1 / 27

Change Analysis for CDISC SDTM 1.5

Change Analysis for CDISC SDTM 1.5. Michael DiGiantomasso February 27, 2017. NJ CDISC User Group Hosted by Novartis. Contents. Detailed Changes (12) Intervention Variables Event Variables Findings Variables Identifier Variables for all classes

marcl
Download Presentation

Change Analysis for CDISC SDTM 1.5

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Change Analysis for CDISC SDTM 1.5 Michael DiGiantomasso February 27, 2017 NJ CDISC User Group Hosted by Novartis

  2. Contents • Detailed Changes (12) • Intervention Variables • Event Variables • Findings Variables • Identifier Variables for all classes • Timing Variables for all classes • Domain Specific variables • Domains (Disease Milestones) • Overview (4) • Purpose • History • Version Guidance • Conclusions (4) • Summary & Impact • Questions • Change Summary (3) • 1.4 to 1.5 Changes • Variable to TA Matrix • Constant WIP as new TAs develop

  3. Purpose • metadata dictionary of all basic modeling concepts • Class • Domain • Variable • Concepts can be arranged in different combinations for various use cases: IGs, TAUGs, etc. • Combinations are given more meaning when bound with terminology, rulesand assumptions in addition with their surrounding metadata and population • Domain Class is a static building block. Sponsors cannot create new classes • Interventions, Events, Findings • Special Purpose – SE,DM,SV,CO,SM,TM,TD • Trial Design – TE,TA,TV,TX,TI,TS • Relationship – POOLDEF,RELSUB,APRELSUB,RELREC,SUPP-- • Associated Persons - APxx • When a building block concept (domain, variable) does not exist, a sponsor may create… • custom domain (within a general observation class) • custom variable (SUPPQUAL QNAM) • New versions of SDTM have an opportunity to standardize and prevent unnecessary custom variables in form of SUPPQUALS The “building blocks”

  4. Building Block Metadata Green highlights are in scope Page 8 of SDTM 1.5, paraphrased “…Not all variables described …are appropriate for all implementations. Please refer to the IG for specific info on any restrictions” The model will not tell you which variables are SEND or SDTM specific, with exception of some domain specific variables like EXMETHOD

  5. History 11 yrs – 4 minor updates “Black Box” / AKA the exotics 2.5 yrs later, 8 months to the day Q. What does 1.5 do for me ? A. Enables a provisional and final SEND IG, and 1 provisional SDTM IG

  6. Version Confusion/Overload PGx example • Quotes from PGx sources on CDISC website and PDF documents • “…it introduces new variables and constructs that will be added to the forthcoming SDTM v1.5” • “…intended to correspond to version 1.5” • “…should be used in close concert with the current version of the CDISC SDTM” • With exception of the 3 highlighted, I can’t use these variables to consistently talk about Biomarkers and Genetics.

  7. Change Metrics • 25 changes, but…23 unique concepts • 18 new general variables - USCHFL is counted 3 times • 3 new domain specific variables • 2 new domains(with domain specific variables) 18

  8. 1.4 to 1.5 : 25 additions IC - Implantation Classification SENDIG DART 1.0

  9. Variable to TA Matrix • Variables mentioned in a TAUG. • does not indicate a TAUG requirement

  10. Intervention Variables • USCHFL - Unscheduled Flag • SEND only: Not to be used with human clinical trials. • Record Qualifier • Expected values are Y or null. • Indicates whether the timing of a performed test or observation was unscheduled. • If a test/observation was performed based upon a protocol-defined schedule, it should be null. • not needed when information on planned assessments is provided in… • Trial Visits (TV) • Subject Visits (SV)

