in registering and reporting summary
results to databases designed for traditional clinical
trial designs that rely on a model of one study per
protocol were identied.
RESULTS
A reporting approach is proposed that accommodates
the complex study design of MPRPs and their
results. This approach involves the use of separate
registration records for each substudy within one
MPRP protocol (with potential exceptions noted).
CONCLUSIONS
How the proposed approach allows for clear,
descriptive, structured information about each
substudy’s prespecied design and supports timely
reporting of results aer completion of each substudy
is described and illustrated. Although the focus is on
reporting to ClinicalTrials.gov, the approach supports
broader application across trial registries and results
databases. This paper is intended to stimulate further
discussion of this approach among stakeholders,
build awareness about the need to improve reporting
of MPRPs, and encourage harmonization across trial
registries globally.
Introduction
In this paper, we describe novel issues specific to
the registration and reporting of results for master
protocols and propose an approach to support
transparent, complete, and timely reporting to trial
registries and results databases such as ClinicalTrials.
go v.1 Reporting issues relating to registration and
disclosure of summary results for master protocol
studies are largely unaddressed in the literature but
are key to ensuring that researchers, journal editors,
potential study participants, and other stakeholders
have the information that they need to understand the
overall master protocol, as well as each substudy. We
summarize the goals and practices of the trial reporting
system, define and describe the key characteristics
of master protocols, provide an overview of the trial
reporting system, and discuss the challenges that
master protocol designs pose regarding trial reporting.
We then present an approach to improving the
reporting of master protocols and highlight additional
issues for consideration. We do not directly look at
the design and analytical aspects of master protocols,
which have been discussed in other publications,2-4 but
instead, we focus on how to ensure such designs and
their results are accommodated and clearly reported by
adapting existing good reporting practices. We aim to
build awareness of the need to improve the reporting
of master protocols, stimulate discussion among
stakeholders about our proposed approach and issues
that remain, and encourage harmonization across
trial registries globally. Although our approach refers
specifically to ClinicalTrials.gov, the process has the
potential to be applied broadly to other trial registries
and results databases.
Key characteristics of master protocol research
programs (MPRPs)
Master protocols are being used more frequently across
the clinical research enterprise, including in cancer
research and in response to the covid-19 pandemic.5-8
These types of studies encompass various designs with
dierent names based on specific design features9;
however, all of these studies can generally be described
as “one overarching protocol designed to answer
multiple questions.”10 A master protocol is conducted
with “a collection of trials or substudies that share key
design components and operational aspects to achieve
better coordination than can be achieved in single
1National Center for
Biotechnology Information,
National Library of Medicine,
National Institutes of Health,
Bethesda, MD, USA
2Essex Management,
Coordinating Center for Clinical
Trials, National Cancer Institute,
National Institutes of Health,
Bethesda, MD, USA
3Coordinating Center for Clinical
Trials, National Cancer Institute,
National Institutes of Health,
Bethesda, MD, USA
4Duke Clinical Research Institute,
Duke University Medical Center,
Durham, NC, USA
5Multi-Regional Clinical
Trials Center of Brigham and
Women’s Hospital and Harvard,
Cambridge, MA, USA
Correspondence to: T Tse
atse@mail.nih.gov
(ORCID 0000-0002-9906-6864)
Additional material is published
online only. To view please visit
the journal online.
Cite this as: BMJ ;:e
http://dx.doi.org/10.1136/
bmj-2021-067745
Accepted: 09 May 2022
WHAT IS ALREADY KNOWN ON THIS TOPIC
Master protocol research programs (MPRPs), which consist of a central protocol
describing multiple substudies, challenge the established model for registration
at trial initiation and reporting of summary results aer completion
Condensing study design information specied in the protocol for multiple MPRP
substudies into one registration record obscures important details, such as
analysis population, primary outcome measures, and completion dates for each
substudy
WHAT THIS STUDY ADDS
The approach proposes reporting each MPRP substudy in a separate study record
to allow for meaningful descriptions of each substudy and to better support the
transparency and accountability
Other factors that require further consideration include coordinating the
registration and results reporting of MPRPs, supporting the identication of
MPRP related records, and harmonizing trial registries worldwide
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trials designed and conducted independently.”10
Thus, we use the term MPRP to highlight the use of
an overarching research protocol for coordinating an
evolving set of studies that constitute a program of
research. We use the term substudy to refer to each
individual trial within the MPRP to which participants
can be assigned. MPRPs have been used to investigate
many interventions for a specific disease with an
umbrella or platform design, as well as various
interventions that target a specific genetic subtype of
tumor independent of cancer type with a basket design
(box 1).11-13 MPRPs can use bayesian or other adaptive
techniques for assigning participants after screening to
substudies or for determining when a substudy should
end.
Generally, MPRPs can allow for greater eciency
than the traditional clinical trial model by
coordinating within one shared centralized protocol
and infrastructure for the investigation of multiple
conditions, experimental interventions, or subgroups
across multiple individual clinical trials (sometimes
referred to as arms).8 14 15 For example, the RECOVERY
MPRP (NCT04381936) eciently identified eligible
participants through a centralized process and
assigned participants to substudies evaluating, over
time, specific interventions for covid-19, as evidence
and knowledge evolved. However, the multistudy
nature of MPRPs challenges established reporting
practices for trial registration and disclosure of
summary results that are aimed at improving clinical
research transparency and accountability as well as
mitigating biases within the medical evidence base.116
Specifically, MPRPs, which can use a single protocol
with multiple substudies, disrupt the current model of
one protocol describing one trial in one trial registry
record. The practice of referring to an entire MPRP as a
single trial (eg, by acronym) might imply that a master
protocol should be represented as one study record
in a trial registry. Yet, many master protocols include
plans for a series of substudies that might start,
end, and be analyzed independently of each other
(including designs with a shared control arm that is
fully or partially used in analyses across substudies).
Condensing this information into one study record
can obscure details of the substudies, such as the
end dates and primary outcome measures, thereby
undermining key transparency and accountability
goals of the trial reporting system. In particular,
international trial registries have uniformly adopted
the World Health Organization Trial Registration
Data Set, a standardized collection of structured data
elements describing key study design components.17
Such structured information allows users to search
for and retrieve registered trial records based on
specific study characteristics, for needs ranging
from patients seeking to enroll in trials to systematic
reviewers identifying trials for a specified population,
intervention, comparison, or outcome. However, each
registry record contains only one set of structured data
elements for describing the design characteristics of
one trial. Designs for multiple trials or substudies
can be reported in a free text field of a single record
(eg, dierent start and end dates in the arms and
interventions fields). Yet, such information will not
be consistently described in the same place by study
sponsors across trials and will not be readily identified
by search tools that depend on structured information
for high-precision data retrieval.
Overview of trial reporting system and challenges for
reporting MPRPs
The trial reporting system was designed to track trials at
each stage from registration at study initiation to results
reporting after completion. Specifically, registration of
key protocol information18 at trial initiation serves as
a public record of the trial and provides public access
to key information about its research plan, which was
prespecified in the protocol. Timely updates to registered
information throughout trial conduct help to keep
the public informed. Public reporting of information
on the summary results in a structured format after
trial completion allows for documentation of basic
scientific findings in a standardized format.19 This
display thereby mitigates publication bias and selective
outcome reporting, complements information on the
results available from the biomedical literature, and
facilitates evidence synthesis via systematic reviewers
and other trial landscape analyses. The trial reporting
system depends on timely and complete submission of
information by study sponsors and investigators and
supports important ethical and scientific goals.
