This Therapeutic Area Data Standards User Guide for Post Traumatic Stress Disorder (TAUG-PTSD) v1.0 was developed under the Coalition for Accelerating Standards and Therapies (CFAST) initiative. This data standard follows several previously published neuroscience-related TAUGs, including Alzheimer's disease, schizophrenia, traumatic brain injury, and major depressive disorder. The TAUG-PTSD was funded by Cohen Veterans Bioscience, Inc as part of the collaborative efforts between Cohen Veterans Bioscience and the Clinical Data Interchange Standards Consortium (CDISC).

The purpose of this TAUG-PTSD is to describe how to use CDISC standards to represent data pertaining to post traumatic stress disorder studies in adult and pediatric populations. This first version (v1.0) focuses on the representation of data using the Study Data Tabulation Model (SDTM), and the Study Data Tabulation Model Implementation Guide (SDTMIG) as well as some Clinical Data Acquisition Standards Harmonization (CDASH) and Analysis Data Model (ADaM) representation.

1. First, read the SDTM v1.7, SDTMIG v3.3, SDTMIG-MD v1.1, CDASHIG v2.0, and ADaM v2.1. These standards are available at http://www.cdisc.org/.
2. Next, read Introduction to Therapeutic Area Standards (at http://wiki.cdisc.org/x/SSy8AQ) and/or take CDISC's free training module TA001 - Overview of Therapeutic Area User Guides (at CDISC Online Training) to be sure to know what to expect from a therapeutic area user guide.
3. Read this guide all the way through (without skipping any sections) at least once.
4. Finally, revisit any sections of particular interest.

All general caveats for TA standards given in the Introduction to Therapeutic Area Standards (http://wiki.cdisc.org/x/SSy8AQ) apply to this document.

Some things to bear in mind while reading this document:

• This document does not replace or supersede the foundational CDISC standards or their implementation guides, and should not be used as a substitute for any other CDISC standard.
• This document does not repeat content already published in another CDISC standard.
• This document is not and does not try to be an exhaustive documentation of every possible kind of data that could be collected in relation to post traumatic stress disorder.
• The advice and examples presented in this document are influenced by ongoing internal standards development at CDISC. If a modeling approach seems inconsistent with a published standard, it may be a genuine error, but it could also be a reflection of potential or upcoming changes to the standard.
• The examples in this document use CDISC Controlled Terminology (CT) where possible, but some values that seem to be controlled terminology may still be under development at the time of publication, or even especially plausible "best-guess" placeholder values. Do not rely on any source other than the CDISC value set in the NCI Thesaurus (available at http://www.cancer.gov/research/resources/terminology/cdisc) for controlled terminology.

This document is divided into the following sections:

• Section 1, Introduction, provides an overall introduction to the purpose and goals of the Post Traumatic Stress Disorder Therapeutic Area Standard User Guide.
• Section 2, Subject and Disease Characteristics, covers data that are usually collected once at the beginning of a study.
• Section 3, Disease Assessments, covers data that are typically collected multiple times over the course of the study.
• Section 4, Routine Data, covers data that are collected in most PTSD studies.
• Section 5, Analysis Data, includes key data analysis concepts for a PTSD study.
• Appendices provide additional background material and describe other supplemental material relevant to PTSD.

CDASH examples include both metadata tables and sample case report forms (CRFs). Each table of CDASH metadata corresponds to an example annotated CRF (aCRF), built directly from the metadata. The annotations show the variables associated with each field in the context of data collection (CDASH) and submission (SDTM) and are denoted by color. Data that are collected using the same variable name as defined in the SDTMIG are in RED. If the CDASHIG variable differs from the one defined in the SDTMIG, the CDASHIG variable is in GREY. Data collected but not submitted in SDTM-based datasets are denoted as NOT SUBMITTED The CDASH variable ----NO (e.g., --AENO, --PRNO) are generically annotated as ASSOCIATE WITH RELATED RECORD VIA RELREC. These RELREC relationships are sponsor-defined and depend on the actual study and the procedures used by the sponsor to create RELREC.