  11. Event Variables • USCHFL- Unscheduled Flag • CDISC Public Comment Resolution • addition of --EVAL, --EVALID, & --ACPTFL variables fundamentally changes the cardinality of the Events class these variables will not be added at this time. • The handling of adjudication data in general needs further discussion. • These variables have been removed from the Events Class in SDTM v1.5 • EVAL- Evaluator • Record Qualifier • Role of the person who provided an evaluation. • Used only for results that are subjective (e.g., assigned by a person or a group). • Examples: ADJUDICATION COMMITTEE, INDEPENDENT ASSESSOR, RADIOLOGIST • EVALID - Evaluator Identifier • Variable Qualifier of –EVAL • Used to distinguish multiple evaluators with the same role recorded in --EVAL. • Examples: ADJUDICATOR 1, ADJUDICATOR 2, CEC ADJUDICATOR • ACPTFL - Accepted Record Flag • Record Qualifier • In cases where more than one assessor provides an evaluation of an event, this identifies the accepted evaluation. • Expected values can include Y, N or null. • This is not intended to be an analysis flag to indicate acceptability for a given analysis

  12. Findings Variables for Result References • All are Variable Qualifiers with labels starting with “Reference Result “ • Example found in SDTM 1.5 - value from a predicted spirometry test’s normal value • possibly based on • subject demographics • test code • category ,etc..

  13. Findings Variables (continued) • LOBXFL - Last Observation Before Exposure Flag • Record Qualifier • Operationally-derived indicator • should be “Y” or null. • identifies last non-missing value prior to RFXSTDTC • DM.RFXSTDTC - First date of exposure to any protocol treatment/therapy • Seems to rival Baseline flag (BLFL) • FDA - Study Data Technical Conformance Guide, p24. mentions baseline flag • REPNUM - Repetition Number • Record Qualifier • incidence number of a repeated test within a given timeframe for the same test. • granularity level can vary, e.g., within a time point or within a visit. • Examples… • multiple blood pressure measurements • multiple analyses of a sample

  14. Findings Variables (continued) • NSPCES - Non-Host Organism Species • Grouping qualifier • Biological classification for a non-host organism. • Examples: BACTERIUM, HCV, HIV, PLASMODIA • CHRON - Chronicity of Finding • Variable Qualifier of --STRESC • Characterizes the duration of a biological process resulting in a finding • Examples: ACUTE, CHRONIC, SUBACUTE. • Important for immunosuppressive studies involving solid organ transplants • DISTR - Distribution Pattern of Finding • Variable Qualifier of --STRESC • Description of the finding’s distribution pattern within the examined area. • Examples: FOCAL, MULTIFOCAL, DIFFUSE • USCHFL- Unscheduled Flag

  15. Domain Specific Variables • ICIMPLBL- Implantation Site Label • SEND only, referenced in SENDIG DART 1.0, Implantation Classification domain • Record Qualifier • Place after after ICSTRESC • Context – when classifying implantations during a uterine exam in a repro toxstudy • describes the location/position of a fetal implantation site in the uterus or uterine horn • EXMETHOD - Method of Administration • SEND ONLY, permissible in SEND 3.1 IG • Record qualifier • Place after EXLOC • Method of administration of the treatment • Example: INFUSION. • For human trials, you would use EXROUTE • EGBEATNO - ECG Beat Number • EGORRES variable qualifier • Place after EGPOS • sequence number that identifies the beat within an ECG

  16. Identifier Variables for all classes • APID - Associated Persons ID • ID for a single, group or pool of associated person(s) • If APID identifies a pool, POOLDEF records must exist for each associated person • FETUSID- Fetus ID • SEND Only • identifies a fetus from a maternal subject for prenatal evaluations. • Unique per USUBJID across a study. • FOCID- Focus of Study Specific Interest • ID of a focus of study-specific interest on or within a subject/specimen • defined in the protocol for which a measurement, test, or exam was performed, such as a • drug application site, e.g., “Injection site 1”, “Biopsy site 1”, “Treated site 1”, • or a more specific focus, e.g., “OD” (right eye) or “Upper left quadrant of the back”. • RECID - Invariant Record ID • Business/Unique key from sponsor/source system (don’t confuse with –SEQ) • Unique study domain record key that remains invariant through subsequent versions of the dataset, even if the content of the record is modified. • When a record is deleted, this value must not be reused in current or future version of the domain. • Great for full life cycle traceability from collection (CDASH) to analysis (ADaM) and reporting

  17. Timing Variables for all classes • NOMDY- Nominal Study Day for Tabulations • nominal study day used by DC&R for grouping observation recs that may be scheduled to occur on different days into a single study day • NOMLBL- Label for Nominal Study Day • A label for a given value of –NOMDY (within a domain) as presented in the study report. SEND only DC&R = Data Collection & Reporting systems