On trial initiation, registration on ClinicalTrials.gov
involves extracting key information from the protocol
for a single study and entering it into a set of structured
data elements that support the display, search, and
download of trial records.18 This model relies on each
clinical trial having defined the study start and end
dates based on key prespecified design and analytical
features that uniquely identify and define the unit of
an individual clinical trial. These features include the
following:
• Population: a defined group of participants, as
described in the conditions of interest and detailed
in the eligibility criteria and target enrollment;
• Interventions: study arms and interventions to
which participants are assigned; and
• Comparison and outcomes: primary and secondary
outcome measures, including the specification of
the arms and interventions being compared within
Box: Examples of MPRP study designs and substudies
•Umbrella design: Adjuvant Lung Cancer enricHmEnt Marker Identification and
Sequencing Trials (ALCHEMIST) (eg, NCT02193282), erlotinib hydrochloride for
early-stage non-small cell lung cancer)
11
•Platform design: Randomised Evaluation of COVid-19 thErRapY (RECOVERY)
(NCT04381936), which efficiently adds and removes specific interventions being
studied for covid-19 based on decision algorithm
12
•Basket design: US National Cancer Institute Molecular Analysis for Therapy Choice
(NCI-MATCH) (eg, NCT04439279), MATCH-Subprotocol R involving trametinib for
cancers with BRAF mutations and fusions
13
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the study to evaluate the eect of an intervention on
a health outcome over a defined time frame.
Generally, these key features apply to each substudy
in an MPRP but do not apply to the MPRP as a whole;
that is, each substudy can have dierent protocol
details. In a basket MPRP, such as NCI-MATCH,
each substudy evaluates tumors with a specific
genetic change (that is, a unique population) and an
intervention intended to target that change (that is, a
unique intervention). Unlike a traditional clinical trial,
in which all the arms and interventions are prespecified
in the protocol from the start, one or more substudies in
an MPRP can be prespecified at the outset while other
substudies are conceived of and added later. However,
MPRPs maintain prespecified plans for the analysis of
substudy results, whether pooled across substudies or,
more commonly, analyzed independently. In this way,
an MPRP can be distinguished from a multiarm study
in which results from each arm are compared with
other arms in the study.
After trial completion, information on the summary
results is reported on ClinicalTrials.gov in a tabular
format, by study arm, in four scientific modules
(participant flow, baseline characteristics, outcome
measures and statistical analyses, and adverse event
information); the full study protocol and statistical
analysis plan are also provided.19
Patient and public involvement
The approach described in this article for reporting
MPRPs to trial registries and results databases such
as ClinicalTrials.gov evolved over several years. Our
proposal is based on the authors’ direct experience
with MPRPs, including reviewing submissions of
registration and summary results and working with
investigators, study sponsors, and other stakeholders,
as well as from monitoring the medical literature.
We did not involve patients or the public because
the analysis focused on addressing largely scientific
challenges in registering and reporting results
information for MPRPs with complex designs.
MPRP trial registration and results reporting
Table 1 presents potential benefits and limitations of use
of a single record to report the entire MPRP as compared
with separate records for each component of the MPRP
(screening and multiple substudies). This approach
is based on the experiences of the National Cancer
Institute in managing the reporting of its NCI-MATCH
MPRP, which is also used for examples in table 1.21
Registration information for NCI-MATCH was
initially posted on ClinicalTrials.gov on 19 June 2015
as one study listing four arms. Each reported arm was
intended to represent a separate substudy with its
own start and end dates and separate analysis plan
(each substudy used the same primary and secondary
outcomes). As NCI-MATCH expanded, the National
Cancer Institute changed the way that the MPRP
was registered to better support the scientific and
administrative aspects of reporting.22 The single record
approach had two main limitations: end users could
not easily search for and interpret key details of NCI-
MATCH substudies, including recruiting status and
summary results, and the sponsor (National Cancer
Institute) found updating registration information for
substudy specific protocol amendments burdensome
(table 1). As of 1 April 2022, NCI-MATCH is represented
on ClinicalTrials.gov by one screening record and 19
substudy records (with the possibility of more being
added), with each substudy evaluating a specific
intervention for patients with tumors containing
particular genetic markers (supplemental material).
This multirecord model has facilitated clear and
transparent reporting of results for the six NCI-
MATCH substudies to date and has been adopted for
other National Cancer Institute’s MPRPs, such as the
basket MPRP Paediatric MATCH (NCT03155620 for
the screening trial), the umbrella MPRPs ALCHEMIST
(NCT02194738 for the screening trial), and the Lung
Cancer Master Protocol or Lung-MAP (NCT03851445).
This multirecord approach is generally consistent
with other MPRP related recommendations that
reinforce the concept of substudies as separate entities.
For example, the addition of each substudy as a new
appendix to the main protocol23 and the use of separate
electronic common technical document folders and
separate investigational new drug applications14 or
separate clinical trial authorisations24 for substudies
submitted to regulatory agencies. The National
Cancer Institute’s experience in using separate
protocol documents and study records has helped
limit the complexity of reporting over time, as closed
substudies accumulate and new substudies continue
to be added. Similarly, separate protocol documents
and study records allow for improved tracking of the
sites participating in each substudy and management
of substudy-specific eligibility criteria. The multirecord
approach for reporting MPRPs includes the use of an
overall screening record, if applicable, and one record
for each substudy (fig 1).
MPRP overall screening record
An MPRP screening record can provide information that
is common to all substudies in the MPRP, allowing each
substudy record to focus on that study’s unique details.
The record can include the procedures for assessing
all eligible participants (and the eligibility criteria
common to all substudies), the methods for allocating
participants to substudies or a shared control group,
and an overarching description of the research program.
The screening record is updated over the conduct of the
MPRP and should reflect the date on which the overall
MPRP was opened to screen participants for eligibility
(start date) and the date on which the eligibility
screening ended for all substudies (completion date).
Further attention is needed to optimize the reporting of
other registration data elements. Particularly, whether
the contents of the screening record should be limited
to a description of the screening procedures (eg, listing
only those interventions necessary for screening) or
should the record also include specific key substudy
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information that provides an overview of the MPRP (eg,
listing all interventions being evaluated as potential
treatments in each MPRP substudy). Similarly, a
screening record could focus on outcome measures
related to the screening process, such as the number
of participants whose tumor was sequenced, and the
number of participants assigned to each substudy
based on molecular sequencing.
After screening for all substudies ends, information
on results specific to the centralized screening process
can be added to the screening record. For example,
in the participant flow module, the number started
could include the number of participants screened,
and the number completed could indicate the number
of participants assigned to a substudy. In the adverse
event information module, reporting would be limited
to events collected during screening and would not
include adverse events collected after participants
were assigned to a substudy; these events would be
reported in the relevant substudy record.
MPRP substudy records
When separate study records are used to represent each
substudy in an MPRP, registration and results reporting
on ClinicalTrials.gov generally follow the established
processes for traditional clinical trials. Each study
registration record describes a substudy’s design (eg,
single arm or parallel design randomized multiarm
study), specific eligibility criteria, prespecified outcome
measures, arms and interventions, recruitment status,
and facility locations. The substudy record should also
include information connecting it to the overall MPRP.
Table | Comparison of single and multiple study record approaches for reporting master protocol research programs (MPRPs) to ClinicalTrials.gov, by
trial reporting system goal
Goal Issues to consider, by MPRP reporting approach
Single study record Multiple study records (supplemental material)
Document trial existence
Registration of key protocol details using
required and optional structured data
elements provides a publicly accessible
record of a clinical trial with a unique
identier for reference; systematic
registration also allows the identication
of all trials with the study design
characteristics of interest
Structured data elements are used to describe the overall MPRP but not
for each substudy, potentially causing uncertainty about the participant
groups and design of each substudy.
Structured data elements are used to describe each MPRP
substudy, clearly reflecting the participant groups and
design of each substudy.
