Download Therapeutic Area Data Standards User Guide for Influenza

Therapeutic Area Data Standards
User Guide for Influenza
Version 1.0 Provisional
Prepared by
CFAST Influenza Standards Team
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Notes to Readers



This is the provisional version of the Therapeutic Area Data Standards User Guide for Influenza. It is ready
for initial use, but depends on the completion of other standards before it can be considered final.
This document is based on SDTMIG v3.2.
This TAUG-Influenza package contains the user guide only; no additional documentation.
Revision History
Date
2014-11-25
2014-09-15
Version
1.0
1.0 Draft
Summary of Changes
Provisional
Draft for Public Review
See Appendix F for Representations and Warranties, Limitations of Liability, and Disclaimers
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
TABLE OF CONTENTS
1
INTRODUCTION ................................................................................................................. 4
1.1
1.2
1.3
1.4
1.5
1.6
PURPOSE................................................................................................................................................................ 4
ORGANIZATION OF THIS DOCUMENT .....................................................................................................................5
CONCEPT MAPS .....................................................................................................................................................6
CONTROLLED TERMINOLOGY ................................................................................................................................ 6
RELATIONSHIPS TO OTHER STANDARDS ................................................................................................................6
KNOWN ISSUES......................................................................................................................................................7
2
SUBJECT AND DISEASE CHARACTERISTICS ........................................................... 8
2.1 INFLUENZA BACKGROUND AND SURVEILLANCE ...................................................................................................8
2.2 DIAGNOSIS AND LABORATORY CONFIRMATION OF INFECTION .............................................................................9
2.2.1
Examples for Diagnosis and Laboratory Confirmation of Infection .................................................... 12
2.3 VIRAL RESISTANCE ............................................................................................................................................. 14
2.3.1
Examples for Influenza Drug Sensitivity Testing ................................................................................ 16
3
DISEASE ASSESSMENTS ................................................................................................ 20
3.1 SYMPTOMS AND SEQUELAE ................................................................................................................................. 20
3.1.1
Examples for Symptoms and Sequelae ................................................................................................ 21
3.2 VIRAL SHEDDING/VIRAL LOAD ........................................................................................................................... 23
3.2.1
Examples for Viral Load Assessment .................................................................................................. 25
3.3 IMMUNOLOGIC RESPONSE TO INFLUENZA ANTIGENS ........................................................................................... 26
3.3.1
Examples for Immune Response .......................................................................................................... 29
3.4 ASSESSMENTS OF RESPIRATION AND PERFUSION ................................................................................................ 31
3.4.1
Examples for Respiration and Perfusion .............................................................................................. 31
3.5 CLINICAL OUTCOME ASSESSMENTS AND OTHER INSTRUMENTS ......................................................................... 33
4
ROUTINE DATA ................................................................................................................ 34
4.1 ADVERSE EVENTS ............................................................................................................................................... 34
4.1.1
Examples for Adverse Events .............................................................................................................. 35
4.2 HEALTHCARE ENCOUNTERS AND ASSOCIATED INTERVENTIONS ......................................................................... 37
4.2.1
Examples for Healthcare Encounters and Associated Interventions .................................................... 37
APPENDICES ............................................................................................................................. 39
APPENDIX A: PROJECT PROPOSAL ................................................................................................................................ 39
APPENDIX B: CFAST ORGANIZATIONS ........................................................................................................................ 40
APPENDIX C: CFAST INFLUENZA DEVELOPMENT TEAM ............................................................................................. 41
APPENDIX D: GLOSSARY AND ABBREVIATIONS ........................................................................................................... 42
Appendix D1: Supplemental Qualifier Name Codes ............................................................................................... 43
APPENDIX E: REFERENCES ........................................................................................................................................... 44
APPENDIX F: REPRESENTATIONS AND WARRANTIES, LIMITATIONS OF LIABILITY, AND DISCLAIMERS ........................ 46
LIST OF FIGURES
Figure 1: CDISC Industry-Wide Data Standards...........................................................................................................4
Figure 2: Concept Classification Key for Concept Maps .............................................................................................. 6
Figure 3: Influenza nomenclature12 ............................................................................................................................. 10
Figure 4: HI Titer......................................................................................................................................................... 27
LIST OF CONCEPT MAPS
Concept Map 1: Diagnosis, laboratory confirmation and strain-typing of influenza ................................................... 11
Concept Map 2: Influenza drug sensitivity testing ...................................................................................................... 15
Concept Map 3: Viral load assessment ........................................................................................................................ 24
Concept Map 4: Microneutralization (MN) and Hemagglutination Inhibition (HI) titers ........................................... 28
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
1 Introduction
This Therapeutic Area Data Standards User Guide for Influenza (TAUG--Influenza) is a provisional standard, which
means that it has been published for initial use, but is dependent upon completion of other standards and thus may
involve risk of upcoming change. This TAUG-Influenza was developed under the Coalition for Accelerating
Standards and Therapies (CFAST) initiative.
CFAST, a joint initiative of CDISC and the Critical Path Institute (C-Path), was launched to accelerate clinical
research and medical product development by facilitating the establishment and maintenance of data standards,
tools, and methods for conducting research in therapeutic areas important to public health. CFAST partners include
TransCelerate BioPharma Inc. (TCB), the U.S. Food and Drug Administration (FDA), and the National Cancer
Institute Enterprise Vocabulary Services (NCI EVS), with participation and input from many other organizations.
See Appendix B for a description of CFAST participating organizations.
CDISC has developed industry-wide data standards enabling the harmonization of clinical data and streamlining
research processes from protocol (study plan) through analysis and reporting, including the use of electronic health
records to facilitate study recruitment, study conduct and the collection of high quality research data. CDISC
standards, implementations and innovations can improve the time/cost/quality ratio of medical research to speed the
development of safer and more effective medical products and enable a learning healthcare system.
Figure 1: CDISC Industry-Wide Data Standards
The goal of the CFAST initiative is to identify a core set of clinical therapeutic area concepts and endpoints for
targeted therapeutic areas and translate them into CDISC standards to improve semantic understanding, support data
sharing and facilitate global regulatory submission.
1.1 Purpose
The focus of the TAUG-Influenza is a subset of the most commonly collected data in both vaccine trials and
antiviral treatment trials. This includes, but is not limited to, symptoms of influenza, identification of influenza
virus, viral and immunologic titers, viral resistance, and adverse events. See Appendix A for the project proposal
that was approved by the CFAST Steering Committee.
This TAUG-Influenza describes the most common data needed for influenza studies, so that those handling the data
(e.g., data managers, statisticians, programmers) understand the data and can apply standards appropriately.
Descriptions addressed in this TAUG-Influenza include the clinical situations from which the data arise, and the
reasons these data are relevant for influenza. The overall goal is to provide the metadata needed to assist in the move
toward closer semantic interoperability between health care and clinical trials.
The TAUG-Influenza also strives to define research concepts unambiguously, so that consistent terminology can be
used in influenza studies to enable aggregation and comparison of data across studies and drug programs.
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Finally, the TAUG-Influenza describes how to use CDISC standards to represent data using the Study Data
Tabulation Model (SDTM) and the SDTM Implementation Guide for Human Clinical Trials (SDTMIG). CDASH
and ADaM are not included in version 1.0, but may be added in a later version.
These CDISC standards are freely available at www.cdisc.org. It is recommended that implementers consult the
SDTM v1.4, SDTMIG v3.2, the Virology Therapeutic Area Data Standards User Guide (VR-UG), and the Study
Data Tabulation Model Implementation Guide for Pharmacogenomics and Pharmacogenetics (SDTMIG-PGx) prior
to implementing these influenza clinical data standards. Note: SDTMIG-PGx is under public review at the time of
finalizing this document.
It is important to note that the inclusion of concepts in this user guide should not be construed as a requirement to
collect data on these concepts in any particular study of influenza. The examples included are intended to show
how data of particular kinds can be represented using CDISC standards. Conversely, the absence of examples
covering concepts such as vital signs, demographics, medical history, etc. should not be construed to mean that these
datasets are not needed.
1.2 Organization of this Document
This document is divided into the following sections:





Section 1, Introduction, provides an overall introduction to the purpose and goals of the Influenza project.
Section 2, Subject and Disease Characteristics, covers data that are usually collected once at the beginning
of a study and background data that are collected in most studies.
Section 3, Disease Assessments, covers data that are used to evaluate disease severity, control, or
progression. These are usually collected repeatedly during a study, and may be used as efficacy endpoints.
Section 4, Routine Data, covers background data that are collected in most studies. Only aspects of these
data that arise in influenza studies and that are not covered by existing standards are discussed.
Appendices provide additional background material and describe other supplemental material relevant to
influenza.
A list of domains used in the examples in this document, and the sections in which these examples appear, is given
below:
Domains from SDTMIG
Interventions
CM Concomitant Medications
PR Procedures
Events
AE Adverse Events
CE Clinical Events
HO Healthcare Encounters
Findings
IS
Immunogenicity Specimen Assessments
LB Laboratory Test Results
MB Microbiology Specimen
PF* Pharmacogenomics Findings*
RE* Respiratory Physiology*
VR* Viral Resistance*
Findings About Events or Interventions
FA Findings About
Section
4.2.1
4.2.1
4.1.1
3.1.1
4.2.1
3.3.1
3.2.1,3.4.1
2.2.1
2.3.1
3.4.1
2.3.1
3.1.1, 4.1.1
* Domain is not final.
Domains from SDTMIG-MD
DI – Device Identifiers
Section
3.4.1, 4.2.1
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
1.3 Concept Maps
This document uses concept maps to explain clinical processes and research concepts. Concept maps, also
sometimes called mind maps, are diagrams which include “bubbles” representing concepts/ideas/things and labeled
arrows that represent the relationships between the concepts/ideas/things. They are generally easier to draw and
more accessible than more formal modeling diagrams, such as Unified Modeling Language (UML) diagrams.
The diagrams in this document use the following coding for classification of concepts. This classification is based
on classes in the Biomedical Research Integrated Domain Group (BRIDG) model. These color-symbol pairs have
been used to highlight kinds of things that occur commonly in clinical data and therefore give rise to common
patterns of data. Some concepts are not coded; they have a thinner, black outline, and no accompanying symbol.
These may include the subject of an observation, as well as characteristics, or attributes, of the coded concepts.
Figure 2: Concept Classification Key for Concept Maps
1.4 Controlled Terminology
CDISC Controlled Terminology is a set of standard value lists that are used throughout the clinical research process,
from data collection through analysis and submission. Influenza terminology is either in production or under
development by the CDISC Terminology Team at the time of publication of this document. Production terminology
is published by the National Cancer Institute’s Enterprise Vocabulary Services (NCI EVS) and is available at:
http://www.cancer.gov/cancertopics/cancerlibrary/terminologyresources/cdisc.
CDISC Controlled Terminology is updated quarterly. Because this document is a static publication, it refers readers
to the NCI EVS page for the most current CDISC terminology (at the link given above). For the same reason, this
document cannot claim to use the most current controlled terminology in either the lists of laboratory tests or in the
examples provided; users should not refer to these as the ultimate authority on what terms to use or to not use.
Verify demonstrated terminology against current published terminology before adopting it.
1.5 Relationships to Other Standards
TAUG-Influenza v1.0 is based upon SDTM v1.4 and SDTMIG v3.2. This document does not replace these
foundational CDISC standards or their implementation guides. The user should read those standards and
implementation guides before applying the advice in this user guide. Additionally, TAUG-Influenza v1.0 relies
heavily upon the Virology Therapeutic Area Data Standards User Guide (VR-UG), and the Study Data Tabulation
Model Implementation Guide for Pharmacogenomics and Pharmacogenetics (SDTMIG-PGx). Note: SDTMIG-PGx
is under public review at the time of finalizing this document.
Certain types of data have existing CDASH and SDTM standards that can be used in influenza studies without
additional development or customization, and so are not covered in special detail in this document.
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
1.6 Known Issues




This guide makes use of draft domains and/or domains created as part of other Therapeutic Area User
Guides which are currently under review and subject to change. SDTM modeling examples in this guide
were based on domain rules that were current as of publication. Any subsequent changes to these domains
will be reflected in a point release of this document.
