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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 Page 2 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) 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 Page 3 November 25, 2014 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. Page 4 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) 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 © 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved Provisional Page 5 November 25, 2014 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. Page 6 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) 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. © 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved Provisional Page 7 November 25, 2014 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 Page 8 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) 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 © 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved Provisional Page 9 November 25, 2014 CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0) 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 Page 10 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 1: Diagnosis, laboratory confirmation and strain-typing of influenza © 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved Provisional Page 11 November 25, 2014 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 Page 12 November 25, 2014 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 Provisional RELID 1 1 Page 35 November 25, 2014 CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0) 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 Page 36 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 Provisional Page 37 November 25, 2014 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. 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 Page 38 November 25, 2014 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 Provisional Page 39 November 25, 2014 CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0) 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. Page 40 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) 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 Provisional Page 41 November 25, 2014 CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0) 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 Page 42 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) 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 Provisional Page 43 November 25, 2014 CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0) 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. Page 44 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) 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 Provisional Page 45 November 25, 2014 CDISC Therapeutic Area Data Standards: User Guide for Influenza (v1.0) 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 Page 46 November 25, 2014 © 2014 Clinical Data Interchange Standards Consortium, Inc. All rights reserved Provisional