Example: Key protocol details for the overall MPRP (NCT02465060v.1*),
with selected details about the subprotocols described only in the
narrative text. Brief title is “NCI-MATCH: Targeted Therapy Directed by
Genetic Testing in Treating Patients With Advanced Refractory Solid
Tumors or Lymphomas (NCI-MATCH)”; enrollment of 3000 participants
(anticipated); four arms, each labelled as a unique subprotocol (F, G, H,
and R) with the respective ve interventions.
Example: Key protocol details provided in structured data
elements for each substudy, such as for Subprotocol R
(NCT04439279v.5). Brief title is “Testing Trametinib as
a Potential Targeted Treatment in Cancers With BRAF
Genetic Changes (MATCH-Subprotocol R)”; enrollment of
35 participants (actual); single arm labelled with the one
assigned intervention.
Track trial progress
Timely updates of key protocol details,
such as recruitment status, changes to
the protocol, and trial milestone dates,
help locate the stage of each trial,
from initiation to completion; potential
participants can nd ongoing trials for
enrollment and a wide range of users can
understand when summary results are
expected
Updates to structured data elements can only document the progress
of the overall MPRP, not for each substudy; progress of individual
substudies can be described using free text data elements, such
information would not be readily and consistently retrievable.
Updates to structured data elements clearly document the
progress of each substudy, thereby allowing the retrieval
of key subprotocol details with precision.
Example: Substudy tracking information limited to a narrative format
in free text data elements (eg, arm information), with structured data
elements used only for tracking the overall MPRP. Overall recruitment
status is “recruiting,” if at least one subprotocol is “recruiting” (even if
others are “completed”); primary completion date anticipated for June
2022, when the last substudy is completed.
Example: Tracking information for the 19 subprotocols
listed in the structured data elements available and
updated individually in each study record. Overall
recruitment status includes “active, not recruiting”
(16 substudies), “completed” (two substudies), and
“withdrawn” (one substudy). Eight substudies provide
actual primary completion dates; 11 substudies provide
estimated primary completion dates.
Verify current and historical record
information
Accessing required and optional
information in all record versions allows
users to review trial details for current
and all previously reported protocol
information; users can assess delity to
the prespecied protocol when reviewing
reported results for a primary outcome in
a manuscript20
While the study record provides the most up-to-date information for the
overall MPRP, the history of changes feature allows users to review all
previously posted information as sequentially numbered versions and
compare any two versions. However, the lack of structured details about
substudies limits the usefulness of this function.
MPRP subprotocol records provide the most up-to-date
information for each substudy; the history of changes
feature in each substudy record allows users to review all
previously posted substudy information and compare any
two versions.
Example: Increasing number of subprotocols listed in Overall MATCH
MPRP record over time. NCT02465060v.1 had four subprotocols, using
arm information, in June 2015); NCT02465060v.3 had 10 subprotocols
in August 2015; NCT02465060v.104 had 17 subprotocols in March
2016; and NCT02465060v.318 had 30 subprotocols in March 2017.
Example: Key changes in the subprotocol R record over
time. NCT04439279v.1 had initial subrecord submitted
in June 2020; NCT04439279v.2 had results information
submitted in February 2021; and NCT04439279v.5 had
additional updates submitted in February 2022.
Access trial results information
Systematic submission and posting of
structured results modules in a tabular
format following trial completion provides
timely access to summary trial results
information independent of, or in
complement to, journal publication; the
use of structured data elements facilitates
the enforcement of results reporting
requirements and mitigates selective
reporting
Structured results reporting modules in ClinicalTrials.gov have been
designed to record ndings from a single study, so reporting meaningful
information is challenging for multiple substudies using a single record
(see results section in table 2).
Structured results reporting modules in ClinicalTrials.gov
can be used to provide clear and meaningful information
for each substudy in individual records, thereby facilitating
understanding of the results of each substudy; reporting
results analyses across substudies or with shared control
groups is challenging without repeating participant
information within records.
Example: Baseline characteristics: reporting for 19 subprotocols
requires 19 table columns; primary outcome measure: reporting for 19
subprotocols, which share one measure (that is, objective response
rate up to three years), requires 19 table columns; secondary outcome
measures: reporting for 19 subprotocols, which share two of the
three secondary outcome measures (that is, progression-free survival,
progression-free survival at six months, and time to progression),
requires three tables with fewer than 19 columns per table.
Example: Of 19 separate substudy records, six have
posted results and 13 have not. When results information
is posted on each record: baseline characteristics were
limited to participants enrolled in each subprotocol;
primary and secondary outcome measures were limited to
outcome measures prespecied in each subprotocol and
information collected from participants enrolled in each
substudy.
Examples are drawn from archived versions of the NCI-MATCH study record and subrecords on ClinicalTrials.gov.21
*An NCT number followed by v.X denotes archived version X of the study record. To view archived versions of a record on ClinicalTrials.gov, click on the “History of Changes” link displayed on the
study record.
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Summary results reported to ClinicalTrials.gov for
each substudy describe findings related to data collected
from the participants allocated to that particular
substudy. In some cases, the prespecified analysis
plan for summary results will include a comparison to
a control, such as data collected from participants in a
shared control group, whether as standard-of-care or
other control (fig 1). Although the term “shared control
group” is used to refer to one group to which participants
are assigned, in practice, the actual set of control
participants analyzed can dier across substudies
because the participants and interventions change
over time, especially if the control is standard of care. If
detailed plans for applying data from the control group
are prespecified in the MPRP protocol,25 representing
information about the specific participants analyzed in
the control group in each substudy registration record
(that is, as the analysis population for the control arm)
would be more informative than as a separate shared
control registration record. This information allows the
relevant analysis groups in the trial (eg, experimental
and control) to be represented and the details of the
shared control specific to that substudy (eg, specific
interventions and attributes of the participants) to be
reported. When reporting results in a substudy record,
the relevant set (or subset) of shared control group
data should be included. Results from participants (or
subsets of participants) in the shared control group
can be reported in the control data for more than one
substudy record.
We exemplify such reporting of a shared control
arm using the trial STAMPEDE (Systemic Therapy in
Advancing or Metastatic Prostate cancer: Evaluation
of Drug Ecacy MPRP; NCT00268476), an MPRP that
is evaluating treatment strategies for prostate cancer.26
STAMPEDE was initiated with one standard-of-care
Screening record
MPRP
ends
MPRP
begins
Pre-MPRP
initiation MPRP
conduct Post-MPRP
completion
Substudy A record
Substudy B record
Experimental arm
Control
Substudy C record
Experimental arm
Control
+ Substudy D record
Experimental arm
Control
Shared control group
Central screening
Experimental arm
Control
Experimental arm
Control
Substudy
ends
Substudy
begins
Registration Updates Results
reporting
Fig | Schematic of a ctional master protocol research program (MPRP) reported using multiple study records. This MPRP consists of a central
screening process, three prespecied substudies (A-C), and a fourth substudy (D) added by protocol amendment. Five study records (green box
enclosure with rounded corners) would be created on ClinicalTrials.gov: a screening record and one record each for substudies A-D. The control in
each substudy includes appropriately selected participants from the shared control group (orange box below experimental arm). The shared control
group is not reported as a separate record; the relevant control participants are reported as a separate arm in each substudy record. The inset shows
key ClinicalTrials.gov reporting events for each study record
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Selected data element Brief description Notes for substudy records
Registration (summary of key protocol items)18
Brief title and acronym A short title for the clinical study written in language
intended for the lay public and including information
on the condition, participants, and interventions
For each substudy, provide information specic to that substudy and indicate that the
substudy is part of an MPRP: include any acronym or other identifying title for both the
MPRP and the substudy. Example (NCT02193282): Erlotinib Hydrochloride in Treating
Patients With Stage IB-IIIA Non-small Cell Lung Cancer That Has Been Completely Removed
by Surgery (ALCHEMIST treatment trial)
Identify a central screening study, indicate that it is part of an MPRP, and include any
acronym or other identifying title for the MPRP. Example (NCT02194738): Genetic Testing
in Screening Patients With Stage IB-IIIA Non-small Cell Lung Cancer That Has Been or Will Be
Removed by Surgery (ALCHEMIST screening trial)
Overall recruitment status Select one: not yet recruiting; recruiting; enrolling
by invitation; active, not recruiting; completed;
suspended; terminated; withdrawn
Indicate the status for each substudy, updating it within 30 days of a change
Select “recruiting” only while the specic substudy is seeking new participants. Example
(ALCHEMIST): of four MPRP related records, the screening study has a status of “recruiting”
(NCT02194738), two substudies are “active, not recruiting” (NCT02595944 and
NCT02193282), and one substudy is “recruiting” (NCT02201992)
Study start date Estimated date when the clinical study opens for
recruitment of participants or the actual date when
the rst participant enrolled
For each substudy, enter the estimated date or the actual date
Primary completion date and
study completion date
Date when the nal participant was examined or
received an intervention for the purposes of nal
collection of data for the primary outcome, and the
date when data collection was completed for all of
the primary outcomes, respectively
For each substudy, enter the date when nal collection of data for the nal participant
occurred for that substudy.