The provisional Virology Resistance (VR) domain provides for a virus nomenclature hierarchy based on
species and strain. Influenza nomenclature commonly makes use of a 3-level hierarchy: species, subtype,
and strain. The lack of an explicit variable to represent subtype does not present a modeling challenge in
strain-typing records since influenza strain names include subtype. However, it does mean that in cases
where influenza is identified and characterized to the level of subtype only (e.g., H1N1), implementers
must make use of the strain variable (VRSTRN) to represent this information. As the VR domain evolves
to include additional layers of nomenclature that allow for a more pure representation of subtype, this guide
will be updated accordingly.
The TAUG-Influenza is piloting an approach where data represented in the Clinical Events domain is
modeled following the rules of Adverse Events domain. Following this approach, only the presence of prespecified secondary infections and influenza symptoms are represented in the CE domain. Information
about the pre-specified clinical events, including solicited events that did not occur for this subject are also
represented in the FACE dataset. This approach is subject to change based user comments.
Example 1 in Section 3.1.1 uses CEEVAL as an indicator that these records came from a patient diary. –
The variable --EVAL has been provisionally approved for use in events domains, but—as used in this
example—may not be sufficient to establish that the source of these records is a patient diary. More
discussion around this topic is necessary.
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
2 Subject and Disease Characteristics
Subject and disease characteristics generally consist of information about the subject including events and activities
that have affected the subject prior to or at the start of the study. For influenza studies, such information may include
diagnostic test results, virus-typing, viral resistance testing, and other characteristics of the virus. Criteria for
admittance to the study may also be included in this category.
2.1 Influenza Background and Surveillance
The term “flu” is often used by the general public to connote a variety of seasonal respiratory infectious diseases
including the common cold. Clinicians who appreciate the distinction between these respiratory infections often
attempt a differential diagnosis based on a patient’s presenting signs and symptoms, particularly when the patient is
judged to be at low risk for influenza-related complications. For example, patients presenting with a cold are more
likely to have nasal discharge, while patients presenting with influenza are more likely to have systemic illness in
the form of body aches, fatigue, and high fever. But these are generalizations that can be misleading given the
substantial overlap in the clinical presentation of different respiratory illnesses. The only definitive way of
attributing an illness to influenza involves laboratory confirmation. Each US state designates sentinel testing sites in
the community where respiratory specimens are collected for reference laboratory testing. This provides
information on whether influenza virus is circulating in the area, and its susceptibility to antiviral drugs. Influenza
virus infection may be diagnosed by signs and symptoms when known to be circulating in the area; by rapid
diagnostic tests; or by reverse transcriptase polymerase chain reaction (RT-PCR); or by viral culture. Influenza
virus may be classified by type (Influenza A, B or C) and by subtype. Types A and B are responsible for the typical
seasonal influenza infections that are transmitted from person to person during outbreaks of disease; to date,
influenza C virus has not been an important cause of human disease. In recent years, many different rapid diagnostic
tests have been cleared for use; however, these differ by influenza type and subtype, specificity, and performance.
Both false positive results and, more commonly, false negative results are problematic. Anti-viral treatment
decisions are generally based on clinical judgment because of the usual delay in results for confirmatory testing.
Ongoing surveillance is important for assessing trends in prevalence and geographic distribution of influenza.
Together with laboratory testing, surveillance is also important for revealing types, subtypes and strains of
circulating influenza viruses. An influenza outbreak is declared when the number of cases exceeds the seasonallyadjusted normal expectancy. The geographic distribution is categorized using the following: sporadic, local,
regional and widespread. When an influenza epidemic (defined as an outbreak of new cases that exceeds the
expected incidence) occurs simultaneously worldwide, it is known as a pandemic. Influenza pandemics typically
occur when a novel strain of the virus emerges and is not covered by the current vaccine or acquired immunity.
Influenza surveillance in the United States is conducted by the Epidemiology and Prevention Branch in the
Influenza Division of the Centers for Disease Control and Prevention (CDC). This branch of the CDC has five
categories of influenza surveillance: (1) virological surveillance by participating laboratories of the World Health
Organization (WHO) and the National Respiratory and Enteric Virus Surveillance System (2) outpatient surveillance
by the U.S. Outpatient Influenza-like Illness Surveillance Network (3) pneumonia and influenza mortality
surveillance, (4) hospitalization surveillance, and (5) geographic spread of influenza (collection by public health
departments)1. The WHO participating laboratories include public health and large medical center laboratories in
the US; the National Respiratory and Enteric Virus Surveillance System is primarily a group of hospital laboratories;
and the outpatient surveillance network is a network of outpatient care providers. Current influenza surveillance
allows the CDC to assess trends in circulating viruses and disease occurrence, but not the number of influenzarelated cases occurring at a specific time during the influenza season or the exact number of influenza-related deaths
for any year. Precise information on mortality is not available due to limitations in reporting, diagnostic testing
practices, and the influence of co-morbidities. While states are required to report (i.e., nationally notifiable) novel
influenza virus infections and laboratory-confirmed deaths due to influenza in children less than 18 years of age, US
states are not required to report adult cases of influenza or influenza-associated deaths. Further, appropriate
diagnostic testing may not be performed. Many sources of mortality information (e.g., death certificates) do not
always list influenza, but instead may list a secondary bacterial infection or death due to co-morbid conditions such
as heart failure. Sophisticated statistical modelling is required to estimate deaths due to influenza. The CDC
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
releases a weekly report (http://www.cdc.gov/flu/weekly/) that summarizes results from these five types of
surveillance.
Influenza disease occurs when the virus is transmitted to the nose or mouth and subsequently evades host defense
mechanisms such as the mucus that lines the epithelial cells of the respiratory tract. The body has two immune
defense responses including innate immunity which is a non-specific first line of defense, and adaptive (or acquired)
immunity which is specific to the invading virus. If the virus manages to evade the body’s innate response and
cause disease, then health must be restored through an adaptive immune response in which either the influenza virus
burden is reduced or the body develops tolerance to the virus 2.
Immunization through vaccines is a deliberate way to induce adaptive immunity by inducing a host response using
attenuated virus or virus-derived antigens. Influenza virus replication is error prone leading to “genetic drift” and
mixing of different virus strains (recombination, genetic shift). For this reason, the virus constantly changes and
may require reassessing and updating vaccines annually. Vaccination is the preferred means of influenza prevention
because protection can last for an entire season; the procedure requires administration only once or twice annually
and is generally safe and well tolerated. The vaccination must be given at least two weeks before exposure to
influenza. There may be a poor match between the vaccine and the exposure strain of influenza, and immunity may
be less robust in some patients (e.g., immunocompromised or elderly patients). Chemoprophylaxis with an antiviral
agent may be useful for selected high-risk patients3. For chemoprophylaxis, the antiviral agent must be taken
throughout the risk period for exposure (posing a possible medication adherence issue), viral strains may be resistant
to the drug, and adverse events may limit use. Often vaccination and chemoprophylaxis are used in combination.
As an example, an outbreak in a healthcare facility may be managed with vaccination and chemoprophylaxis for
about two weeks to allow for development of immunity.
There are two classes of anti-influenza medications available in the United States; adamantanes and neuraminidase
inhibitors. A variety of other antiviral medications have been studied (e.g., aspirin, statins and corticosteroids) or
are currently being studied (e.g., immunoglobulins, tissue protective, and reparatory factors), but so far none have
shown sufficient evidence of efficacy to be considered for routine use outside of controlled trials 2. The commercially
available adamantanes are amantadine and rimantadine that prevent viral replication through the blockade of an ion
channel in the influenza virus; however neither is currently recommended for use by the CDC due to intrinsic
resistance by influenza B and current high levels of circulating resistance by influenza A viruses 4. The
commercially available neuraminidase inhibitors are oseltamivir (Tamiflu®) and zanamivir (Relenza®), both of
which currently have activity against influenza A and B viruses by blocking neuraminidase, a protein on the surface
of the virus that releases newly formed virions5. However, as with all antimicrobial agents, susceptibility patterns
often change (usually decrease) over time and cross-resistance between anti-viral medications is an ongoing
concern6. Of note, other investigational agents may be available during emergencies by expanded access programs
and emergency use authorization7.
2.2 Diagnosis and Laboratory Confirmation of Infection
There are three general methods of tests used to confirm influenza infection8. The first method, viral culture, has
been considered as the traditional reference standard for influenza testing. This method involves introducing samples
containing virus to a culture of cells known to be permissive to influenza infection. A positive result is indicated by
the observation of cytotoxicity (cell death). The advantages to viral culture are its high sensitivity and its ability to
detect novel viruses. Additionally, it provides evidence of replicating virus (of key importance in vaccine
development), and provides a means of amplifying virus for further testing. It has the disadvantages of turn-around
time (days) and need for specialized personnel. Newer versions of viral isolation have improved testing time, but
lose some of the sensitivity and range of virus detection of the traditional culture technique. It is important to note
that viral culture in and of itself cannot identify specific sub-types without additional testing via the other methods
described in this section.
A second method used to test for influenza (or to confirm a positive culture) is based on nucleic acid amplification
techniques (NAAT) known as reverse transcriptase-polymerase chain reaction (RT-PCR). RT-PCR testing is
emerging as the primary method for testing in many hospitals and health care facilities. Compared to traditional
culture technique, RT-PCR has similar or greater sensitivity, can detect some resistant variant viruses that do not
grow in culture, has a more rapid turn-around time (less than 24 hours for conventional RT-PCR and less than 3
hours for newer techniques in development), is more automated, and does not usually require propagation of viable
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virus. Disadvantages to RT-PCR are the need for specialized personnel and costly specialized reagents and
equipment8. The RT-PCR methods are based on proprietary primers and differ in exactly which types/subtypes are
being detected.
Rapid influenza diagnostic tests (RIDTs) are a third testing method for influenza virus. RIDTs are immunoassays
that provide qualitative results (positive or negative) within a short period of time (often less than 15 minutes) and
do not require highly specialized equipment or personnel for interpretation, which makes them especially useful in
outpatient settings. This advantage is offset by the disadvantage that RIDTs lack sensitivity (i.e., some patients with
disease do not test positive), so a negative RIDT cannot be interpreted to mean that anti-viral therapy is not needed.
Antigen testing by direct immunofluorescence assay (DFA) is more sensitive and only has a somewhat less rapid
turn-around time (e.g., 1-2 hours) compared to RIDTs, but requires more specialized equipment and personnel for
interpretation. RIDTs may be designed to detect influenza A only, influenza B only, or both, with or without the
ability to distinguish influenza A from influenza B. All three methods described above are further illustrated in
Concept Map 1: Diagnosis, laboratory confirmation and strain typing of influenza, below.
As mentioned in Section 2.1 above, influenza virus may be further classified by subtype. Influenza A viruses are
subtyped based on viral surface glycoproteins. Two glycoproteins, hemagglutinin (HA) and neuraminidase (NA) are
antigens that react with host (e.g., human) antibodies and are used for subtype classification of influenza Type A.
For the purposes of subtype nomenclature, HA and NA are further abbreviated as H and N, respectively (e.g., H1N1
is a common subtype of Influenza A).
As of 2013, 27 subtypes of H and N glycoproteins had been identified, although most of these were detected in
birds, rather than humans9. In humans, a smaller number of subtypes of influenza A (e.g., H1, H2, H3, N1, N2)
typically circulate and cause disease4. Both influenza Types A and B may be further subdivided by strain of virus.
The CDC and WHO name influenza virus strains using the following sequence of identifying characteristics:
antigenic type, host of origin, geographical origin, strain number (a sequential isolation number), year of isolation,
and for influenza A, the subtype classification using the H and N antigen description. An example using these
classification schemata for an influenza Type A virus would be A/duck/Alberta/35/76(H1N1). For human-origin
viruses, no host of origin designation is given, as shown in Figure 3 below10,11. These strain nomenclature
designations are often reserved for prototypic isolates maintained as reference standards. Therefore, investigators
sometimes append the text “-like” to the end of a strain name for strains isolated from subjects that are determined to
be of the same lineage based on genetic markers.