The following diagram illustrates how to interpret the annotations.

When viewing sample CRFs and aCRFs, bear in mind that:

• When implementing CDASH in a denormalized structure, denormalized CDASH variable names are created by the sponsor, when needed. Denormalized CDASH variable names for TAUGs generally use the following naming convention:
  < Topic Variable values >_<Qualifier(s)>_<SDTMIG Target >.

  Sponsors may define their own conventions for creating denormalized CDASH variable names. Examples:

  • DIABP_VSORRES, where DIABP is the value for VSTESTCD (topic variable) and VSORRES is the SDTMIG target.
  • DIABP_ARM _RIGHT_VSORRES, where DIABP is the value for VSTESTCD (topic variable); ARM and RIGHT are values of the SDTM Qualifier variables VSLOC and VSLAT:VSORRES is the SDTMIG target.
  • Depression_MHOCCUR, where Depression is the value of MHTERM (topic variable); MHOCCUR is the SDTMIG target.      

• More information may also be found in the CDASH Model and CDASHIG.
• Example CRFs are provided to illustrate data collection instruments. These are only examples and are not meant to recommend any particular layout over another.
• Example CRFs include instructions for the clinical site regarding how to enter collected information on the CRF.
• Example CRFs are best understood in conjunction with their respective metadata tables and/or the CDASH Domain Metadata Tables.
• Most example CRFs do not include the Highly Recommended header variables. The population of these values is usually determined by the sponsor's data management system.
• Sponsors are responsible for understanding and implementing CDISC Controlled Terminology where applicable.
• CDASH variable names for denormalized variables are examples. Sponsors may use other conventions for creating denormalized CDASH variable names.
• CDASH variable names that are annotated as "NOT SUBMITTED" may be used to contribute towards the population of other appropriate variables when the SDTM-based datasets are created.
• CDASH variables may also be mapped to or used to populate other SDTMIG variables that are not shown.
• Although a CDASH variable usually maps to a single SDTM-based domain, some CRFs may illustrate mapping to multiple variables as indicated by SDTM annotations such as TUDTC AND TRDTC. CDASH variables may also be mapped to or used to populate other SDTMIG variables that are not shown.

• --TESTCD/--TEST: When controlled terminology for tests is developed, there is often debate about how much information related to the test should be incorporated into the --TEST and --TESTCD variables, and how much should be represented in other variables. For example, the pre-coordination of test qualifiers such as "mean" is still under discussion. The incorporation of qualifier information into the test definition is referred to as pre-coordination, whereas the representation of qualifier information in a separate qualifier variable is referred to as post-coordination. At the time of publication of this TAUG, some --TEST/--TESTCD values are preliminary; final approved terminology may be different.
• Large Volume of Raw Data:
  • This TAUG presents examples of the representation in SDTM-based domains of derived data that was calculated by the external vendor. Representing these derived measures within an SDTM-based domain (e.g., sleep testing, startle response) is under consideration by the Submission Data Standards (SDS) and Analysis Data Model (ADaM) Teams and is subject to change.

  • All collected data that supports review, reporting, and analysis should be submitted. There are cases where a large volume of raw data is generated by a device many times per second (e.g., ECG waveform data, data collected by polysomnography). In this case, summary data that are received as an output from a device may be represented in an SDTM dataset (e.g., average over a fixed period of time) instead of the full set of the raw data. Even though summary data are submitted, health authorities may request the submission of all of the raw data from the device.

• Representation of Device properties in DU: Device set-up properties that are fixed for all subject using the same device can be represented by leaving the USUBJID null. However, when multiple testing sites are using the same device with different device set-up parameters, the set-up parameters must be provided for each subject. This may create duplicate information when all subjects at that test site are evaluated using the same set-up parameters.  
• CDASH MHSTDAT, MHENDAT Question Text/Prompt: The MHSTDAT (MHENDAT) question text "What was the medical condition or event start (end) date?" and prompt "Start/End Date" in the CDASHIG does not consider the need to ask a specific question about Diagnosis Date or Symptom Start (End) Date. The example aCRF in Section 2.1, PTSD History - Symptoms and Diagnosis, uses the prompts Date and Start Date. CDASH is considering updating these Question Text and Prompts to allow the sponsor to include the values recorded in MHEVDTYP.