Example (ALCHEMIST): screening study record (NCT02194738) estimates a primary
completion date of 28 September 2026; three substudies list estimated primary
completion dates of 1 July 2024 (NCT02595944), 10 October 2026 (NCT02193282), and
1 May 2022 (NCT02201992)
Brief summary A short description of the clinical study, including
a brief statement of the hypothesis, written in
language intended for the lay public
For each substudy, provide a non-technical description, including the aim of the substudy;
identication as a substudy in an MPRP; explanation of enrollment through a centralized
eligibility screening process and the NCT number of the MPRP screening record, if
applicable
Enrollment Estimated or actual total number of participants
enrolled; the term “enrolled” indicates an individual’s
agreement to participate aer completing the
informed consent process
For each substudy, initially provide the total estimated number of participants to be
enrolled, then update the record with the actual number aer enrollment ends. Include
the estimated and actual number of participants from the shared control group used for
comparison as a control arm, as specied in the protocol or analysis plan
Arms, groups, and
interventions
Prespecied group or subgroup of participants and
the specic interventions (including no intervention
or standard of care) that they are assigned to
receive, according to the protocol
For each substudy, specify the arms to which participants will be allocated and provide a
name for and description of the interventions associated with each arm. List the control
arm, including any shared control arm, for each substudy if it is prespecied to be included
as a comparator in the analysis of results
Outcome measures Planned measures that are important to evaluating
the eects of the intervention
For each substudy, include all prespecied primary and secondary outcome measures.
Example (NCT03213665): The primary outcome for National Cancer Institute’s Paediatric
MATCH is the objective response rate (time frame up to two years)
Primary and secondary outcomes for each substudy should be included in the substudy
record, even if they are the same for multiple substudies in the MPRP
Eligibility Limited list of key inclusion and exclusion criteria for
the selection of participants in the clinical study
For each substudy, describe the key criteria for participants to be assigned to that substudy
(eg, specic biomarker, disease characteristics)
If participants must go through a centralized screening process, list the NCT number and
brief title or acronym of the screening record as the rst inclusion criterion in each substudy
Example (NCT04439279): MATCH-Subprotocol R’s rst inclusion criterion is that patients
must have met applicable eligibility criteria in the Master MATCH Protocol (NCT02465060)
before registration to treatment subprotocol.
Central contact person (or
facility contact)
A person who can answer questions about
enrollment at any study location
For each substudy provide appropriate contact information
If a central screening process is used, ensure that the person whose contact information is
provided can answer questions about centralized screening
References Citations and links to publications and websites that
are relevant to the protocol
For each substudy, include any references that help users to understand the relation
between the substudy and the overall MPRP design
Uploaded study documents (full study protocol document and statistical analysis plan)19
Document upload
information
Full study protocol, statistical analysis plan, and
informed consent forms
For each substudy, we recommend that the protocol document and appendices for that
substudy be uploaded during study registration to assist users in understanding the
substudy’s design, plans for data collection and analysis, and relation to the overall MPRP
For each substudy, the nal protocol and statistical analysis plan are submitted at the time
of results submission
Results (summary results information)19
General Results information, provided in modules as tables
with study arms as columns and summary results as
rows, is generally expected to be submitted by one
year aer the primary completion date
For each substudy, provide results information aer the primary completion date is
reached
Include control arm data in each substudy record as prespecied in the analysis plan. Data
reported for the control arm derived from the shared control group will likely vary across
substudies based on when a substudy took place and when the data were analyzed. Creating
separate records for each substudy facilitates clear reporting of the relevant participants from
the control group included in each substudy analysis
Participant flow A summary table of participants’ progress, by
assignment group, including the number of
participants who started and completed the study;
analogous to a CONSORT flow diagram
For each substudy specify the arms to which participants in that substudy were assigned. If
relevant, include the control arm with participants from the shared control group
Identify the total number of participants that started and completed each arm of the
substudy
Table | Key considerations for selected data elements in reporting master protocol research programs (MPRPs) to ClinicalTrials.gov using multiple
substudy records
(Continued)
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shared control arm and five experimental intervention
arms (NCT00268476v.1). Note, an NCT number
followed by “v.X” (when X is a number) denotes
archived version X of the study record; to view archived
versions of a record on ClinicalTrials.gov, click on
the “History of Changes” link displayed on the study
record. Results of STAMPEDE were then published in
two articles, one presenting findings from three of the
arms (zoledrenic acid, docetaxel, and zoledronic acid
plus docetaxel)27 compared with the shared control
group, and the other presenting findings for the two
other arms (celecoxib and celecoxib plus zoledronic
acid)28 also compared with the shared control group.
More experimental intervention arms have been added
and analyzed independently of the others, including
abiraterone with prednisolone29 and radiotherapy,30
each compared with data collected from patients
assigned to the standard-of-care shared control
group contemporaneously to the experimental arms
(NCT00268476v.50). This pattern of adding new arms
and reporting their results independently indicates
that an MPRP study design is well suited for the
proposed multirecord approach, with each registration
record identifying the prespecified interventions
and analytical comparisons for each substudy. By
contrast, a less common MPRP design plan that
prespecifies the pooling of data across substudies
for analysis might not be appropriate for multirecord
registration of an MPRP.31 For example, a biomarker
strategy design, which was implemented in the TCA
Ovarian Cancer Trial, compared pooled results from
assay-directed assignment of participants to one of
12 biomarker-targeted chemotherapy interventions
(biomarker-strategy arm) to participants assigned by
physician’s choice (control arm).32 Table 2 displays key
considerations for reporting MPRPs to ClinicalTrials.
gov using multiple substudy records.
Additional factors to consider
Although the use of multiple study records greatly
facilitates registration and results reporting for an
MPRP, some challenges remain.
Coordinating registration and results reporting of
MPRPs
MPRPs generally require, and have resulted in,
unprecedented cooperation among public and private
organizations, such as in the ACTIV (Accelerating
covid-19 Therapeutic Interventions and Vaccines)
partnership.6 However, one study sponsor or principal
investigator must take responsibility for each study
record. Maintaining and updating information for the
overall screening record and multiple substudy records
for an MPRP, including uploading study protocol
and statistical analysis plan documents,33 require
careful coordination among partners regarding roles
and responsibilities for reporting.24 An advantage of
reporting MPRPs using multiple substudy records is
flexibility in identifying the most appropriate sponsor
or investigator to be responsible for each study record.
Our experience has been that what might be perceived
as extra burden of managing multiple substudy
records is counterbalanced by the ability to focus the
work of research partners and investigators to their
specific substudies and to facilitate clear and timely
communication about the research design and better
support results reporting for each substudy.