Figure 3: Influenza nomenclature12
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Concept Map 1: Diagnosis, laboratory confirmation and strain-typing of influenza
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
2.2.1 Examples for Diagnosis and Laboratory Confirmation of Infection
Example 1
This example shows how to represent data from four different rapid influenza diagnostic tests used to enroll subjects in an influenza treatment trial. In accordance
with SDTMIG v3.1.2 and later, SDTMIG findings related to organism identification are represented in the MB domain. Each positive test is confirmed using
either viral culture or RT-PCR. MBGRPID is used to link the rapid test and the confirmatory test. Data on collection method are represented in SUPPMB. The
names of the rapid influenza diagnostic test used are represented in the device domain DI, and linked to the MB domain via SPDEVID.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Row 2:
Row 3:
Row 4:
Shows a negative result from a rapid test that is designed to detect only Influenza A.
Shows a negative result from a rapid test that is designed to detect only Influenza B.
Shows a positive result from a rapid test that is designed to detect Influenza A or B but cannot distinguish between the two.
Shows the confirmatory test as determined by RT-PCR for Subject INF01-03 from row 3. The result is specific to subtype and strain
(A/California/7/2009 (H1N1)-like).
Shows the result of Influenza A from a rapid test that is designed to detect Influenza A or B and can distinguish between the two.
Shows the confirmatory test as determined by viral culture for Subject INF01-04 from row 5. The result is specific to subtype and strain
(A/California/7/2009 (H1N1)-like).
Row 5:
Row 6:
mb.xpt
Row
1
2
3
4
5
6
STUDYID
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
Row
1 (cont)
2 (cont)
3 (cont)
4 (cont)
5 (cont)
6 (cont)
DOMAIN
MB
MB
MB
MB
MB
MB
USUBJID
INF01-01
INF01-02
INF01-03
INF01-03
INF01-04
INF01-04
MBSTRESC
NEGATIVE
NEGATIVE
POSITIVE
A/California/7/2009 (H1N1)-like
INFLUENZA A VIRUS
A/California/7/2009 (H1N1)-like
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SPDEVID
1
2
3
4
MBSPEC
MUCUS
MUCUS
MUCUS
MUCUS
MUCUS
MUCUS
MBSEQ
1
1
1
2
1
2
MBLOC
NOSTRIL
NOSTRIL
NOSTRIL
NOSTRIL
NOSTRIL
NOSTRIL
MBGRPID
1
1
1
1
MBREFID
SAMP0101
SAMP0102
SAMP0103
SAMP0103
SAMP0104
SAMP0104
MBTESTCD
INFAAG
INFBAG
INFABAG
VRIDENT
INFABAG
VRIDENT
MBTEST
Influenza A Antigen
Influenza B Antigen
Influenza A/B Antigen
Viral Identification
Influenza A/B Antigen
Viral Identification
MBMETHOD
IMMUNOASSAY
IMMUNOASSAY
IMMUNOASSAY
REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION
IMMUNOASSAY
FLUORESCENT IMMUNOASSAY
MBORRES
NEGATIVE
NEGATIVE
POSITIVE
A/California/7/2009 (H1N1)-like
INFLUENZA A VIRUS
A/California/7/2009 (H1N1)-like
VISITNUM
1
1
1
1
1
1
VISIT
VISIT 1
VISIT 1
VISIT 1
VISIT 1
VISIT 1
VISIT 1
MBDTC
2011-08-06
2011-08-06
2011-08-06
2011-08-06
2011-08-06
2011-08-06
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
All Rows:
Show how to represent collection method for each of the identification tests.
suppmb.xpt
Row
1
2
3
4
5
6
STUDYID
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
Rows 1-4:
RDOMAIN
MB
MB
MB
MB
MB
MB
USUBJID
INF01-01
INF01-02
INF01-03
INF01-03
INF01-04
INF01-04
IDVAR
MBSEQ
MBSEQ
MBSEQ
MBSEQ
MBSEQ
MBSEQ
IDVARVAL
1
1
1
2
1
2
QNAM
COLMETH
COLMETH
COLMETH
COLMETH
COLMETH
COLMETH
QLABEL
Collection Method
Collection Method
Collection Method
Collection Method
Collection Method
Collection Method
QVAL
NASAL WASH
NASAL WASH
NASAL WASH
NASAL WASH
NASAL SWAB
NASAL SWAB
QORIG
CRF
CRF
CRF
CRF
CRF
CRF
QEVAL
Show the type of assay and the commercial kit name used.
di.xpt
Row
1
2
3
4
5
6
7
8
STUDYID
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
DOMAIN
DI
DI
DI
DI
DI
DI
DI
DI
SPDEVID
1
1
2
2
3
3
4
4
DISEQ
1
2
1
2
1
2
1
2
DIPARMCD
DEVTYPE
TRADENAM
DEVTYPE
TRADENAM
DEVTYPE
TRADENAM
DEVTYPE
TRADENAM
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
DIPARM
Device Type
Trade Name
Device Type
Trade Name
Device Type
Trade Name
Device Type
Trade Name
DIVAL
Rapid Influenza Diagnostic Test
SAS FluAlert A
Rapid Influenza Diagnostic Test
SAS FluAlert B
Rapid Influenza Diagnostic Test
QuickVue Influenza Test
Rapid Influenza Diagnostic Test
BinaxNOW Influenza A&B
Page 13
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
2.3 Viral Resistance
Influenza viruses undergo constant changes through processes known as antigenic drift and antigenic shift.
Antigenic drift refers to the relatively common and evolutionary form of genetic mutations that result in new viral
strains of influenza. Antigenic shift refers to a less common, episodic genetic reassortment between viruses that
leads to a immunologically novel virus with potential for causing widespread and more serious illness13. The result
of antigenic drift or shift is that the amino acids that comprise viral surface proteins mutate and may allow the
influenza virus strain to evade adaptive host immune response and the efficacy of vaccines and/or anti-viral
medications14. The disease severity associated with a novel influenza strain is a function of the virulence factors of
the virus and host defense mechanisms9.
Influenza Types A and B are RNA viruses with a genome that has eight segments. Two of these segments encode
the HA and NA glycoproteins which allow virus access to host cell; three encode polypeptides (PB1, PB2, PA) that
assemble into an RNA dependent-RNA polymerase which replicates and transcribes; one encodes a nucleoprotein
(NP) that is involved in encapsulating virus genome to form a ribonucleoprotein (RNP) particle for the purposes of
transcription and packaging; one encodes matrix proteins [M1 or M2 (or BM2 for influenza Type B)]; and one
encodes interferon antagonist (NS1) and nuclear export protein (NSP) 15. The HA and PB2 are major determinates of
pathogenicity that influence replication efficiencies in the upper and lower respiratory tracts. The NS1 protein
influences cell responses induced by interferon and may interfere with innate immunity. Mutations in NA and the
matrix M2 protein may confer resistance to antiviral agents, thus limiting therapy of acute infection to supportive
care4.
Currently, a small number of influenza viral isolates undergo susceptibility testing to detect antiviral resistance.
Most of this testing information is obtained through general surveillance by organizations such as the CDC and
WHO. Potential drug resistance can be assessed through genotypic and phenotypic testing. Genotypic testing by
various types of sequencing techniques looks for genomic variants that are known to exhibit drug resistance. The
Sanger sequencing method has traditionally been considered the gold standard because of the range of information it
provides and for its availability and affordability compared to the alternatives of newer pyrosequencing techniques
and real-time PCR. The latter techniques, however, can rapidly detect viruses with known resistance patterns4,16.
Phenotypic testing requires viral culture techniques and is based on the ability of an antiviral drug to inhibit viral
replication at clinically relevant concentrations. Currently, antiviral susceptibility testing provides guidance on
antiviral use based on a sampling of influenza virus strains; however, since the antiviral testing is reported weeks
after virus isolation, the results (trends) affect regional recommendations rather than direct patient-specific
treatment.
A major limitation of genotypic assays is that even a single nucleotide change in a virus can cause a substantial
change in assay performance. Phenotypic assays overcome this testing limitation and may provide an overall better
indicator of drug susceptibility4. Neuraminadase inhibition (NAI, or NI) assays can be adapted to determine
susceptibility of neuraminidase inhibitor drugs such as oseltamivir and zanamivir. The assay requires a luminescent
or fluorescent substrate that is cleaved by NA, and instrumentation to detect the level of light emission or
fluorescence. The viral sample is incubated with a range of neuraminidase inhibitor concentrations to identify the
concentration of drug that causes a 50% reduction in NA activity (IC50). The IC50 values of various test viruses are
compared to the usual form of a virus known as the wild type, but the clinically relevant threshold for establishing
resistance is not well-established at this time16. When a cell culture-based assay is used to determine the
concentration at which 50% viral activation is inhibited, the resulting value is referred to as the 50% effective
concentration (EC50). As with the IC50 value for a test virus, the EC50 value of a test virus can be compared to that
of a known reference wild type isolate. Such phenotypic assays have limitations with respect to their sensitivity to
detect shifts in susceptibility versus a reference virus. Investigation of resistance using both genotypic and
phenotypic assays helps to overcome the limitations of each approach. Resistance testing is applicable to establish
population management strategies and is generally not applicable to individual patients because the availability and
lag-time for results limits the usefulness of resistance testing for individualized decisions. The concept map below
further illustrates the principles of viral resistance as described in this section.
Page 14
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Concept Map 2: Influenza drug sensitivity testing
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
Page 15
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
2.3.1 Examples for Influenza Drug Sensitivity Testing
Example 1
This example shows a longitudinal assessment of genetic variation in the influenza neuraminidase gene from two subjects. These assessments look for changes in
the Arginine (R) residue at position 292 in the neuraminidase protein over a period of five days, because this change is known to confer drug resistance 17.
PFORRES shows the one letter amino acid abbreviation more commonly seen in literature. PFSTRESC shows the result using standard Human Genome
Variation Society (HGVS) nomenclature.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Rows 2-3:
Rows 4-6:
Shows that the baseline assessment found no variation in R292 for Subject INF01-01. Note that the experimental result (PFORRES) and the
reference result (PFORREF) are the same. The standard result (PFSTRESC) value of “p.(=)” indicates there is no change detected.
Show that R292 residue mutated to Lysine (K) on Day 2 and remained that way through Day 5 for Subject INF01-01. Note that the
experimental result (PFORRES) has changed to “K.”
Show that the baseline, Day 2, and Day 5 assessments found no variation in R292 for Subject INF01-02.
pf.xpt
Row
1
2
3
4
5
6
Row
1 (cont)
2 (cont)
3 (cont)
4 (cont)
5 (cont)
6 (cont)
STUDYID
INFLU123
INFLU123
INFLU123
INFLU123
INFLU123
INFLU123
DOMAIN
PF
PF
PF
PF
PF
PF
USUBJID
INF01-01
INF01-01
INF01-01
INF01-02
INF01-02
INF01-02
PFSPCIES
PFSTRAIN
INFLUENZA A
H3N2
INFLUENZA A
H3N2
INFLUENZA A
H3N2
INFLUENZA A
H3N2
INFLUENZA A
H3N2
INFLUENZA A
H3N2
PFORRES
R
K
K
R
R
R
PFSEQ
1
2
3
1
2
3
PFGENTYP
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PFGENRI
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
PFTESTCD
AA
AA
AA
AA
AA
AA
PFORREF PFGENLOC PFSTRESC VISITNUM
R
292
p.(=)
1
R
292
p.Arg292Lys
2
R
292
p.Arg292Lys
3
R
292
p.(=)
1
R
292
p.(=)
2
R
292
p.(=)
3
VISIT
BASELINE
DAY 2
DAY 5
BASELINE
DAY 2
DAY 5
PFTEST
AMINO ACID
AMINO ACID
AMINO ACID
AMINO ACID
AMINO ACID
AMINO ACID
PFCAT
PROTEIN VARIATION
PROTEIN VARIATION
PROTEIN VARIATION
PROTEIN VARIATION
PROTEIN VARIATION
PROTEIN VARIATION
PFDTC
2012-03-01
2012-03-02
2012-03-05
2012-03-01
2012-03-02
2012-03-05
Example 2
This example shows how to represent data from an NA inhibition assay assessing influenza susceptibility to a neuraminidase inhibitor during an antiviral
treatment trial. This assessment was done at three time points over a five-day period. Each time point compares a known reference strain to a subject-derived
sample strain that has previously been identified as being of the same lineage based on genetic markers (thus the strain name ending in “-like”). Information
about the sample collection method, analysis software, and software version used to calculate the IC50 values is represented in SUPPVR and linked to the parent
domain via VRSEQ. Information about the commercial kit used is represented in the Device Identifiers domain (DI), and linked to the VR domain via SPDEVID.