Post traumatic stress disorder (PTSD) is a clinically diagnosed psychiatric condition that can occur following the experience or the witnessing of life-threatening events, such as military combat, natural disasters, terrorist incidents, serious accidents, or physical or sexual assault in adulthood or childhood. It is characterized by experiencing distress or fear in non-threatening situations, as well as disturbing thoughts or feelings related to the event, which can negatively affect relationships and impair functioning. A person may develop PTSD after directly experiencing or witnessing a traumatic event, or by being confronted with an event happening to someone close to the individual. Not everyone who has been exposed to a traumatic event will develop PTSD. According to the National Center for PTSD, about 7 or 8 out of every 100 people will experience PTSD at some point in their lives.[1]

Symptoms of PTSD include re-experiencing symptoms (e.g., flashbacks, frightening thoughts), avoidance symptoms (e.g., staying away from people, places, or things that trigger the memory of the traumatic event), hyperarousal and reactivity symptoms (e.g., easily startled or angered), and cognition and mood symptoms (e.g., negative thoughts or loss of interest in normal activities).[2] These symptoms often can be very debilitating and interfere with work and relationships and can continue to be experienced even when there is no perceivable danger or threat.

In general, information about subject and disease characteristics includes events and activities that have affected the subject prior to or at the start of the study. For PTSD, this includes basic demographic data, details about the trauma that the subject may have experienced, and baseline assessments as to the severity of the subject's PTSD. Commonly co-occurring physical and mental health conditions are often also collected, as well substance use information. Basic demographic data collected in PTSD studies generally include date of birth or age, sex, race, and ethnicity. Other socioeconomic characteristics such as years of education, education level, annual income, employment status, and marital status are typically collected. More complex measures of social status, social support, and social circumstances may also be collected. These more complex measures are often collected using published instruments (within CDISC, these are referred to as Questionnaires, Ratings, and Scales [QRS]). Because there are many challenges associated with the collection of information on social status and social circumstances (many that depend on the particular research goal of the study), no specific SDTM examples of these measures are provided in this TAUG. Typically published instruments would be modeled in appropriate QRS domains. Other characteristics that are collected but not based on a published measure (e.g., annual income, education level) may be represented in the Subject Characteristics (SC) domain. See the SDTMIG for additional information on the Demographics (DM), Subject Characteristics (SC), Medical History (MH), Substance Use (SU) domains, and the QRS domains.

Various published instruments may also be administered to collect information used to characterize the subject at the start of the study. These questionnaires are typically represented in the SDTM QS domain. These same instruments may be repeated during the study (See Section 3.2, Questionnaires, Ratings, and Scales).    

The American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM–5) is the most widely accepted nomenclature used by clinicians and researchers for the classification of mental disorders. PTSD is included in a new category in DSM–5, Trauma- and Stressor-Related Disorders;[3] full copyrighted criteria are available from the American Psychiatric Association. The diagnosis of PTSD requires exposure to a traumatic or threatening event, either by directly experiencing or witnessing the event, and symptoms that last more than a month.

Disease assessments are typically done repeatedly over the course of post traumatic stress disorder (PTSD) studies and are used to evaluate how the subject is progressing. The assessments most commonly used to determine the course of PTSD are various questionnaires, scales, and instruments. (See Section 3.2, Questionnaires, Ratings, and Scales, for a list of those identified for development as part of this TAUG.) These are often used to assess the severity of PTSD symptoms. Physiological testing (e.g., skin conductance, startle response) may also be performed. In their article, Hamilton et al provided a catalog of measures for use in PTSD research. [4]

The brain circuitry of PTSD has been studied using various imaging modalities which can help to identify damage to the brain. Brain regions that are thought to be important include the hippocampus, amygdala, and medial prefrontal cortex. Imaging of the brain may be performed to assess the anatomic features of the brain and to assess the functioning of the brain during specific tasks (e.g., response to a stimuli). Magnetic resonance imaging (MRI) and computed tomography (CT) scans are often used to assess the structural features of the brain; positron emission tomography (PET), regional cerebral blood flow (rCBF), and functional magnetic resonance imaging (fMRI) are used to assess the functioning of the brain.