Identication of MPRP related records
Trial registries provide search features to help
researchers, journal editors, potential study
participants, and other stakeholders identify relevant
studies of interest. Researchers, in particular, rely
on such features to understand the landscape for
a condition or intervention. ClinicalTrials.gov does
not include a specialized structured method for
systematically and automatically identifying study
records that are related, including the multiple
substudies that make up an MPRP; however,
study sponsors and investigators can support the
identification of related MPRP study records by
ensuring a brief title and acronym is standardized
for each substudy if a multiple record approach to
reporting MPRPs is used (table 2).24 Registries could
evaluate methods for further facilitating identification
Selected data element Brief description Notes for substudy records
Baseline characteristics A summary table of demographic and baseline
measures, by arm and for the overall study, including
all relevant measures (eg, age, sex, race, and
ethnicity)
For each substudy, specify the number of participants analyzed at baseline and the
baseline characteristics, by arm. If relevant, include the control arm with collected baseline
measures from the shared control group
Outcome measures A summary table with descriptive information for
each primary and secondary outcome measure,
by arm, including any scientically appropriate
statistical analyses
For each substudy, specify the number of participants analyzed, by arm, and report the
results of outcome measures evaluating the eect of an intervention on participants
An MPRP can use the same or dierent outcome measures across substudies. If relevant,
include the control arm with collected data from the shared control group
Adverse event information Three summary tables of anticipated and
unanticipated adverse events for all cause mortality
(all deaths); serious adverse events; and other (not
including serious) adverse events
For each substudy, specify the overall percentage of participants (number aected or
number at risk) with adverse events in each arm and identify each adverse event by system
organ class. If relevant, include the control arm with collected data from the shared control
group
Other
Study record updates33 Made at least once a year, with some data elements
required sooner aer a change
Update each substudy record regularly and with any important changes to the study
protocol
External to the study
record—publications and
other sources34
Include NCT numbers in abstracts of publications
and other communications
For the substudy, include the NCT numbers of both the screening record and the specic
substudy record
Table | Continued
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in a structured way, for example, by adding a data
element that would allow sponsors and investigators
to identify the NCT numbers of all ClinicalTrials.gov
study records related to a single MPRP or by using
other methods for sharing unique identifiers to identify
study records as part of a related research program.
Based on current ClinicalTrials.gov functionality
and the fact that some researchers use one record for
an entire MPRP, users should be aware of potential
challenges related to the multistudy nature of MPRPs
and key data elements.4 21 For example, separate study
records for the overall screening process and for each
substudy could lead to the double counting of studies
related to a specific disease, condition, or intervention
and, similarly, of the number of participants enrolled
and for which results are reported. However, single
record MPRPs could lead to similar (and potentially
worse) problems with overcounting, resulting from the
inability to disaggregate the number of participants
enrolled in specific substudies.
These challenges are not unique to ClinicalTrials.gov
and also apply to other types of trial reporting, such
as in journal publications. Some of the challenges can
be managed, in part, if sponsors and investigators
clearly title MPRP screening and substudy records
and if users use these and other data elements to
help identify potential overlap in MPRP records.
Additionally, inclusion of the relevant NCT numbers
(or other identifiers) for the screening and substudy
records in all communications, such as at the end of
abstracts for published articles as recommended by the
International Committee of Medical Journal Editors,34
can help bolster clear identification of related MPRP
components.
Harmonizing trial registries
We have described an approach to registering a single
MPRP using multiple study records in the context
of the ClinicalTrials.gov registration and results
reporting model. Study sponsors might also have an
obligation to report MPRPs to other trial registries;
therefore, consideration of coordinating MPRP
reporting approaches across registries is important.
A harmonized approach would entail ecient and
reliable registration and results reporting processes
that support sponsors and investigators and minimize
confusion among end users when information about
the same trial is found in multiple places. Because
registries support trial reporting policies and legal
requirements, broad global collaboration and
harmonization across requirements to support this
approach for reporting MPRPs would be welcomed.
Conclusion
The clinical research enterprise is highly dynamic, with
a continuous evolution of study designs to meet new
challenges. The trial reporting system must adapt as
new study designs emerge to ensure that the system can
continue to satisfy the goals of reporting. MPRPs and
their substudies challenge the traditional trial reporting
model, whether via submission to a trial registry and
results database or via dissemination in biomedical
publications. We cannot allow the complexity of
these research designs to undermine the gains that
the research enterprise has made towards ensuring
careful, accurate, complete, and timely reporting. The
approach that we describe here is intended to ensure
that MPRPs are reported in a manner consistent with
the goals of the trial reporting system. MPRP substudy
records could help potential participants to identify
studies of interest, aid researchers and journal editors
in the evaluation of reporting integrity, and mitigate
the impact of publication bias. Overall, we anticipate
that carefully structured reporting of MPRPs and their
substudies across the clinical research enterprise
would enhance understanding of this important
research design and improve communication of the
results in publications and in trial registries and
databases such as ClinicalTrials.gov.
Contributors: All authors conceived the idea, draed the manuscript,
or critically revised the manuscript for important intellectual
content, gave nal approval of the version to be published, and are
accountable for all aspects of the work. The corresponding author
attests that all listed authors meet authorship criteria and that no
others meeting the criteria have been omitted. RJW acts as the
guarantor.
Funding: Supported, in part, by the National Center for Biotechnology
Information of the National Library of Medicine and the Intramural
Research Program of the National Cancer Institute, National Institutes
of Health. The funders had no role in considering the study design or
in the collection, analysis, interpretation of data, writing of the report,
or decision to submit the article for publication. Dr Williams worked on
this article mostly while employed by the National Library of Medicine,
National Institutes of Health. The views expressed in this article
are those of the authors and do not necessarily reflect the views or
policies of the National Institutes of Health. Neither patients nor the
public were involved in any way.
Competing interests: All authors have completed the ICMJE uniform
disclosure form at https://www.icmje.org/disclosure-of-interest/ and
declare: supported, in part, by the National Center for Biotechnology
Information and the Intramural Research Program of the National
Cancer Institute for the submitted work; RJW, HDD, and TT received
support from the National Center for Biotechnology Information of the
National Library of Medicine, National Institutes of Health; SDC, DL,
GAS, and SAP received support from the Intramural Research Program
of the National Cancer Institute, National Institutes of Health; and DAZ
received personal fees from ClinicalTrials.gov (and provided technical
consultation to ClinicalTrials.gov outside the submitted work); no
nancial relationships with any organizations that might have an
interest in the submitted work in the previous three years; no other
relationships or activities that could appear to have influenced the
submitted work.
Ethical approval: Neither patients nor the public were involved in
any way.
Data sharing: No additional data are available.
The lead authors arm that the manuscript is an honest, accurate,
and transparent account of the study being reported; that no
important aspects of the study have been omitted; and that any
discrepancies from the study as originally planned (and, if relevant,
registered) have been explained.
Dissemination to participants and related patient and public
communities: We plan to share this work through an accompanying
opinion piece describing the context and relevance of this approach
to increasing transparency and accountability. We also plan to share it
on social media, post a link on ClinicalTrials.gov, and ensure that the
article is publicly accessible on PubMed Central (as required by the
NIH Public Access Policy).
Provenance and peer review: Not commissioned; externally peer
reviewed.