Note that the values in VRGENTYP and VRGENRI are chosen based on the target molecule of the study drug, a neuraminidase inhibitor.
Page 16
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Rows 1, 4, and 8:
Rows 2, 5, and 9:
Rows 3, 6, and 10:
Rows 7 and 11:
Row 12:
Show the response of the virus extracted from the subject based on drug concentrations required to produce 50% inhibition of the
standard virus growth.
Show a reference viral sample response based on drug concentrations required to produce 50% inhibition of the standard virus growth.
Show the fold change of the response of the virus extracted from the subject compared to the reference viral sample response based on
drug concentrations required to produce 50% inhibition of the standard virus growth. This is the subject sample result divided by the
reference result. Because these records are derived, VRDRVFL=Y.
Show the fold change of the response of the virus extracted from the subject at follow-up compared to the response of the virus
extracted from the same subject at baseline. The results are based on drug concentrations required to produce 50% inhibition of the
standard virus growth. This is the subject sample follow-up result divided by the subject sample baseline result. Because these records
are derived, VRDRVFL=Y.
Shows the qualitative net assessment of the overall change in susceptibility of subject sample virus over time.
VRORRES/VRSTRESC shows “Reduced Susceptibility”.
vr.xpt
Row
1
2
3
4
5
6
7
8
9
10
11
12
STUDYID
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
Row
1 (cont)
2 (cont)
3 (cont)
4 (cont)
5 (cont)
6 (cont)
7 (cont)
8 (cont)
9 (cont)
10 (cont)
11 (cont)
12 (cont)
DOMAIN
VR
VR
VR
VR
VR
VR
VR
VR
VR
VR
VR
VR
VRSPCIES
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
INFLUENZA A
USUBJID SPDEVID VRSEQ VRGRPID
INF01-01
10
1
1
INF01-01
10
2
1
INF01-01
3
1
INF01-01
12
4
1
INF01-01
12
5
1
INF01-01
6
1
INF01-01
7
1
INF01-01
12
8
1
INF01-01
12
9
1
INF01-01
10
1
INF01-01
11
1
INF01-01
12
1
VRSTRAIN
A/California/7/2009 (H1N1)-like
A/California/7/2009 (H1N1)
A/California/7/2009 (H1N1)-like
A/California/7/2009 (H1N1)
A/California/7/2009 (H1N1)-like
A/California/7/2009 (H1N1)
VRGENTYP
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
PROTEIN
VRDRUG
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
Investigamavir
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
VRGENRI
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
NEURAMINIDASE
VRORRES
0.20
0.21
0.95
0.21
0.22
0.95
1.05
4.18
0.20
21
21
REDUCED SUSCEPTIBILITY
VRTESTCD
IC50S
IC50R
IC50FCR
IC50S
IC50R
IC50FCR
IC50FCB
IC50S
IC50R
IC50FCR
IC50FCB
ICNETAS
VRORRESU
nM
nM
nM
nM
nM
nM
VRTEST
IC50 Subject Result
IC50 Reference Control Result
IC50 Fold Change from Reference
IC50 Subject Result
IC50 Reference Control Result
IC50 Fold Change from Reference
IC50 Fold Change from Baseline
IC50 Subject Result
IC50 Reference Control Result
IC50 Fold Change from Reference
IC50 Fold Change from Baseline
Inhibitory Concentration Net Assessment
VRSTRESC
0.20
0.21
0.95
0.21
0.22
0.95
1.05
4.18
0.20
21
21
REDUCED SUSCEPTIBILITY
VRSTRESN
0.20
0.21
0.95
0.21
0.22
0.95
1.05
4.18
0.20
21
21
Page 17
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Row
VRSTRESU
nM
1 (cont)
nM
2 (cont)
3 (cont)
nM
4 (cont)
nM
5 (cont)
6 (cont)
7 (cont)
nM
8 (cont)
nM
9 (cont)
10 (cont)
11 (cont)
12 (cont)
VRSPEC
MUCUS
VRMETHOD
NEURAMINIDASE INHIBITION ASSAY
NEURAMINIDASE INHIBITION ASSAY
VRANMETH
SOFTWARE ANALYSIS
SOFTWARE ANALYSIS
MUCUS
NEURAMINIDASE INHIBITION ASSAY
NEURAMINIDASE INHIBITION ASSAY
SOFTWARE ANALYSIS
SOFTWARE ANALYSIS
VRDRVFL
Y
Y
Y
MUCUS
NEURAMINIDASE INHIBITION ASSAY
NEURAMINIDASE INHIBITION ASSAY
SOFTWARE ANALYSIS
SOFTWARE ANALYSIS
Y
Y
VISITNUM
1
1
1
2
2
2
2
3
3
3
3
3
VISIT
BASELINE
BASELINE
BASELINE
DAY 2
DAY 2
DAY 2
DAY 2
DAY 5
DAY 5
DAY 5
DAY 5
DAY 5
VRDTC
2011-08-01
2011-08-01
2011-08-01
2011-08-02
2011-08-02
2011-08-02
2011-08-02
2011-08-05
2011-08-05
2011-08-05
2011-08-05
2011-08-05
The table below shows how to represent collection method, analysis software and software version in SUPPVR.
Rows 1, 6, and 11:
Rows 2, 4, 7, 9, 12, and 14:
Rows 3, 5, 8, 10, 13, and 15:
Show the sample collection method used in the NA inhibition assay.
Show the analysis software used to calculate the IC50 values.
Show the version of the analysis software used to calculate the IC50 values.
suppvr.xpt
Row STUDYID RDOMAIN USUBJID IDVAR IDVARVAL QNAM
QLABEL
INFL123
VR
INF01-01 VRSEQ
1
COLMETH Collection Method
1
INFL123
VR
INF01-01 VRSEQ
1
SFTWR
Analysis Software
2
INFL123
VR
INF01-01 VRSEQ
1
SFTWRVER Software Version
3
INFL123
VR
INF01-01 VRSEQ
2
SFTWR
Analysis Software
4
INFL123
VR
INF01-01 VRSEQ
2
SFTWRVER Software Version
5
INFL123
VR
INF01-01 VRSEQ
4
COLMETH Collection Method
6
INFL123
VR
INF01-01 VRSEQ
4
SFTWR
Analysis Software
7
INFL123
VR
INF01-01 VRSEQ
4
SFTWRVER Software Version
8
INFL123
VR
INF01-01 VRSEQ
5
SFTWR
Analysis Software
9
INFL123
VR
INF01-01 VRSEQ
5
SFTWRVER Software Version
10
INFL123
VR
INF01-01 VRSEQ
8
COLMETH Collection Method
11
INFL123
VR
INF01-01 VRSEQ
8
SFTWR
Analysis Software
12
INFL123
VR
INF01-01 VRSEQ
8
SFTWRVER Software Version
13
INFL123
VR
INF01-01 VRSEQ
9
SFTWR
Analysis Software
14
INFL123
VR
INF01-01 VRSEQ
9
SFTWRVER Software Version
15
QVAL
NASAL SWAB
JASPR
1.3
JASPR
1.3
NASAL SWAB
JASPR
1.3
JASPR
1.3
NASAL SWAB
JASPR
1.3
JASPR
1.3
QORIG
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
CRF
QEVAL
The table below shows how to represent the type of assay and the commercial kit name in the DI domain.
Page 18
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
di.xpt
Row
1
2
3
4
STUDYID
INFL123
INFL123
INFL123
INFL123
DOMAIN
DI
DI
DI
DI
SPDEVID
10
10
12
12
DISEQ
1
2
1
2
DIPARMCD
DEVTYPE
TRADENAM
DEVTYPE
TRADENAM
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
DIPARM
Device Type
Trade Name
Device Type
Trade Name
DIVAL
NA Inhibition Assay
NA-XTD KIT
NA Inhibition Assay
NA-STAR KIT
Page 19
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3 Disease Assessments
Disease assessments are typically done repeatedly over the course of the study and are used to evaluate how the
subject is progressing. In influenza, assessments of interest include symptoms, viral shedding, immunologic
response, and tests of respiration and perfusion.
3.1 Symptoms and Sequelae
Upon exposure to the influenza virus, the mean incubation period is two days with viral shedding that begins before
the patient is symptomatic and lasts for up to ten days or longer particularly in children (although viral shedding
rapidly decreases after three to five days). Typical signs and symptoms of an outpatient with an influenza infection
include fever, muscle aches and headaches that usually resolve within five days; and cough and lack of energy that
may last for weeks. Other symptoms may include sore throat and runny nose; children may also have otitis media,
or nausea and vomiting18. This type of presentation is not uncommon with other types of infectious diseases and
must be considered in the differential diagnosis, so a diagnosis based purely on a clinical definition is poorly
predictive for influenza. When combined with epidemiologic data in the setting of a known outbreak or seasonal
influenza activity, presentation with an influenza-like illness is considered as probable influenza and managed as
such.
Some patients with influenza develop severe pulmonary disease and may require intubation and mechanical
ventilation. Other organ dysfunction may occur as a consequence or complication of the influenza infection. For
example, in addition to aggravating pre-existing cardiac conditions, influenza may present as a myocarditis that
leads to cardiogenic shock and death19. Patients may also have nervous system complications from influenza. A
wide variety of neurological and neuromuscular syndromes associated with influenza have been reported, but a
group of syndromes known as influenza-associated encephalopathy is the most common cause of death20.
Secondary bacterial infections also contribute to influenza related mortality especially from bacterial pneumonia
including staphylococcal pneumonia.
During outbreaks of seasonal influenza, patients older than 65 years of age, younger than 5 years of age, and those
with co-morbid conditions are at most risk for complications, hospitalizations, and death 21. However, other groups
may be at risk for more severe disease during epidemics or pandemics, as noted during the 2009 influenza
A(H1N1)pdm09 pandemic when immunocompetent patients less than 65 years of age were most likely to develop
complications. This paradox is thought to be due to very robust immune (inflammatory) response. Other groups at
risk for more severe illness during this outbreak included those patients with major organ dysfunctions, pregnancy,
morbid obesity, and history of smoking, although it is important to note that up to half of the patients had no
underlying medical conditions22.
Page 20
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3.1.1 Examples for Symptoms and Sequelae
Example 1
This example shows a subject from an antiviral treatment trial who experienced one of four pre-specified secondary infections as solicited on a case report form.
The same subject experienced five of eight pre-specified symptoms of influenza, solicited by a patient diary. The subject was evaluated for symptoms of
influenza every day for a total of seven days (additional data not shown) and thus the evaluation interval (CEEVLINT/FAEVLINT) is equal to “in the last day”
using ISO 8601 format (-P1D). The presence of pre-specified secondary infections and influenza symptoms are represented in the Clinical Events (CE) domain.
Information about the pre-specified clinical events, including solicited events that did not occur for this subject are also represented in the FACE dataset.
Some Required and Expected variables have been omitted in consideration of space and clarity. Start and End Dates were omitted in this example for brevity.
Controlled terminology is still under development, thus some values in the examples are not CDISC controlled terms. Verify demonstrated terminology against
current standards before adopting it.
Row 1:
Rows 2-6:
Shows Subject INF01-02 experienced a secondary infection of pneumonia as solicited on Day 5.
Show which symptoms of influenza the subject experienced as solicited on Day 7. Note that these symptoms were collected via a patient diary
as indicated by CEEVAL=STUDY SUBJECT. Severity grades on symptoms that occurred may be used to calculate composite symptom scores.
ce.xpt
Row
1
2
3
4
5
6
STUDYID
INFL123
INFL123
INFL123
INFL123
INFL123
INFL123
Row
1 (cont)
2 (cont)
3 (cont)
4 (cont)
5 (cont)
6 (cont)
DOMAIN
CE
CE
CE
CE
CE
CE
VISITNUM
5
7
7
7
7
7
VISIT
DAY 5
DAY 7
DAY 7
DAY 7
DAY 7
DAY 7
USUBJID
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
CESEQ
1
2
3
4
5
6
CEDTC
2011-08-06
2011-08-08
2011-08-08
2011-08-08
2011-08-08
2011-08-08
CETERM
PNEUMONIA
FEVER
CHILLS
COUGH
BODY ACHES
FATIGUE
CECAT
SECONDARY INFECTION
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
CEPRESP
Y
Y
Y
Y
Y
Y
CESEV
MILD
MILD
MODERATE
MODERATE
MODERATE
CEEVAL
HEALTH CARE PROFESSIONAL
STUDY SUBJECT
STUDY SUBJECT
STUDY SUBJECT
STUDY SUBJECT
STUDY SUBJECT
CEEVLINT
-P1D
-P1D
-P1D
-P1D
-P1D
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
Page 21
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Rows 1-4:
Show that Subject INF01-02 experienced a secondary infection of pneumonia but did not experience any of the remaining pre-specified
secondary infections as solicited on Day 5.