The following concept map shows the various components of an imaging evaluation and where this information is stored in SDTM. SDTM imaging examples can be found in several previously published TAUGs, including Huntington's Disease and Traumatic Brain Injury.

Concept Map: Imaging

Questionnaires, Ratings, and Scales (QRS) are maintained as stand-alone supplements on the CDISC website at http://cdisc.org/qrs. The following table lists assessments that are being pursued as potential supplements to the SDTMIG as part of the development work for Version 1.0 of the TAUG-PTSD. Supplements may or may not be finalized at the time of publication of this document, and depend on copyright approval where applicable. CDISC cannot produce supplements for copyrighted measures without the express permission of the copyright holder.

Sponsors should refer to the CDISC website (https://www.cdisc.org/foundational/qrs) if a measure of interest is not included below, as it may have been developed for another TAUG. New measures are implemented on an ongoing basis by the CDISC QRS Terminology and Standards Development sub-teams.

QRS Supplements of Interest to PTSD

Skin conductance (SC)—also known as galvanic skin response, electrodermal response, psychogalvanic reflex, skin conductance response, or skin conductance level—is a method of measuring the electrical conductance of the skin. Skin conductance is used as an indication of psychological or physiological arousal. When sweat gland activity increases, there is an increase in skin conductance. Skin conductance can be used as a measure of emotional and sympathetic nervous system responses with spontaneous fluctuations or reactions to stimuli. Skin conductance is often measured in persons with PTSD, who often exhibit stronger skin conductance when asked questions regarding a traumatic event or asked to imagine a traumatic event they have experienced. Skin conductance is normally measured with electrodes positioned on the index and middle fingers. The specific research protocol describes how the skin conductance test is administered and analyzed.

Baseline and trauma challenge psychophysiological recordings are used to measure skin conductance and heart rate in response to a Trauma Interview and Trauma Imagery in order to determine changes in these values (see concept map below). The protocol for a skin conductance test consists of a Baseline phase and a Trauma Challenge phase (includes Trauma Interview and Trauma Imagery). During the Baseline phase, skin conductance and heart rate are monitored continuously while the participant rests quietly. During the first part of the Trauma Challenge phase, heart rate and skin conductance are continuously measured while the participant is administered a 21-question, open-ended trauma interview. After the interview, skin conductance and heart rate are monitored continuously while the participant is asked to think about and imagine the traumatic event. The full protocol for the administration of this measurement is available at https://www.phenxtoolkit.org/protocols/view/630901.[3] Any skin conductance device that records continuously at a rate of 5 samples per second or higher and any h eart rate measurement device that records continuously at a rate of 20 samples per second or higher may be used.

Concept Map: Baseline and Trauma Challenge Psychophysiological Recordings

A sponsor should represent the collected skin conductance data in an appropriate SDTMIG domain and any derived data in an appropriate ADaM dataset. Example 1 shows how the actual collected data may be represented in an SDTMIG domain.

PTSD patients have been reported to have a reduced capacity to suppress fear under safe conditions. A startle response test, which is a psychophysiological test, is used to investigate this reduced capacity to suppress fear. The startle response is measured by exposing the subject to various danger and safety cues and measuring recordings of the eyeblink muscle contraction using an electromyogram (EMG). The following concept map provides an overview of the measurement of the startle response. An individual study would typically have a protocol describing the stimuli, the number of times the set of stimuli are repeated (blocks) during the testing session, and the number of times within each block the specific stimuli are repeated (trials).  