This is an Open Access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license,
which permits others to distribute, remix, adapt, build upon this work
non-commercially, and license their derivative works on dierent
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terms, provided the original work is properly cited and the use is non-
commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
1 Zarin DA, Tse T, Williams RJ, Rajakannan T. Update on trial
registration 11 years aer the ICMJE policy was established. N Engl J
Med2017;376:383-91. doi:10.1056/NEJMsr1601330
2 Cecchini M, Rubin EH, Blumenthal GM, et al. Challenges with
novel clinical trial designs: Master protocols. Clin Cancer
Res2019;25:2049-57. doi:10.1158/1078-0432.CCR-18-3544
3 Janiaud P, Serghiou S, Ioannidis JPA. New clinical trial designs
in the era of precision medicine: An overview of denitions,
strengths, weaknesses, and current use in oncology. Cancer Treat
Rev2019;73:20-30. doi:10.1016/j.ctrv.2018.12.003
4 Meyer EL, Mesenbrink P, Dunger-Baldauf C, et al. The evolution of
master protocol clinical trial designs: A systematic literature review.
Clin Ther2020;42:1330-60. doi:10.1016/j.clinthera.2020.05.010
5 US Food and Drug Administration. COVID-19: Master protocols
evaluating drugs and biological products for treatment or prevention:
Guidance for industry [nal guidance for industry]. 2021 May.
https://www.fda.gov/regulatory-information/search-fda-guidance-
documents/covid-19-master-protocols-evaluating-drugs-and-
biological-products-treatment-or-prevention.
6 Collins FS, Stoels P. Accelerating COVID-19 therapeutic
interventions and vaccines (ACTIV): An unprecedented partnership
for unprecedented times. JAMA2020;323:2455-7. doi:10.1001/
jama.2020.8920
7 Park JJH, Hsu G, Siden EG, Thorlund K, Mills EJ. An overview of
precision oncology basket and umbrella trials for clinicians. CA
Cancer J Clin2020;70:125-37. doi:10.3322/caac.21600
8 Yee LM, McShane LM, Freidlin B, Mooney MM, Korn EL. Biostatistical
and logistical considerations in the development of basket and
umbrella clinical trials. Cancer J2019;25:254-63. doi:10.1097/
PPO.0000000000000384
9 Siden EG, Park JJ, Zoratti MJ, et al. Reporting of master protocols
towards a standardized approach: a systematic review.
Contemp Clin Trials Commun2019;15:100406. doi:10.1016/j.
conctc.2019.100406
10 Woodcock J, LaVange LM. Master protocols to study multiple
therapies, multiple diseases, or both. N Engl J Med2017;377:62-70.
doi:10.1056/NEJMra1510062
11 Govindan R, Mandrekar SJ, Gerber DE, et al. ALCHEMIST Trials: A
Golden Opportunity to Transform Outcomes in Early-Stage Non-
Small Cell Lung Cancer. Clin Cancer Res2015;21:5439-44. . .
doi:10.1158/1078-0432.CCR-15-0354
12 RECOVERY Collaborative Group. Horby P, Lim WS, Emberson JR,
Maam M et al. Dexamethasone in hospitalized patients with
covid-19. N Engl J Med 2021;384:693-704. doi:10.1056/
NEJMoa2021436.
13 Johnson DB, Zhao F, Noel M, et al. Trametinib Activity in Patients
with Solid Tumors and Lymphomas Harboring BRAF Non-V600
Mutations or Fusions: Results from NCI-MATCH (EAY131). Clin Cancer
Res2020;26:1812-9. . doi:10.1158/1078-0432.CCR-19-3443
14 U.S. Food and Drug Administration. Master protocols: ecient clinical
trial design strategies to expedite development of oncology drugs
and biologics: Guidance for industry [nal guidance for industry].
2022 Mar. https://www.fda.gov/regulatory-information/search-fda-
guidance-documents/master-protocols-ecient-clinical-trial-design-
strategies-expedite-development-oncology-drugs-and.
15 Park JJH, Siden E, Zoratti MJ, et al. Systematic review of basket trials,
umbrella trials, and platform trials: a landscape analysis of master
protocols. Trials2019;20:572. doi:10.1186/s13063-019-3664-1
16 Zarin DA, Fain KM, Dobbins HD, Tse T, Williams RJ. 10-year
update on study results submitted to ClinicalTrials.gov. N Engl J
Med2019;381:1966-74. doi:10.1056/NEJMsr1907644
17 World Health Organization. WHO trial registration data set (version
1.3.1). https://www.who.int/clinical-trials-registry-platform/network/
who-data-set.
18 National Institutes of Health. National Library of Medicine.
ClinicalTrials.gov protocol registration data element denitions for
interventional and observational studies. 2020 Oct.https://prsinfo.
clinicaltrials.gov/denitions.html.
19 National Institutes of Health. National Library of Medicine.
ClinicalTrials.gov results data element denitions for interventional
and observational studies. 2021 Feb. https://prsinfo.clinicaltrials.
gov/results_denitions.html.
20 Zarin DA, Tse T. Trust but verify: trial registration and determining
delity to the protocol. Ann Intern Med2013;159:65-7.
doi:10.7326/0003-4819-159-1-201307020-00011
21 Conley BA, Doroshow JH. Molecular analysis for therapy choice:
NCI MATCH. Semin Oncol2014;41:297-9. doi:10.1053/j.
seminoncol.2014.05.002
22 Yee LM, McShane LM, Freidlin B, Mooney MM, Korn EL. Biostatistical
and logistical considerations in the development of basket and
umbrella clinical trials. Cancer J2019;25:254-63. doi:10.1097/
PPO.0000000000000384
23 Adaptive Platform Trials Coalition. Adaptive platform trials: denition,
design, conduct and reporting considerations. Nat Rev Drug
Discov2019;18:797-807. doi:10.1038/s41573-019-0034-3
24 European Medicines Agency. Complex clinical trials—Questions and
answers. 23 May 2022. EMA/298712/2022. https://ec.europa.
eu/health/system/les/2022-06/medicinal_qa_complex_clinical-
trials_en.pdf.
25 Dodd LE, Freidlin B, Korn EL. Platform trials - Beware the
noncomparable control group. N Engl J Med2021;384:1572-3.
doi:10.1056/NEJMc2102446
26 James ND, Sydes MR, Clarke NW, et al. Systemic therapy for advancing
or metastatic prostate cancer (STAMPEDE): a multi-arm, multistage
randomized controlled trial. BJU Int2009;103:464-9. doi:10.1111/
j.1464-410X.2008.08034.x
27 James ND, Sydes MR, Clarke NW, et al, STAMPEDE investigators.
Addition of docetaxel, zoledronic acid, or both to rst-line long-term
hormone therapy in prostate cancer (STAMPEDE): survival results
from an adaptive, multiarm, multistage, platform randomised
controlled trial. Lancet2016;387:1163-77. doi:10.1016/S0140-
6736(15)01037-5
28 James ND, Sydes MR, Mason MD, et al, STAMPEDE investigators.
Celecoxib plus hormone therapy versus hormone therapy alone
for hormone-sensitive prostate cancer: rst results from the
STAMPEDE multiarm, multistage, randomised controlled trial. Lancet
Oncol2012;13:549-58. doi:10.1016/S1470-2045(12)70088-8
29 James ND, de Bono JS, Spears MR, et al. STAMPEDE Investigators.
Abiraterone for prostate cancer not previously treated with
hormone therapy. N Engl J Med2017;377:338-51. doi:10.1056/
NEJMoa1702900
30 Parker CC, James ND, Brawley CD, et al. Systemic Therapy for
Advanced or Metastatic Prostate cancer: Evaluation of Drug Ecacy
(STAMPEDE) investigators. Radiotherapy to the primary tumour
for newly diagnosed, metastatic prostate cancer (STAMPEDE): a
randomised controlled phase 3 trial. Lancet2018;392:2353-66.
doi:10.1016/S0140-6736(18)32486-3
31 Yee LM, McShane LM, Freidlin B, Mooney MM, Korn EL. Biostatistical
and logistical considerations in the development of basket and
umbrella clinical trials. Cancer J2019;25:254-63. doi:10.1097/
PPO.000000000000038410.1097/PPO.0000000000000384
32 Cree IA, Kurbacher CM, Lamont A, Hindley AC, Love S, TCA Ovarian
Cancer Trial Group. A prospective randomized controlled trial of
tumour chemosensitivity assay directed chemotherapy versus
physician’s choice in patients with recurrent platinum-resistant
ovarian cancer. Anticancer Drugs2007;18:1093-101. doi:10.1097/
CAD.0b013e3281de727e
33 National Institutes of Health, Department of Health and Human
Services. Clinical Trials Registration and Results Information
Submission. Final rule. Fed Regist2016;81:64981-5157. https://
www.federalregister.gov/documents/2016/09/21/2016-22129/
clinical-trials-registration-and-results-information-submission.