Show which influenza symptoms the subject did or did not experience as solicited on day 7 (as indicated by the FATESTCD = “OCCUR”).
Note that these symptoms were collected via a patient diary as indicated by FAEVAL = “STUDY SUBJECT”.
Rows 5-12:
face.xpt
Row
1
2
3
4
5
6
7
8
9
10
11
12
STUDYID
INFL456
INFL456
INFL456
INFL456
INFL456
INFL456
INFL456
INFL456
INFL456
INFL456
INFL456
INFL456
Row
1 (cont)
2 (cont)
3 (cont)
4 (cont)
5 (cont)
6 (cont)
7 (cont)
8 (cont)
9 (cont)
10 (cont)
11 (cont)
12 (cont)
DOMAIN
FA
FA
FA
FA
FA
FA
FA
FA
FA
FA
FA
FA
USUBJID
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF01-02
INF02-02
FASEQ
1
2
3
4
5
6
7
8
9
10
11
12
FATESTCD
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
OCCUR
FAEVAL
VISITNUM
HEALTH CARE PROFESSIONAL
5
HEALTH CARE PROFESSIONAL
5
HEALTH CARE PROFESSIONAL
5
HEALTH CARE PROFESSIONAL
5
STUDY SUBJECT
7
STUDY SUBJECT
7
STUDY SUBJECT
7
STUDY SUBJECT
7
STUDY SUBJECT
7
STUDY SUBJECT
7
STUDY SUBJECT
7
STUDY SUBJECT
7
Page 22
November 25, 2014
FATEST
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
Occurrence
VISIT
DAY 5
DAY 5
DAY 5
DAY 5
DAY 7
DAY 7
DAY 7
DAY 7
DAY 7
DAY 7
DAY 7
DAY 7
FAOBJ
Pneumonia
Ear Infection
Bronchitis
Sinus Infection
Fever
Chills
Cough
Sore Throat
Runny Nose
Body Aches
Headaches
Fatigue
FADTC
2011-08-06
2011-08-06
2011-08-06
2011-08-06
2011-08-08
2011-08-08
2011-08-08
2011-08-08
2011-08-08
2011-08-08
2011-08-08
2011-08-08
FACAT
SECONDARY INFECTION
SECONDARY INFECTION
SECONDARY INFECTION
SECONDARY INFECTION
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
INFLUENZA SYMPTOMS
FAORRES
Y
N
N
N
Y
Y
Y
N
N
Y
N
Y
FASTRESC
Y
N
N
N
Y
Y
Y
N
N
Y
N
Y
FAEVLINT
-P1D
-P1D
-P1D
-P1D
-P1D
-P1D
-P1D
-P1D
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3.2 Viral Shedding/Viral Load
The influenza virus is spread when the virus is shed from the host and transfers to other individuals through
respiratory droplets when the host sneezes, coughs, or transfers the droplets through direct or indirect contact. The
host may shed the virus from the day prior to symptom onset to 10 days after illness is noted, but infectivity appears
to decrease after three to five days unless the host is severely immunocompromised 21. It is important that collection
details (e.g., time of isolate relative to symptom onset, method of isolate collection such as nasopharyngeal washing
vs. swab) of viral isolates used for testing be recorded and both the collection and processing procedures should be
standardized as much as possible. Viral load can be assessed by quantitative reverse transcriptase PCR (qRT-PCR)
with the results expressed as influenza log10 RNA copies/mL, or via a surrogate measure by quantitative cell culture
with the results expressed as log10 50% tissue culture infectious doses per milliliter of sample (log10TCID50/mL). It
is important to note that PCR-based methods of viral load assessment can result in detection and amplification of
influenza RNA present due to prior administration of seasonal influenza vaccine 23. Concept map 3 below describes
the different methods of viral load assessment.
Although microneutralization (MN) or hemagglutination inhibition (HI or HAI) assay titers can also give
quantitative results, they are primarily designed to quantify immune factors and are therefore covered as assessments
of immunologic response in section 3.3.
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
Page 23
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Concept Map 3: Viral load assessment
Page 24
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3.2.1 Examples for Viral Load Assessment
Example 1
This example shows how to represent data from three different assessments that serve as either direct or surrogate viral load measurements for three different
subjects participating in an antiviral treatment study. For viral infection prevention, vaccine trial titers were handled identically, with the caveat that qRT-PCR
may also amplify virus particles from the vaccine itself. Collection method is represented in SUPPLB.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Shows the results of a qRT-PCR assay to assess viral load in terms of RNA copies/mL. LBLLOQ shows that this particular protocol has a
lower limit of quantification of 0.9 log10 RNA copies/mL.
Shows the results of a tissue culture based infectivity assay performed to determine the amount of virus required to kill 50% of the cultured
cells (TCID50/mL).
Shows the results of a tissue culture based infectivity assay performed to determine the number of plaque-forming units (PFU) per mL of
subject sample.
Row 2:
Row 3:
lb.xpt
Row
1
STUDYID DOMAIN USUBJID LBSEQ
LBREFID
INFL456
LB
INF02-01
1
SAMPMU0201
LBTESTCD
INFAVLD
2
INFL456
LB
INF02-02
1
SAMPMU0202
IATCID50
3
INFL456
LB
INF02-03
1
SAMPMU0203
IAVRPLAQ
Row
LBSTRESC
LBSTRESN
LBSTRESU
1 (cont)
6.4
6.4
log10 RNA
copies/mL
2 (cont)
3 (cont)
7.6
11
7.6
11
log10 TCID50/mL
PFU/mL
All Rows:
LBTEST
Influenza A Viral Load
Influenza A 50 Percent Tissue Culture
Infective Dose
LBCAT
VIRAL LOAD
LBORRES
6.4
LBORRESU
log10 RNA copies/mL
VIRAL LOAD
7.6
log10 TCID50/mL
Influenza A Viral Plaque Formation
VIRAL LOAD
11
PFU/mL
LBSPEC
LBMETHOD
QUANTITATIVE REVERSE
MUCUS
TRANSCRIPTASE POLYMERASE
CHAIN REACTION
LAVAGE FLUID END-POINT DILUTION ASSAY
LAVAGE FLUID
VIRAL PLAQUE ASSAY
LBLLOQ
VISITNUM
VISIT
LBDTC
0.9
2
VISIT 2
2011-08-08
2
2
VISIT 2
VISIT 2
2011-08-08
2011-08-08
Collection method for the subject samples that participated in viral load assessments shown above.
supplb.xpt
Row
1
2
3
STUDYID
INFL456
INFL456
INFL456
RDOMAIN
LB
LB
LB
USUBJID
INF02-01
INF02-02
INF02-03
IDVAR
LBSEQ
LBSEQ
LBSEQ
IDVARVAL
1
1
1
QNAM
COLMETH
COLMETH
COLMETH
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
QLABEL
Collection Method
Collection Method
Collection Method
QVAL
NASAL SWAB
NASAL WASH
NASAL WASH
QORIG
CRF
CRF
CRF
QEVAL
Page 25
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3.3 Immunologic response to Influenza Antigens
Once the influenza virus evades the innate immune system barriers that include the mucus layer of the respiratory
tract, the virus then lodges in pulmonary epithelial, macrophages and dendritic cells. Antigens of the virus elicit an
immune response that causes the release of chemokines that attract other mediators to the site of viral invasion.
Proinflammatory cytokines and eicosanoids elicit both local and systemic responses such as inflammation and
fever2. Phagocytic cells are recruited to the area and pre-existing antibodies attach to the viral envelope to initiate
viral clearance. Adaptive changes in the immune system allow for a future response to virus re-exposure by
memory B cells and antibody-secreting cells.
Serologic tests for influenza antibody detection are usually not of benefit for the acute diagnosis of an individual
patient with suspected influenza. A full antibody response to infection takes weeks, although exposure to a virus
that is similar to a virus from the prior influenza season may result in a recall antibody response that occurs within
one week. Definitive diagnosis by serological testing requires two samples collected 10-21 days apart. Influenza
infection is confirmed by at least a four-fold increase in antibody titer in comparing the repeat test to the initial test
result. However, these tests are useful for retrospective confirmation of infection, general influenza surveillance and
for vaccine development. Two such tests are the microneutralization (MN) and HI assays.
The MN assay detects strain-specific antibodies that bind to the hemagglutinin protein. Newer MN uses microtiter
plates and an enzyme-linked immunosorbent assay (ELISA) to detect viral infected Madin-Darby canine kidney
(MDCK) cells. MN testing is performed by first determining the tissue culture infectious dose (TCID 50) of the
virus. Next, virus in a fixed TCID50 is combined with two-fold varying dilutions of sera. After sufficient time is
allowed for antibodies to bind to viral antigen, host cells (e.g., MDCK) are added, and subsequently, ELISA is used
to detect viral nucleoprotein of infected cells24. Failure of 1:2 serum dilution to inhibit viral infection is consistent
with a lack of specific antibodies against the test strain. The titer is expressed as the inverse of the largest dilution of
serum that is able to prevent detectable MDCK cell infection.
The HI assay also uses microtiter plates and is based on the ability of viral HA to cause aggregation of red blood
cells. Normally, when red blood cells are added to aqueous solution, the red blood cells settle to the bottom and
appear as a red dot. If influenza virus is added, the viral antigen binds to the red cells forming a suspended lattice
network (i.e., hemagglutination). Specific antibodies bind to the HA and shield this glycoprotein from interacting
with the RBCs25. The HI assay may be used similar to the MN assay to determine antibody titers in sera. This assay
can be used to determine how well vaccines are matched to circulating strains of influenza. Sera from vaccinated
persons or animals are collected and used in the HI assay to determine antibody titer. If viral strains from the
vaccine strain and sick patient are antigenically similar, the lattice is not formed (i.e., no hemagglutination) and the
RBCs sink to the bottom of the well. If the strain of virus from the sick patient is poorly matched to the vaccine
strain, the antibodies do not bind to HA and hemagglutination does occur. The strain(s) used in the production of
the vaccine serves as the positive control and the result should correspond with a high titer. Sera (antibodies) from
influenza infected patients causing hemagglutination at comparably low titers are considered to have viral strains
that are mismatched to the vaccine. Normally, when red blood cells are added to a virus, high HI titers correspond
to greater antigenic similarity and to the test strain immunity. For example if the antibody dilution is 1:160 for one
strain of virus, the antibody dilution for another virus could be either 1:320 or 1:640 to define viral similarity 25.
No correlation has yet been established between HI or MN results and the aspect of the adaptive immune response
that gives rise to protective immunity.
Page 26
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Figure 4: HI Titer
The virus sample depicted in Figure 4 above has an HI titer of 1280; meaning the most dilute sample of antibody-containing serum that still blocked
hemagglutination from occurring was at a 1:1280 dilution. At this dilution, the antibodies are still capable of binding to the hemagglutinin antigens on the virus.
At dilutions greater than 1:1280, the cells are not able to freely sink to the bottom of the well and instead form an agglutinated lattice that covers the wells25.
Concept map 4 below compares and contrasts HI and MN titers as a means of quantifying immunologic response to influenza.
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
Page 27
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Concept Map 4: Microneutralization (MN) and Hemagglutination Inhibition (HI) titers
Page 28
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3.3.1 Examples for Immune Response
Example 1
This example shows two immune response titers from a vaccine trial: Hemagglutination Inhibition (HI) and Microneutralization (MN). Both of these assays use
the subject’s serum to quantify influenza immune factors circulating in the blood. The subjects’ sera are tested against a laboratory strain of influenza virus.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Shows the results of an HI titer. ISORRES shows that a 1:32 dilution of subject serum was the most dilute sample capable of inhibiting
hemagglutination. The standard result titer is expressed as the inverse of this dilution.