Concept Map: Startle Data

All collected data that supports review, reporting, and analysis should be submitted. There are cases where a large volume of raw data is generated by a device many times per second (e.g., data collected during startle response tests). In such cases, summary data that are received as an output from a device may be represented in an SDTM dataset (e.g., average over a fixed period of time) instead of the full set of the raw data. Even though summary data are submitted, health authorities may request the submission of all of the raw data from the device. In Example 1, only the peak value is included in the dataset; in Example 2, the mean peak values are included.

Subjects diagnosed with PTSD often report sleep problems. A polysomnography (PSG) test records certain body functions as the subject sleeps, and can be used to diagnose sleep disorders. A full PSG is typically conducted in a sleep center, but it may sometimes be conducted using a portable device. Tests are usually performed during a subject's normal sleep pattern. The PSG is used to diagnosis various sleep disorders (e.g., narcolepsy, obstructive sleep apnea, periodic limb movement disorders). A home sleep apnea test (HSAT) may also be used to evaluate sleep disorders. The PSG monitors many body functions, including brain activity, eye movements, muscle activity, heart rhythm, and respiratory functions. For information on standards for the use of these monitoring devices, see the Further Reading Sources in Appendix D, References.

The American Academy of Sleep Medicine's (AASM) Manual for the Scoring of Sleep and Associated Events (available at https://aasm.org/clinical-resources/scoring-manual/) is updated annually; when presenting sleep test results, it is important to document which version was used. The AASM manual provides rules for scoring sleep stages, arousal, respiratory events during sleep, movements during sleep, and cardiac events.

All collected data that supports review, reporting, and analysis should be submitted. There are cases where a large volume of raw data is generated by a device many times per second (e.g., data collected during PSG tests). In this case, summary data that are received as an output from a device may be represented in an SDTM dataset (e.g., average over a fixed period of time) instead of the full set of the raw data. Even though summary data are submitted, health authorities may request the submission of all of the raw data from the device.

Some routinely collected data are not specific to a therapeutic area, such as data collected to assess the subject's history, substance use by the subject, and prior concomitant medications. The CDASH and SDTM foundational standards provide advice for the representation of such data. This section discusses how to represent data collected using the Emory Treatment Resistance Interview for PTSD (E-TRIP; available at https://pid.emory.edu/ark:/25593/p2wrj).[5]  

Emory Treatment Resistance Interview for PTSD (E-TRIP)

E-TRIP was developed to evaluate previous treatment outcomes in PTSD. Treatments for PTSD may include psychotherapy or medications. Typical psychotherapy treatments include Prolonged Exposure (PE), Cognitive Processing Therapy (CPT), and Eye Movement Desensitization and Reprocessing (EMDR). Medication treatments may include approved selective-serotonin reuptake inhibitors (SSRIs), as well as off-label use of SSRIs, monoamine oxidase inhibitors (MAOIs), sedatives, and other antidepressants. C linician-administered questions are included to assess the adequacy and benefit derived from past treatment trials.[5] 

E-TRIP is similar to other clinical classifications measures that have been described in the literature in that it uses a score that serves as a surrogate for, or ranking of, the disease status. The interviewer reviews and interprets a subject's status with respect the use of previous treatments for PTSD. The evaluations of each of the treatments by the interviewer is considered a clinical classification (represented in the Disease Response and Clin Classification (RS) domain), whereas the actual administration information for each treatment is represented in the Concomitant/Prior Medications (CM) and the Procedures (PR) domain.

Within CDISC, Clinical Classification instruments represented in the RS domain fall under the concept of Questionnaires, Ratings and Scales (QRS), and CDISC publishes standard QRS Supplements to the SDTMIG along with controlled terminology. Once generated, the Clinical Classifications Supplement is posted on the CDISC website (http://www.cdisc.org/qrs). Sponsors should always consult current QRS Supplements for guidance on submitting such data.