34 International Committee of Medical Journal Editors. “Publishing &
editorial issues: Clinical trials – Registration.” Recommendations for
the conduct, reporting, editing, and publication of scholarly work in
medical journals. http://www.icmje.org/recommendations/browse/
publishing-and-editorial-issues/clinical-trial-registration.html#one.
Web appendix: Online appendix
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... Williams et al. showed in their study on the WHO-listed "ClinicalTrials.gov" registry that about 12 % of all studies, a substantial proportion of which are RCTs, had to be terminated prematurely due to problems [19]. The results of an analysis by Chapman et al. are even clearer: In addition to a discontinuation rate of 21 % of all RCTs (81 out of 395 RCTs), only 66 % of the completed studies were published [20]. ...
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Over the years, clinical registries and randomized controlled trials gained acceptance. With increasing experience, it was possible to obtain knowledge of benefits and limitations in both designs. During the last years, the research focus was placed on new study concepts such as register-based randomized controlled trials intending to merge the benefits of evidence obtained by RCTs and clinical registers. In this review, we aim to provide an overview of the evolution and the present stage of clinical trials. While doing so, we outline past experience and look ahead toward improving models for high-quality clinical trials.
... Drug resources like DrugBank, ChEMBL, and ZINC15 that are continually supplemented with novel drugs from a time much before the pandemic era are effectively applied to correlate different experimental observations to druggable compounds that are either approved or under clinical trial [161][162][163][164]. Trial databases such as ClinicalTrials.gov ...
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Objectives Seamless clinical trials have received much attention as a possible way to expedite drug development. The growing importance of seamless design can be seen in oncology research, especially in the early stages of drug development. Our objective is to examine the basic characteristics of seamless early-phase oncology trials registered on the ClinicalTrials.gov database and to determine their results reporting rates. We also aim to identify factors associated with results reporting. Methods Cross-sectional study. We defined seamless early-phase trials as either those registered as Phase 1/2 or Phase 1 with planned expansion cohort(s). Using the ClinicalTrials.gov registry, we searched for interventional cancer clinical trials with primary completion date (PCD) between 2016 and 2020. After trial selection, we performed manual data extraction based on the trial record description and the results posted in the trial registry. We used logistic regression to search for predictors of results reporting. Protocol: https://osf.io/m346x/. Results We included 1051 seamless early-phase oncology trials reported as completed (PCD) between 2016 and 2020. We provided descriptive statistics including the number of patients enrolled, study start date, primary completion date, funding, type of intervention, cancer type, design details, type of endpoints, recruitment regions, and number of trial sites. Overall, only 34.7% trials reported results on ClinicalTrials.gov. The results reporting rates for 24 months was 24.0%. The overall reporting rate for Phase 1/2 studies was over three times higher than for seamless Phase 1. Conclusions Our study provides cross-sectional data on seamless early-phase oncology trials registered on ClinicalTrials.gov. We highlight the challenges of the evolving clinical trial design landscape and the problem of missing results in the seamless design context, which raises serious ethical concerns. Efforts should be made to adapt the functionality of the ClinicalTrials.gov database to emerging clinical trial models.
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Background: Clinical observation has revealed that multiple sclerosis (MS) and autoimmune thyroid disease (AITD) are strongly correlated. The aim of this study was to explore the shared molecular causes of MS and AITD, and to conduct drug rearrangement on this basis, search for comorbidity drugs and feasible drugs for mutual reference between the two diseases. Methods: Based on genome-wide association study (GWAS) data and transcriptome data, susceptibility genes and differentially expressed genes related to MS and AITD were identified by bioinformatics analysis. Pathway enrichment, gene ontology (GO), protein-protein interaction analysis, and gene-pathway network analysis of the above genes were performed to identify a common target pool, including common genes, common hub genes, and common pathways, and to explore the specific pathogenesis of the two diseases, respectively. Drugs that target the common pathways/genes were identified through the Comparative Toxicogenomics Database (CTD), DrugBank database, and Drug-Gene Interaction (DGI) Database. Common hub genes were compared with the target genes of drugs approved for treating MS/AITD and drugs under investigation identified by DrugBank and ClinicalTrials, respectively. Results: We identified a pool of shared targets containing genes and pathways, including 46 common genetic susceptibility pathways and 9 common differentially expressed pathways, including JAK-STAT signaling pathway, Th17 cell differentiation, Th1 and Th2 cell differentiation, PD-L1 expression and PD-1 checkpoint pathway in cancer, etc. In addition, a total of 29 hub genes, including TYK2, JAK1, STAT3, IL2RA, HLA-DRB1, and TLR3, were identified. Drugs approved for treating MS or AITD, such as methylprednisolone, cyclophosphamide, glatiramer, natalizumab, and methimazole, can target the shared genes and pathways, among which methylprednisolone and cyclophosphamide have been shown to be beneficial for the treatment of the two diseases, indicating that these drugs have the potential to become a priority in the treatment of comorbidities. Moreover, drugs targeting multiple common genes and pathways, including tacrolimus, deucravacitinib, and nivolumab, were identified as potential drugs for the treatment of MS, AITD, and their comorbidities. Conclusion: We observed that T-cell activation-related genes and pathways play a major role in the pathogenesis of both MS and AITD, which may be the molecular basis of the comorbidity. Moreover, we identified a variety of drugs which may be used as priority or potential treatments for comorbidities.
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Background Coronavirus disease 2019 (Covid-19) is associated with diffuse lung damage. Glucocorticoids may modulate inflammation-mediated lung injury and thereby reduce progression to respiratory failure and death. Methods In this controlled, open-label trial comparing a range of possible treatments in patients who were hospitalized with Covid-19, we randomly assigned patients to receive oral or intravenous dexamethasone (at a dose of 6 mg once daily) for up to 10 days or to receive usual care alone. The primary outcome was 28-day mortality. Here, we report the preliminary results of this comparison. Results A total of 2104 patients were assigned to receive dexamethasone and 4321 to receive usual care. Overall, 482 patients (22.9%) in the dexamethasone group and 1110 patients (25.7%) in the usual care group died within 28 days after randomization (age-adjusted rate ratio, 0.83; 95% confidence interval [CI], 0.75 to 0.93; P<0.001). The proportional and absolute between-group differences in mortality varied considerably according to the level of respiratory support that the patients were receiving at the time of randomization. In the dexamethasone group, the incidence of death was lower than that in the usual care group among patients receiving invasive mechanical ventilation (29.3% vs. 41.4%; rate ratio, 0.64; 95% CI, 0.51 to 0.81) and among those receiving oxygen without invasive mechanical ventilation (23.3% vs. 26.2%; rate ratio, 0.82; 95% CI, 0.72 to 0.94) but not among those who were receiving no respiratory support at randomization (17.8% vs. 14.0%; rate ratio, 1.19; 95% CI, 0.91 to 1.55). Conclusions In patients hospitalized with Covid-19, the use of dexamethasone resulted in lower 28-day mortality among those who were receiving either invasive mechanical ventilation or oxygen alone at randomization but not among those receiving no respiratory support. (Funded by the Medical Research Council and National Institute for Health Research and others; RECOVERY ClinicalTrials.gov number, NCT04381936; ISRCTN number, 50189673.)