Shows the results of an MN titer. ISORRES shows that a 1:64 dilution of subject serum was the most dilute sample capable of neutralizing
Influenza virus in the assay. The standard result titer is expressed as the inverse of this dilution.
Row 2:
is.xpt
Row
STUDYID
DOMAIN
USUBJID
ISSEQ
ISREFID
ISTESTCD
1
INFL456
IS
INF02-01
1
SAMPBL0201
INFAHIT
2
INFL456
IS
INF02-02
2
SAMPBL0202
INFAMNT
Row
1 (cont)
2 (cont)
ISSTRESN
32
64
ISSTRESU
titer
titer
ISSPEC
SERUM
SERUM
ISTEST
Influenza A Hemagglutination
Inhibition Antibody Titer
Influenza A Microneutralization
Antibody Titer
ISMETHOD
HEMAGGLUTINATION INHIBITION ASSAY
MICRONEUTRALIZATION ASSAY
ISCAT
ISORRES
ISORRESU
ISSTRESC
SEROLOGY
1:32
dilution
32
SEROLOGY
1:64
dilution
64
ISDTC
2011-08-08
2011-08-08
Example 2
The Enzyme-Linked ImmunoSpot (ELISpot) assay is a method for monitoring cell-mediated immunity. It is used to detect antigen-specific T or B cells.
This example shows how to represent the quantification of antibody secreting cells (ASCs) as the number of spots per million peripheral blood mononuclear cells
(PBMC) as determined by ELISpot from a vaccine trial. A spot represents a single reactive cell as a result of running an ELISpot assay.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Row 2:
Row 3:
Shows the total number of IgG ASCs from a subject’s blood sample.
Shows the number of H1 specific IgG ASCs from the same subject’s blood sample.
Shows the number of H3 specific IgG ASCs from the same subject’s blood sample.
is.xpt
Row
1
2
3
STUDYID
INFL456
INFL456
INFL456
DOMAIN
IS
IS
IS
USUBJID
INF02-01
INF02-01
INF02-01
ISSEQ
1
2
3
ISREFID
SAMPBL0201
SAMPBL0201
SAMPBL0201
ISTESTCD
TIGGASC
H1IGGASC
H3IGGASC
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
ISTEST
Total IgG Antibody Secreting Cells
H1 Specific IgG Antibody Secreting Cells
H3 Specific IgG Antibody Secreting Cells
ISORRES
2019
626
592
ISORRESU
SFC/10^6 cells
SFC/10^6 cells
SFC/10^6 cells
ISSTRESC
2019
626
592
Page 29
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Row
1 (cont)
2 (cont)
3 (cont)
ISSTRESN
2019
626
592
Page 30
November 25, 2014
ISSTRESU
SFC/10^6 cells
SFC/10^6 cells
SFC/10^6 cells
ISSPEC
BLOOD
BLOOD
BLOOD
ISMETHOD
ELISPOT
ELISPOT
ELISPOT
ISDTC
2011-08-08
2011-08-08
2011-08-08
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3.4 Assessments of Respiration and Perfusion
Patients with severe influenza most often require hospitalization for progressive hypoxemia, but patients with chronic disease states may also require
hospitalization for exacerbation or decompensation of these pre-existing conditions. Once hospitalized, patients are at additional risk for iatrogenic disease
including bacterial infections. Therefore, ongoing monitoring and assessments of organ function are needed. The intensity and complexity of monitoring
depends on the patient’s severity of illness and associated level of care (e.g., ICU vs. non-ICU setting). For a patient with less severe illness on a hospital ward,
routine monitoring might consist of checks of vital signs, oxygen saturation by pulse oximetry, and daily physical examination and review of systems. Whereas a
mechanically ventilated patient in the ICU setting would require more intensive monitoring that likely would include arterial blood gases, catheterization for
hemodynamic monitoring, radiographs or other imaging studies, and laboratory testing (e.g., electrolytes and nutritional indices, complete blood count,
coagulation parameters, indicators of renal and hepatic function).
3.4.1 Examples for Respiration and Perfusion
Example 1
This example shows how to represent data from an arterial blood gas in the LB domain.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Row 2:
Shows the ratio of partial pressure of arterial O2 to the fraction of inspired O2 (PaO2/FiO2) for one subject.
Shows the percentage of available hemoglobin that is saturated with oxygen (SaO2) for one subject.
lb.xpt
Row
1
STUDYID
INFL123
DOMAIN
LB
USUBJID
INF01-01
LBSEQ
1
LBTESTCD
PO2FIO2
LBTEST
PP Arterial O2/Fraction Inspired O2
LBCAT
ARTERIAL BLOOD GAS
LBORRES
326
LBORRESU
mmHg
LBSTRESC
326
2
INFL123
LB
INF01-01
2
OXYSAT
Oxygen Saturation
ARTERIAL BLOOD GAS
90
%
90
Row
1 (cont)
2 (cont)
LBSTRESN
326
90
LBSTRESU
mmHg
%
LBSPEC
ARTERIAL BLOOD
ARTERIAL BLOOD
LBDTC
2011-08-08
2011-08-08
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
Page 31
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Example 2
This example shows how to represent two respiratory tests in the respiratory physiology (RE) domain.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Shows the peak nasal inspiratory flow in L/min. Information about the type of device used is stored in the DI domain and linked to the RE
domain using SPDEVID.
Shows that infiltrates from the same subject were seen on a chest x-ray.
Row 2:
re.xpt
Row
1
2
STUDYID
INFL123
INFL123
Row
1 (cont)
2 (cont)
DOMAIN
RE
RE
RESTRESU
L/min
Row 1:
USUBJID
INF01-01
INF01-01
RELOC
NOSE
LUNG
SPDEVID
ABC001
REMETHOD
X-RAY
RESEQ
1
2
RETESTCD
PNIF
INFILTRS
RETEST
Peak Nasal Inspiratory Flow
Infiltrates
REORRES
100
Y
REORRESU
L/min
RESTRESC
100
Y
RESTRESN
100
REDTC
2011-08-06
2011-08-08
Shows that the device type to measure peak nasal inspiratory flow was a peak flow meter.
di.xpt
Row
1
STUDYID
INFL123
Page 32
November 25, 2014
DOMAIN
DI
SPDEVID
ABC001
DISEQ
1
DIPARMCD
TYPE
DIPARM
Device Type
DIVAL
PEAK FLOW METER
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
3.5 Clinical Outcome Assessments and Other Instruments
Clinical Outcome Assessments and other assessment instruments are maintained as standalone guides on the CDISC
website at http://cdisc.org/ft-and-qt.
The table below lists the assessment instruments that will be supplements to the SDTMIG as part of the release of
TAUG-Influenza v1.0. These instruments may or may not be finalized at the time of publication of this user guide.
Sponsors should refer to the link above if an instrument of interest is not included below, as it may have been
developed for another therapeutic area, and new instruments are implemented in an ongoing basis by the CDISC
Clinical Outcome Assessments Terminology and Standards Development sub-teams. See CDISC COP 017
(http://www.cdisc.org/bylaws-and-policies) for details on implementing or requesting development of standard
instruments for SDTM-based submissions.
Instrument Name
APACHE II
Influenza Intensity and Impact Questionnaire™ (Flu-iiQ™)26
SDTM Domain
Clinical Classifications (CC)*
Questionnaires (QS)
Copyright Status
Public Domain
Copyrighted
*Clinical Classifications is a draft domain as of publication of this guide.
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
Page 33
November 25, 2014
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
4 Routine Data
Some data are routinely collected throughout a study but are of more direct interest to the subject’s welfare, the
safety of the study treatment, and/or as factors in assessing the subject’s condition or reaction to a treatment, than to
the therapeutic area in particular. For influenza studies, such routinely collected data may include adverse events
and healthcare encounters, vital signs, routine observations performed for monitoring purposes, and concomitant
medications.
4.1 Adverse Events
Neuraminidase inhibitors are typically available in oral capsules or a suspension that can be given by mouth or by a
tube placed in the gastrointestinal tract. They are generally well-tolerated except for occasional nausea and
vomiting, and possibly transient neuropsychiatric effects such as delirium. Inhaled formulations of neuraminidase
inhibitors, such as zanamivir, may cause bronchospasm, particularly in patients with pre-existing lung disease such
as asthma or chronic obstructive pulmonary disease (COPD). Other potential adverse effects of zanamivir involve
the nose and throat (e.g., cough, local infections), gastrointestinal tract (e.g., nausea, diarrhea), and the central
nervous system (e.g., headache), although it may cause rare allergic reactions and is contraindicated in patients with
allergy to milk protein.
There is widespread agreement that the efficacy of anti-viral agents is time-dependent and most likely to be effective
if given within 48 hours of influenza symptoms. Both oseltamivir and zanamivir have been demonstrated to reduce
the time to symptomatic improvement27. Although many clinicians consider the potential benefits of either
oseltamivir or zanamivir to outweigh the relatively low risk of drug-related adverse effects in otherwise healthy
patients with seasonal influenza, there is little evidence that these neuraminidase inhibitors prevent serious
complications, hospitalizations or death associated with influenza even when given early in the course of illness27–29.
Regardless, antiviral administration is often instituted in patients considered to be at risk for more severe disease
such as the elderly and patients with other acute or chronic health problems. In such patients, anti-viral
administration should not be delayed while waiting for laboratory confirmation of influenza. Although oseltamivir
is usually considered to be the first-line agent in part because of its availability as an oral dosage form, influenza
resistance patterns as determined from ongoing surveillance of influenza epidemics and pandemics may dictate
changes in the anti-viral regimen5. The duration of anti-viral therapy is usually 5 days for uncomplicated cases of
influenza, but longer courses are often required in patients with more severe disease.
Influenza vaccines are generally available in two forms; an intramuscular injectable containing inactivated
influenza, and a nasal spray containing live attenuated influenza. Adverse effects for the injectable form may
include both reactions localized to the site of injection as well as systemic reactions. Common localized reactions
include redness, tenderness, swelling, and soreness. Typical systemic reactions experienced include headache,
muscle aches, fever, and malaise. The most common reaction to the nasal spray is nasal congestion. Normally,
reactions to both forms of the vaccine are mild and temporary. However, in rare cases more serious reactions may
occur. Of particular concern is any type of autoimmune disorder that is either new or exacerbated after vaccination.
Also for most influenza vaccines, AEs due to egg allergies may also occur based on how vaccines are prepared.
Page 34
November 25, 2014
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
4.1.1 Examples for Adverse Events
Example 1
This example shows how to represent data on pre-specified AEs that solicited for influenza-like illness (ILI) and Guillain-Barre Syndrome in a vaccine trial.
This is represented in the AE domain. Since these are pre-specified events, “No” responses would be represented in the FAAE dataset.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Shows Subject INF02-01 experienced ILI. Note that the investigator deemed this event to be related to the vaccine, as indicated by AEREL.
Further details about this event are represented in the FAAE dataset.
Shows that a pre-specified AE of “Guillain-Barre Syndrome” occurred for this subject. Note that the investigator deemed this event to be
related to the vaccine, as indicated by AEREL.