  18. Disease Milestone Domains • First introduced in TAUG Diabetes 1.0 • TM – Trial Disease Milestone • Trial Design Class - Protocol Defined metadata for events not controlled by study schedule • Observations/activities • expectedto occur in the disease course • timing is of study interest • SM – Subject Disease Milestones • Special Purpose Class • record the timing, for each subject, of Disease Milestones defined in the TM

  19. Disease MilestoneTiming Variables for all classes Required when relating any general observation domain to a milestone in SM • MIDS- Disease Milestone Instance Name • Instance of a “Disease Milestone Type (MIDSTYPE)” found in TM metadata • unique within a subject. • MIDSDTC - Milestone date • RELMIDS - Relation to Milestone • IMMEDIATELY BEFORE, AT TIME OF, AFTER. • beforethe study (Diabetes Diagnosis Date) • duringthe study (Hypoglycemic Event) • Clinical Events (CE) example • one event is the Subject milestone • others events occur in relation to the subject milestone

  20. Disease Milestones in action Define it at Trial Level Patient summary and sequence of milestones • Actual occurrence of patient milestone, and other observations in relation to it. • Diagnosis would occur in MH. • In some cases, Meals, Conmeds and Interventions would be required or recorded in relation to a disease milestone… • which is shown next…

  21. Data links “back” to SM and TM Events ARE the Disease Milestone Special Purpose Subject Level Summary Trial Design Metadata Domains than can relate to a Disease Milestone TM SM EX MH ML CE FA AE LB CM CE RELREC • validation rules should be developed to • ensure that SM records point to a valid TM record • Show TM records that do not have any instantiated SM records • Others TA specific rules could be developed…

  22. Summary & Impact

  23. Summary Observations - SDTM & SEND SDTM 1.5 standardizes tabulation and qualification of data in relation to Disease Milestones Constant, record level Business/Unique keys which live and expire with the life of the record. Great for full life cycle traceability from collection to analysis IDs for associated persons and study specific interests Grouping by Non-Host Organism Species (findings) Chronicity and Distribution Pattern (findings) Reference result values which can be used to compare to actual result. This is an alternative way for comparing to normal ranges Flagging the Last non missing Observation Before 1st Exposure/treatment another level of granularity within a timepoint (TPT) to sequence multiple observations (such as blood pressure readings) Domain specific variables – a bit confusing at first. These seem like a permanent suppqual or NSV that lives in the domain without having to specify it in a general observation class, only to mark it as PROHIBITED in all other domain assumptions for that class.

  24. Summary Observations – SEND only SDTM 1.5 standardizes tabulation and qualification of data in relation to the following concepts Nominal Study Day for tabulations flagging unscheduled events for all types of data Fetal implantation sites for toxicology studies

  25. Impact • Enables final version of SENDIG 3.1 • “Enables” provisionalIGs PGx 1.0, DART 1.0 • Failure to include PGx variables first introduced in 2014 October seems tragic • Standards are critical in modernizing the FDA review process • There were no specific FDA requirements for this version • FDA reviewed the document internally in late 2015 and found no issues, but wanted to wait for a final version of an IG that implements SDTM 1.5 before deciding it’s catalog worthiness • Therefore, not on the Data Standards Catalog

  26. Conclusions • SDTM v1.5 is a positive step in the evolution of the standard. • New concepts can allow data in a predictable format for standardized reporting & analysis. • Metadata about versions & compatibility should be in a database…not in PDFs or web pages • SDTM (model) can be boiled down to 2 dimensions • List of Static classes and domains which can be added upon, like we see with SM and TM. • List of variables which grows horizontally with each release, in an effort to standardize what’s important to industry and therefore • Cut down in the vertical expansion of SUPPQUALs • Preventing misuse of data into variables not intended for that data (often to avoid SUPPQUALs) • Considering studies have 100s of millions of records translating into billions of data points…Is there a concern in too many variables to describe it all ? What is too many ? Imaginary SDTM 4.0 with variable count

  27. Questions https://www.pinnacle21.com/ https://www.cdisc.org/standards/foundational/sdtm

More Related