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Purpose Recent years have seen a change in the way that clinical trials are being conducted. There has been a rise of designs more flexible than traditional adaptive and group sequential trials which allow the investigation of multiple substudies with possibly different objectives, interventions, and subgroups conducted within an overall trial structure, summarized by the term master protocol. This review aims to identify existing master protocol studies and summarize their characteristics. The review also identifies articles relevant to the design of master protocol trials, such as proposed trial designs and related methods. Methods We conducted a comprehensive systematic search to review current literature on master protocol trials from a design and analysis perspective, focusing on platform trials and considering basket and umbrella trials. Articles were included regardless of statistical complexity and classified as reviews related to planned or conducted trials, trial designs, or statistical methods. The results of the literature search are reported, and some features of the identified articles are summarized. Findings Most of the trials using master protocols were designed as single-arm (n = 29/50), Phase II trials (n = 32/50) in oncology (n = 42/50) using a binary endpoint (n = 26/50) and frequentist decision rules (n = 37/50). We observed an exponential increase in publications in this domain during the last few years in both planned and conducted trials, as well as relevant methods, which we assume has not yet reached its peak. Although many operational and statistical challenges associated with such trials remain, the general consensus seems to be that master protocols provide potentially enormous advantages in efficiency and flexibility of clinical drug development. Implications Master protocol trials and especially platform trials have the potential to revolutionize clinical drug development if the methodologic and operational challenges can be overcome.
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With advancements in biomarkers and momentum in precision medicine, biomarker‐guided trials such as basket trials and umbrella trials have been developed under the master protocol framework. A master protocol refers to a single, overarching design developed to evaluate multiple hypotheses with the general goal of improving the efficiency of trial evaluation. One type of master protocol is the basket trial, in which a targeted therapy is evaluated for multiple diseases that share common molecular alterations or risk factors that may help predict whether the patients will respond to the given therapy. Another variant of a master protocol is the umbrella trial, in which multiple targeted therapies are evaluated for a single disease that is stratified into multiple subgroups based on different molecular or other predictive risk factors. Both designs follow the core principle of precision medicine—to tailor intervention strategies based on the patient's risk factor(s) that can help predict whether they will respond to a specific treatment. There have been increasing numbers of basket and umbrella trials, but they are still poorly understood. This article reviews common characteristics of basket and umbrella trials, key trials and recent US Food and Drug Administration approvals for precision oncology, and important considerations for clinical readers when critically evaluating future publications on basket trials and umbrella trials and for researchers when designing these clinical trials.
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Background: Master protocols, classified as basket trials, umbrella trials, and platform trials, are novel designs that investigate multiple hypotheses through concurrent sub-studies (e.g., multiple treatments or populations or that allow adding/removing arms during the trial), offering enhanced efficiency and a more ethical approach to trial evaluation. Despite the many advantages of these designs, they are infrequently used. Methods: We conducted a landscape analysis of master protocols using a systematic literature search to determine what trials have been conducted and proposed for an overall goal of improving the literacy in this emerging concept. On July 8, 2019, English-language studies were identified from MEDLINE, EMBASE, and CENTRAL databases and hand searches of published reviews and registries. Results: We identified 83 master protocols (49 basket, 18 umbrella, and 16 platform trials). The number of master protocols has increased rapidly over the last five years. Most have been conducted in the US (n = 44/83) and investigated experimental drugs (n = 82/83) in the field of oncology (n = 76/83). The majority of basket trials were exploratory (i.e., phase I/II; n = 47/49) and not randomized (n = 44/49), and more than half (n = 28/48) investigated only a single intervention. The median sample size of basket trials was 205 participants (interquartile range, Q3-Q1 [IQR]: 500-90 = 410), and the median study duration was 22.3 (IQR: 74.1-42.9 = 31.1) months. Similar to basket trials, most umbrella trials were exploratory (n = 16/18), but the use of randomization was more common (n = 8/18). The median sample size of umbrella trials was 346 participants (IQR: 565-252 = 313), and the median study duration was 60.9 (IQR: 81.3-46.9 = 34.4) months. The median number of interventions investigated in umbrella trials was 5 (IQR: 6-4 = 2). The majority of platform trials were randomized (n = 15/16), and phase III investigation (n = 7/15; one did not report information on phase) was more common in platform trials with four of them using seamless II/III design. The median sample size was 892 (IQR: 1835-255 = 1580), and the median study duration was 58.9 (IQR: 101.3-36.9 = 64.4) months. Conclusions: We anticipate that the number of master protocols will continue to increase at a rapid pace over the upcoming decades. More efforts to improve awareness and training are needed to apply these innovative trial design methods to fields outside of oncology.
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Researchers, clinicians, policymakers and patients are increasingly interested in questions about therapeutic interventions that are difficult or costly to answer with traditional, free-standing, parallel-group randomized controlled trials (RCTs). Examples include scenarios in which there is a desire to compare multiple interventions, to generate separate effect estimates across subgroups of patients with distinct but related conditions or clinical features, or to minimize downtime between trials. In response, researchers have proposed new RCT designs such as adaptive platform trials (APTs), which are able to study multiple interventions in a disease or condition in a perpetual manner, with interventions entering and leaving the platform on the basis of a predefined decision algorithm. APTs offer innovations that could reshape clinical trials, and several APTs are now funded in various disease areas. With the aim of facilitating the use of APTs, here we review common features and issues that arise with such trials, and offer recommendations to promote best practices in their design, conduct, oversight and reporting.
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Purpose: Substantial preclinical evidence and case reports suggest that MEK inhibition is an active approach in tumors with BRAF mutations outside the V600 locus, and in BRAF fusions. Thus, Subprotocol R of the NCI-MATCH study tested the MEK inhibitor trametinib in this population. Methods: The NCI-MATCH study performed genomic profiling on tumor samples from patients with solid tumors and lymphomas progressing on standard therapies or with no standard treatments. Patients with pre-specified fusions and non-V600 mutations in BRAF were assigned to Subprotocol R using the NCI-MATCHBOX algorithm. The primary endpoint was objective response rate (ORR). Results: Among 50 patients assigned, 32 were eligible and received therapy with trametinib. Of these, 1 had a BRAF fusion and 31 had BRAF mutations (13 and 19 with class 2 and 3 mutations, respectively). There were no complete responses; 1 patient (3%) had a confirmed partial response (patient with breast ductal adenocarcinoma with BRAF G469E mutation) and 10 patients had stable disease as best response (clinical benefit rate 34%). Median progression free survival was 1.8 months and median overall survival was 5.7 months. Exploratory subgroup analyses showed that patients with colorectal adenocarcinoma (n=8) had particularly poor PFS. No new toxicity signals were identified. Conclusions: Trametinib did not show promising clinical activity in patients with tumors harboring non-V600 BRAF mutations, and the subprotocol did not meet its primary endpoint.
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Oncology clinical trials are undergoing transformation to evaluate targeted therapies addressing a wider variety of biologically defined cancer subgroups. Multiarm basket and umbrella trials conducted under master protocols have become more prominent mechanisms for the clinical evaluation of promising new biologically driven anticancer therapies that are integral to precision oncology medicine. These new trial designs permit efficient clinical evaluation of multiple therapies in a variety of histologically and biologically defined cancers. These complex trials require extensive planning and attention to many factors, including choice of biomarker assay platform, mechanism for processing clinicopathologic and biomarker data to assign patients to substudies, and statistical design, monitoring, and analysis of substudies. Trial teams have expanded to include expertise in the interface between biology, clinical oncology, bioinformatics, and statistics. Strategies for the design, conduct, and analysis of these complex trials will continue to evolve to meet new challenges and opportunities in precision oncology medicine.