Row 2:
ae.xpt
Row
STUDYID
DOMAIN
USUBJID
AESEQ
AETERM
AEDECOD
AEPRESP
1
INFL456
AE
INF02-01
1
ILI
Influenza like
illness
Y
2
INFL456
AE
INF02-02
1
Guillain-Barre
Syndrome
Guillain-Barre
syndrome
Y
AEBODSYS
General disorders and
administration site
conditions
Nervous system
disorders
AESEV
AEREL
AESTDTC
AEENDTC
SEVERE
RELATED
2011-02-04
2011-02-11
MODERATE RELATED
2011-02-14
Row 1: Shows Subject INF02-01 missed 2 days of work or school as a result of ILI as indicated by FAOBJ.
faae.xpt
Row
1
STUDYID
INFL456
Row
1 (cont)
DOMAIN
FA
FASTRESN
2
Rows 1-2:
USUBJID
INF02-01
FASTRESU
DAYS
FASEQ
1
FATESTCD
AMTSCHWK
FATEST
Amount of School or Work Missed
FAOBJ
ILI
FAORRES
2
FAORRESU
DAYS
FASTRESC
2
FADTC
20011-02-11
Shows the relationship between influenza like illness and the further details about the illness. The data are linked via --SEQ.
relrec.xpt
Row
1
2
STUDYID
INFL456
INFL456
RDOMAIN
AE
FAAE
USUBJID
IDVAR
AESEQ
FASEQ
IDVARVAL RELTYPE
ONE
ONE
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
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RELID
1
1
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Example 2
This example shows how to represent AE data from an influenza antiviral treatment trial.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Rows 1-2:
Show 2 systemic AEs that subject INF01-02 experienced. AEREL shows the investigator’s judgment as to the relation of the AEs to the study
drug used in this influenza antiviral treatment trial.
ae.xpt
Row
1
2
STUDYID
INFL123
INFL123
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November 25, 2014
DOMAIN
AE
AE
USUBJID
INF01-02
INF01-02
AESEQ
AETERM
AEDECOD
1
SEIZURE
Convulsion
2
CONFUSION Confusional state
AESEV
MODERATE
MILD
AESER
N
N
AEREL
RELATED
POSSIBLY RELATED
AESTDTC
2011-08-08
2011-08-08
AEENDTC
2011-08-08
2011-08-10
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
4.2 Healthcare Encounters and Associated Interventions
Patients requiring hospitalization during the 2009 influenza pandemic had a range of systemic illness that included gastrointestinal, central nervous system, and
cardiovascular involvement, but the major syndrome leading to intensive care unit admission in about half of the patients was a viral pneumonitis with acute
respiratory distress syndrome (ARDS)22. Exacerbation or decompensation of pre-existing pulmonary or cardiovascular disease states was also common. These
hospitalized patients often needed intubation and mechanical ventilation within 24 hours of admission. The pulmonary complications were sometimes
accompanied by shock and renal failure necessitating additional interventions such as vasoactive medications and renal replacement therapy, respectively.
Antibiotics were needed for co-infection with bacterial pneumonia often due to gram positive cocci such as Staphylococcus and Streptococcus species. The 2009
influenza pandemic illustrates how varying influenza strains may have morbidity and mortality predilections for different groups of patients.
As with other patients admitted to an ICU, attention must be given to pain, agitation, and delirium with medication administration according to published
guidelines. In patients at risk for stress induced bleeding (e.g., on mechanical ventilation for more than 48 hours, coagulopathy), histamine-2-antagonists or
proton pump inhibitors are used for prophylaxis. Similarly, most patients will be at risk for venous thromboembolism and will need prophylaxis with
medications (e.g., heparin or a low-molecular-weight heparin) or mechanical forms of prophylaxis, or combined prophylaxis with both in high-risk patients.
4.2.1 Examples for Healthcare Encounters and Associated Interventions
Example 1
Information about hospitalization events is represented in the Healthcare Encounters (HO) domain.
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Row 2:
Shows subject INF02-01 was hospitalized. Reason for hospitalization is shown in the SUPPHO dataset below.
Shows subject INF02-02 was admitted to an intensive care unit.
ho.xpt
Row
1
2
STUDYID
INFL456
INFL456
Row 1:
DOMAIN
HO
HO
USUBJID
INF02-01
INF02-02
HOSEQ
1
1
HOTERM
HOSPITAL
INTENSIVE CARE UNIT
HOSTDTC
2011-08-08
2011-08-10
HOENDTC
2011-08-13
2011-08-14
Shows Influenza is the reason that subject INF02-01 was hospitalized.
suppho.xpt
Row
1
STUDYID
INFL456
RDOMAIN
HO
USUBJID
INF02-01
IDVAR
HOSEQ
IDVARVAL
1
QNAM
HOINDC
QLABEL
Indication
QVAL
INFLUENZA
QORIG
CRF
QEVAL
Example 2
When mechanical ventilation is required for the treatment of influenza, this is represented in the Procedures (PR) domain. The example below shows how to
represent this information for a subject who received mechanical ventilation in hospital. This could be linked back to the hospitalization record via RELREC
(example not shown).
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
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Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Shows Subject INF02-02 required mechanical ventilation from 10 August - 12 August.
pr.xpt
Row
1
STUDYID
INFL456
DOMAIN
PR
USUBJID
INF02-02
PRSEQ
1
SPDEVID
ABC002
PRTRT
Mechanical Ventilation
PRSTDTC
2011-08-10
PRENDTC
2011-08-12
Example 3
Supplemental oxygen administration is handled as a concomitant medication. The example below shows how to represent this information for a subject who
received supplemental oxygen in hospital. This could be linked back to the hospitalization record via RELREC (example not shown).
Some Required and Expected variables have been omitted in consideration of space and clarity. Controlled terminology is still under development, thus some
values in the examples are not CDISC controlled terms. Verify demonstrated terminology against current standards before adopting it.
Row 1:
Shows Subject INF02-01 required supplemental oxygen at a dose of 3 liters per minute for a 6-day period.
cm.xpt
Row
1
STUDYID
INFL456
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DOMAIN
CM
USUBJID
INF02-01
CMSEQ
1
CMTRT
Supplemental Oxygen
CMDOSE
3
CMDOSU
L/min
CMSTDTC
2011-08-12
CMENDTC
2011-08-18
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
Provisional
CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Appendices
Appendix A: Project Proposal
CFAST is proposing development of a CDISC Therapeutic Area User Guide for Influenza. This standard would
build on an FDA TA standards requirements model, existing related CDISC SDTM and TA standards, such as the
CDISC Virology Therapeutic Area Data Standard, and facilitate review of data relevant to prevention, monitoring
and treatment of Influenza.
The workgroup proposes developing a CDISC Therapeutic Area User Guide for Influenza, including concept maps,
metadata, examples and controlled terminology. The standardization effort is expected to evaluate the following
areas of specific interest to Influenza to determine where new SDTM development is needed: Data and methods to
substantiate diagnosis and confirmation of Influenza virus infection, dosing and treatment regimens, onset and
duration of general symptoms (e.g., fever, cough, nasal congestion, runny nose, myalgia, headache, and fatigue),
medical history of special interest (e.g., chronic underlying diseases such as COPD, asthma, heart disease, diabetes,
renal or hepatic disease), AEs of special interest (e.g., injection site reactions and immunogenicity for biologics),
CMs of special interest (e.g., related to treatment of chronic underlying diseases and as part of antiviral treatment
regimens), collected data to support determination of endpoints (e.g., time to resolution of symptoms, rates of virusclearance (i.e., time to undetected virus in nasal swabs by RT-PCR or culture), time to detection of antiviral drug
resistant virus, and biomarkers (e.g., antibody responses to Influenza vaccines, other infection-related biomarkers
such as Interleukin-6 and blood and urine biomarkers in case of secondary bacterial infection).
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
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Appendix B: CFAST Organizations
CDISC
CDISC is a global, open, multidisciplinary, non-profit organization that has established standards to support the
acquisition, exchange, submission and archive of clinical research data and metadata. The CDISC mission is to
develop and support global, platform-independent data standards that enable information system interoperability to
improve medical research and related areas of healthcare. CDISC standards are vendor-neutral, platformindependent and freely available via the CDISC website.
Critical Path Institute (C-Path)
An independent, non-profit organization established in 2005 with public and private philanthropic support from the
Arizona community, Science Foundation Arizona, and the U.S. Food and Drug Administration, C-Path’s mission is
to improve human health and well-being by developing new technologies and methods to accelerate the
development and review of medical products. An international leader in forming collaborations, C-Path has
established global, public-private partnerships that currently include 1,000+ scientists from government regulatory
agencies, academia, patient advocacy organizations, and dozens of major pharmaceutical companies.
Association of Clinical Research Organizations
The Association of Clinical Research Organizations (ACRO) represents the world's leading clinical research
organizations. ACRO members provide specialized services that are integral to the development of drugs, biologics
and medical devices. ACRO advances clinical outsourcing to improve the quality, efficiency and safety of
biomedical research. Each year, ACRO’s members conduct thousands of clinical trials and provide related drug
development services in more than 115 countries while ensuring the safety of nearly 2 million research participants.
Innovative Medicines Initiative
The Innovative Medicines Initiative (IMI) is Europe's largest public-private partnership aiming to improve the drug
development process by supporting a more efficient discovery and development of better and safer medicines for
patients. IMI supports collaborative research projects and builds networks of industrial and academic experts in
Europe that will boost innovation in healthcare. Acting as a neutral third party in creating innovative partnerships,
IMI aims to build a more collaborative ecosystem for pharmaceutical research and development. IMI supports
research projects in the areas of safety and efficacy, knowledge management and education and training.
National Cancer Institute Enterprise Vocabulary Services
Since 1997, NCI Enterprise Vocabulary Services (EVS) has provided terminology content, tools, and services to
accurately code, analyze and share cancer and biomedical research, clinical and public health information. EVS
works with many partners to develop, license and publish terminology, jointly develop software tools, and support
harmonization and shared standards. EVS provides the foundational layer for NCI's informatics infrastructure, and
plays an important role in federal and international standards efforts.
TransCelerate BioPharma, Inc.
Launched in September 2012, TransCelerate BioPharma, Inc. aims to simplify and accelerate the delivery of
innovative medicines to patients. The TCB mission is to collaborate across the global biopharmaceutical R&D
community in order to identify, prioritize, design and facilitate implementation of solutions designed to drive the
efficient, effective and high quality delivery of new medicines.
U.S. Food and Drug Administration
The FDA is an agency of the United States Department of Health and Human Services. FDA is responsible for
protecting the public health by assuring the safety, efficacy and security of human and veterinary drugs, biological
products, medical devices, our nation’s food supply, cosmetics, and products that emit radiation. FDA is also
responsible for advancing the public health by helping to speed innovations that make medicines more effective,
safer, and more affordable and by helping the public get the accurate, science-based information they need to use
medicines and foods to maintain and improve their health30.
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
Appendix C: CFAST Influenza Development Team
Name
Bess LeRoy, Co-lead, Metadata Development
Jon Neville, Co-lead, Metadata Development
Laura Butte, Project Manager
Steve Kopko, SDTM and Concept Model Development
Brian Erstad, PharmD, Science Writer
David Nix, PharmD, Science Writer
Erin Muhlbradt, Terminologist
Jordan Li, Terminologist
Bernice Yost, Terminologist
Emily Hartley, Questionnaire Terminology Team
Diane Wold, Concept Modeling Team Lead
Institution/Organization
Critical Path Institute
Critical Path Institute
Critical Path Institute
CDISC
University of Arizona, College of Pharmacy
University of Arizona, College of Pharmacy
NCI EVS
NCI EVS
CDISC
Critical Path Institute
Glaxo Smithkline
Ron Fitzmartin, PhD, Liaison
Damon Deming, PhD, Influenza Therapeutic-area Expert
Kirk Prutzman, PhD, Influenza Therapeutic-area Expert
Jeffry Florian, PhD, Influenza Therapeutic-area Expert
FDA - Sr. Advisor, Data Standards Program
FDA – CDER reviewer
FDA - CBER reviewer
FDA - CDER reviewer
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
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Appendix D: Glossary and Abbreviations
ADaM
ASC
BRIDG
CDASH
CDISC
CFAST
Collected
Controlled
Terminology
CRF
Domain
EC50
eCRF
ELISpot
Foundational
Standards
HA
HGVS
HI
IC50
MDCK
MedDRA
MN
NA
NCI EVS
NIH
PBMC
PCR
PNIF
PFU
PRO
qRT-PCR
RIDT
RT-PCR
SDS
SDTM
SDTMIG
SHARE
TCID50
Analysis Data Model
Antibody Secreting Cell
Biomedical Research Integrated Domain Group
Clinical Data Acquisition Standards Harmonization Project.
Clinical Data Interchange Standards Consortium
Coalition for Accelerating Standards and Therapies
“Collected” refers to information that is recorded and/or transmitted to the sponsor. This
includes data entered by the site on CRFs/eCRFs as well as vendor data such as core lab
data. This term is a synonym for “captured.”
A finite set of values that represent the only allowed values for a data item. These values
may be codes, text, or numeric. A code list is one type of controlled terminology.
Case Report Form (sometimes called a Case Record Form). A printed, optical, or electronic
document designed to record all required information to be reported to the sponsor for each
trial subject.
A collection of observations with a topic-specific commonality about a subject.
Half maximal effective concentration: The concentration of a drug which induces a response
halfway between the baseline and maximum, commonly used as a measure of potency.