This section illustrates the use of the Analysis Data Model (ADaM) to create a dataset to support the analysis of skin conductance. The example uses the measures collected as part of the Baseline and Trauma Challenge Psychophysiological Recordings described in Section 3.3, Skin Conductance. As previously noted, a high volume of collected values are generated when measuring skin conductance; using these individual measures directly for analyses is not practical. Instead, measures of skin conductance are often divided into pre-defined segments or time spans and then a summary measure (e.g., average, median, maximum) is determined for this segment. The summary measures for each segment are then used to derive analysis endpoints (e.g., changes in skin conductance over time). Different types of statistical methodologies and endpoints are applicable when analyzing skin conductance. The derived measures presented in this example are part of the protocol described by this vendor (available at https://www.phenxtoolkit.org/).[4]

As described in Section 3.3, Skin Conductance, skin conductance is measured during three defined phases: Baseline, Trauma Interview, and Trauma Imagery. According to the vendor, changes in skin conductance are of interest both within a phase and across phases. Therefore, baseline measures for each phase of the procedure need to be derived so that change from baseline can be calculated both within a phase and across phases. Example 1 uses the ADaM Basic Data Structure (BDS) to model these derived parameters using the collected skin conductance measures in the Nervous System Findings (NV) domain. Values of baseline are required to be defined within each phase of the interview, which requires the use of the BASETYPE variable to distinguish the set of records that utilize a given derivation of baseline.

This example is not intended to illustrate every possible variable that might be included in datasets created for statistical analysis of skin conductance. In addition to the selected variables shown in the example, a typical analysis dataset would contain additional subject-level variables, as well as variables to support traceability. In addition, this example is intended to be descriptive and illustrative of the use of the ADaM model, and should not be interpreted as the complete or the sole analysis requirements. The metadata and derivations presented are for illustrative purposes and attempt to closely follow the derivations described by the vendor. Refer to ADaM v2.1 and Version 1.1 of the ADaM Implementation Guide (ADaMIG) for required background about ADaM and the ADaM data structures.

Example 1

ADSCD Dataset Metadata

ADSCD Variable Metadata

PARAMCD [CL.PARAM]

Parameter Value Level List - ADSCD [AVAL]

The following table lists the non-standard variables used in this document, and gives their parent domain and variable-level metadata.

(Parenthesis indicates CDISC/NCI codelist)

Works Cited

1. US Department of Veterans Affairs, PTSD: National Center for PTSD. How common is PTSD? https://www.ptsd.va.gov/public/PTSD-overview/basics/how-common-is-ptsd.asp. Updated October 3, 2016. Accessed September 17, 2018.
2. National Institute of Mental Health. Post-traumatic stress disorder. https://www.nimh.nih.gov/health/topics/post-traumatic-stress-disorder-ptsd/index.shtml. Updated February 2016. Accessed September 17, 2018.
3. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington, VA: American Psychiatric Association; 2013.
4. Hamilton CM, Strader LC, Pratt JG, et al. (2011) The PhenX toolkit: get the most from your measures. Am J Epidemiol. 2011 Aug 1;174(3):253-260. doi:10.1093/aje/kwr193.
5. Dunlop BW, Kaye JL, Youngner C, Rothbaum B. Assessing treatment-resistant posttraumatic stress disorder: the Emory Treatment Resistance Interview for PTSD (E-TRIP). Behav Sci. 2014;4(4):511-527. https://pid.emory.edu/ark:/25593/p2wrj

Further Reading

• Practice parameters for the indications for polysomnography and related procedures. Polysomnography Task Force, American Sleep Disorders Association Standards of Practice Committee. Sleep. 1997;20:406-422. doi:10.1093/sleep/20.6.406

• Practice parameters for the use of portable recording in the assessment of obstructive sleep apnea. Standards of Practice Committee of the American Sleep Disorders Association Report. Sleep. 1994;17:372-377.

• Rechtschaffen A, Kales A, eds. A manual of standardized terminology, techniques, and scoring system for sleep stages of human subjects . Washington DC: Public Health Service, U.S. Government Printing Service; 1968.

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.

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