Electronic Case Report Form
Enzyme-linked ImmunoSpot: an assay method for assessing cell-mediated immunity
Used to refer to the suite of CDISC standards that describe the clinical study protocol
(Protocol), design (Study Design), data collection (CDASH), laboratory work (Lab),
analysis (ADaM), and data tabulation (SDTM and SEND). See http://www.cdisc.org/ for
more information on each of these clinical data standards.
Hemagglutination
Human Genome Variation Society
Hemagglutination Inhibition
Half maximal inhibitory concentration: A measure of the effectiveness of a substance in
inhibiting a specific biological or biochemical function.
Madin-Darby canine kidney cells- used in laboratories for various cell-based assays.
Medical Dictionary for Regulatory Activities. New global standard medical terminology
designed to supersede other terminologies (such as COSTART and ICD9) used in the
medical product development process.
Microneutralization
Neuraminidase
National Cancer Institute (NCI) Enterprise Vocabulary Services
National Institutes of Health
Peripheral Blood Mononuclear Cell
Polymerase Chain Reaction
Peak Nasal Inspiratory Flow
Plaque-forming Units
Patient Reported Outcome
Quantitative Reverse Transcriptase Polymerase Chain Reaction
Rapid Influenza Diagnostic Test
Reverse Transcriptase Polymerase Chain Reaction
Submission Data Standards. Also the name of the team that maintains the SDTM and
SDTMIG.
Study Data Tabulation Model
SDTM Implementation Guide (for Human Clinical Trials)
Shared Health and Clinical Research Electronic Library. CDISC’s metadata repository,
currently under development.
Half maximal Tissue Culture Infectious Dose- The amount of virus required to kill 50% of
infected hosts or to produce a cytopathic effect in 50% of inoculated tissue culture cells
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
UML
Unified Modeling Language
Appendix D1: Supplemental Qualifier Name Codes
The following table contains additional standard QNAM and QLABEL values for use in the Supplemental
Qualifiers (SUPP--) special-purpose datasets.
QNAM
QLABEL
Applicable Domains
COLMETH Collection Method
MB, VR, LB
HOINDC
Indication
HO
SFTWR
Analysis Software
VR
SFTWRVER Software Version
VR
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
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Appendix E: References
1.
CDC - Overview of Influenza Surveillance in the United States | Seasonal Influenza (Flu). 2013. Available at:
http://www.cdc.gov/flu/weekly/overview.htm. Accessed August 27, 2014.
2.
Iwasaki A, Pillai PS. Innate immunity to influenza virus infection. Nat. Rev. Immunol. 2014;14(5):315-328.
3.
Harper SA, Bradley JS, Englund JA, et al. Seasonal influenza in adults and children--diagnosis, treatment,
chemoprophylaxis, and institutional outbreak management: clinical practice guidelines of the Infectious
Diseases Society of America. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 2009;48(8):1003-1032.
4.
Laplante J, St George K. Antiviral resistance in influenza viruses: laboratory testing. Clin. Lab. Med.
2014;34(2):387-408.
5.
Hurt AC. The epidemiology and spread of drug resistant human influenza viruses. Curr. Opin. Virol.
2014;8C:22-29.
6.
Influenza Antiviral Drug Resistance | Seasonal Influenza (Flu) | CDC. 2014. Available at:
http://www.cdc.gov/flu/about/qa/antiviralresistance.htm. Accessed August 28, 2014.
7.
CDER. Information by Drug Class - Influenza (Flu) Antiviral Drugs and Related Information. 2013. Available
at: http://www.fda.gov/drugs/drugsafety/informationbydrugclass/ucm100228.htm#use. Accessed August 28,
2014.
8.
Peaper DR, Landry ML. Rapid diagnosis of influenza: state of the art. Clin. Lab. Med. 2014;34(2):365-385.
9.
Lin T-Y, Brass AL. Host genetic determinants of influenza pathogenicity. Curr. Opin. Virol. 2013;3(5):531536.
10. Types of Influenza Viruses | About (Flu) | CDC. Available at: http://www.cdc.gov/flu/about/viruses/types.htm.
Accessed August 28, 2014.
11. A revision of the system of nomenclature for influenza viruses: a WHO memorandum. Bull. World Health
Organ. 1980;58(4):585-591.
12. Burschik. Influenza Virus Nomenclature (for a Fujian Flu Virus).; 2007. Available at:
http://commons.wikimedia.org/wiki/File:Influenza_nomenclature.svg#mediaviewer/File:Influenza_nomenclatu
re.svg.
13. Noh JY, Kim WJ. Influenza vaccines: unmet needs and recent developments. Infect. Chemother.
2013;45(4):375-386.
14. Gopinath SCB, Tang T-H, Chen Y, Citartan M, Tominaga J, Lakshmipriya T. Sensing strategies for influenza
surveillance. Biosens. Bioelectron. 2014;61:357-369.
15. Portela A, Digard P. The influenza virus nucleoprotein: a multifunctional RNA-binding protein pivotal to virus
replication. J. Gen. Virol. 2002;83(Pt 4):723-734.
16. Nguyen HT, Fry AM, Gubareva LV. Neuraminidase inhibitor resistance in influenza viruses and laboratory
testing methods. Antivir. Ther. 2012;17(1 Pt B):159-173.
17. Meijer A, Rebelo-de-Andrade H, Correia V, et al. Global update on the susceptibility of human influenza
viruses to neuraminidase inhibitors, 2012-2013. Antiviral Res. 2014;110C:31-41.
18. Clinical Signs and Symptoms of Influenza | Health Professionals | Seasonal Influenza (Flu). Available at:
http://www.cdc.gov/flu/professionals/acip/clinical.htm. Accessed August 28, 2014.
19. Estabragh ZR, Mamas MA. The cardiovascular manifestations of influenza: a systematic review. Int. J.
Cardiol. 2013;167(6):2397-2403.
20. Tsai JP, Baker AJ. Influenza-associated neurological complications. Neurocrit. Care 2013;18(1):118-130.
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CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0)
21. Centers for Disease Control and Prevention (CDC). Prevention and control of seasonal influenza with vaccines.
Recommendations of the Advisory Committee on Immunization Practices--United States, 2013-2014. MMWR
Recomm. Rep. Morb. Mortal. Wkly. Rep. Recomm. Rep. Cent. Dis. Control 2013;62(RR-07):1-43.
22. Writing Committee of the WHO Consultation on Clinical Aspects of Pandemic (H1N1) 2009 Influenza,
Bautista E, Chotpitayasunondh T, et al. Clinical aspects of pandemic 2009 influenza A (H1N1) virus infection.
N. Engl. J. Med. 2010;362(18):1708-1719.
23. Curran T, McCaughey C, Ellis J, et al. False-positive PCR results linked to administration of seasonal influenza
vaccine. J. Med. Microbiol. 2012;61(Pt 3):332-338. doi:10.1099/jmm.0.036178-0.
24. WHO | Manual for the laboratory diagnosis and virological surveillance of influenza. WHO. Available at:
http://www.who.int/influenza/gisrs_laboratory/manual_diagnosis_surveillance_influenza/en/. Accessed August
28, 2014.
25. Antigenic Characterization | Health Professionals | Seasonal Influenza (Flu). 2014. Available at:
http://www.cdc.gov/flu/professionals/laboratory/antigenic.htm. Accessed August 28, 2014.
26. Burch J, Corbett M, Stock C, et al. Prescription of anti-influenza drugs for healthy adults: a systematic review
and meta-analysis. Lancet Infect. Dis. 2009;9(9):537-545.
27. Heneghan CJ, Onakpoya I, Thompson M, Spencer EA, Jones M, Jefferson T. Zanamivir for influenza in adults
and children: systematic review of clinical study reports and summary of regulatory comments. BMJ
2014;348:g2547.
28. Jefferson T, Jones M, Doshi P, Spencer EA, Onakpoya I, Heneghan CJ. Oseltamivir for influenza in adults and
children: systematic review of clinical study reports and summary of regulatory comments. BMJ
2014;348:g2545.
29. What We Do. Available at: http://www.fda.gov/AboutFDA/WhatWeDo/default.htm. Accessed September 10,
2014.
© 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved
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Appendix F: Representations and Warranties, Limitations of
Liability, and Disclaimers
CDISC Patent Disclaimers
It is possible that implementation of and compliance with this standard may require use of subject matter covered by
patent rights. By publication of this standard, no position is taken with respect to the existence or validity of any
claim or of any patent rights in connection therewith. CDISC, including the CDISC Board of Directors, shall not be
responsible for identifying patent claims for which a license may be required in order to implement this standard or
for conducting inquiries into the legal validity or scope of those patents or patent claims that are brought to its
attention.
Representations and Warranties
“CDISC grants open public use of this User Guide (or Final Standards) under CDISC’s copyright.”
Each Participant in the development of this standard shall be deemed to represent, warrant, and covenant, at the time
of a Contribution by such Participant (or by its Representative), that to the best of its knowledge and ability: (a) it
holds or has the right to grant all relevant licenses to any of its Contributions in all jurisdictions or territories in
which it holds relevant intellectual property rights; (b) there are no limits to the Participant’s ability to make the
grants, acknowledgments, and agreements herein; and (c) the Contribution does not subject any Contribution, Draft
Standard, Final Standard, or implementations thereof, in whole or in part, to licensing obligations with additional
restrictions or requirements inconsistent with those set forth in this Policy, or that would require any such
Contribution, Final Standard, or implementation, in whole or in part, to be either: (i) disclosed or distributed in
source code form; (ii) licensed for the purpose of making derivative works (other than as set forth in Section 4.2 of
the CDISC Intellectual Property Policy (“the Policy”)); or (iii) distributed at no charge, except as set forth in
Sections 3, 5.1, and 4.2 of the Policy. If a Participant has knowledge that a Contribution made by any Participant or
any other party may subject any Contribution, Draft Standard, Final Standard, or implementation, in whole or in
part, to one or more of the licensing obligations listed in Section 9.3, such Participant shall give prompt notice of the
same to the CDISC President who shall promptly notify all Participants.
No Other Warranties/Disclaimers. ALL PARTICIPANTS ACKNOWLEDGE THAT, EXCEPT AS PROVIDED
UNDER SECTION 9.3 OF THE CDISC INTELLECTUAL PROPERTY POLICY, ALL DRAFT STANDARDS
AND FINAL STANDARDS, AND ALL CONTRIBUTIONS TO FINAL STANDARDS AND DRAFT
STANDARDS, ARE PROVIDED “AS IS” WITH NO WARRANTIES WHATSOEVER, WHETHER EXPRESS,
IMPLIED, STATUTORY, OR OTHERWISE, AND THE PARTICIPANTS, REPRESENTATIVES, THE CDISC
PRESIDENT, THE CDISC BOARD OF DIRECTORS, AND CDISC EXPRESSLY DISCLAIM ANY
WARRANTY OF MERCHANTABILITY, NONINFRINGEMENT, FITNESS FOR ANY PARTICULAR OR
INTENDED PURPOSE, OR ANY OTHER WARRANTY OTHERWISE ARISING OUT OF ANY PROPOSAL,
FINAL STANDARDS OR DRAFT STANDARDS, OR CONTRIBUTION.
Limitation of Liability
IN NO EVENT WILL CDISC OR ANY OF ITS CONSTITUENT PARTS (INCLUDING, BUT NOT LIMITED
TO, THE CDISC BOARD OF DIRECTORS, THE CDISC PRESIDENT, CDISC STAFF, AND CDISC
MEMBERS) BE LIABLE TO ANY OTHER PERSON OR ENTITY FOR ANY LOSS OF PROFITS, LOSS OF
USE, DIRECT, INDIRECT, INCIDENTAL, CONSEQUENTIAL, OR SPECIAL DAMAGES, WHETHER
UNDER CONTRACT, TORT, WARRANTY, OR OTHERWISE, ARISING IN ANY WAY OUT OF THIS
POLICY OR ANY RELATED AGREEMENT, WHETHER OR NOT SUCH PARTY HAD ADVANCE NOTICE
OF THE POSSIBILITY OF SUCH DAMAGES.
Note: The CDISC Intellectual Property Policy can be found at:
http://www.cdisc.org/system/files/all/article/application/pdf/cdisc_20ip_20policy_final.pdf
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