CDISC A complete course

SDTM : Study data tabulation model Introduction to clinical
Introduction to Clinical
1
Adverse event
2
SAE
3
ARM
4
Baseline
5
Randomization
6
Parallel
7
Crossover
8
DMC [Data Monitoring Committee ]
9
Eligible Criteria
10
Inclusion/Exclusion Criteria
11
Inform consent
12
Masking
13
Study Design
14
Study Documents
15
Study Start date
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Study Type
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Title
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Blinded Trails
ICH/GCP Guidelines
21 CRF Part 11
Clinical Research Methodology
1
Phase 1
2
Phase 2
3
Phase 3
4
Phase 4
aCRF Desigining
1
Rawdatasets
2
Blank CRF
3
SDTM Control Terminology Protocol
4
Blank Annotated aCRF
5
SDTM IG Guide
6
CDISC Annotation Rules.
Trail Designing
Purpose of Trail designing
1
Clearly and quickly grasp the design of a clinical trial
2
Compare the designs of different trials
3
Search a data warehouse for clinical trials with certain features
4
Compare planned and actual treatments and visits for subjects in a clinical trial
TA :Trail Arm
1
describes the sequences of Elements in each Epoch for each Arm, and thus describes the complete sequence of Elements in each Arm
TV : Trial Visits
1
describes the planned schedule of Visits
TI : Trial Inclusion/Exclusion Criteria
1
describes the inclusion/exclusion criteria used to screen subjects
TE : Trial Elements
1
describes the Elements used in the trial
Trial Summary
1
lists key facts (parameters) about the trial that are likely to appear in a registry of clinical trials.
TD: Trial Disease Assessment
1
provides information on the protocol-specified disease assessment schedule, and will be used for comparison with the actual occurrence of the efficacy assessments in order to determine whether there was good compliance with the schedule.
TM: Trial Disease Milestones
1
describes observations or activities identified for the trial which are anticipated to occur in the course of the disease under study and which trigger the collection of data.
Spec Designing
1
An SDTM Spec designing will be explained based on aCRF designing and docs
SDTM Domain in-depth domain explanation and programming conversion Techniques.
Models for Special Purpose Domains
DM Demographics
1
A special purpose domain that includes a set of essential standard variables that describe each subject in a Clinical study.
SV Subject Visits
1
A special purpose domain that contains the actual start and end data/time for each visit of each individual subject.
Models for Interventions Domains
CM Concomitant and Prior Medications
1
An interventions domain that contains concomitant and prior medications used by the subject, such as those given on an as needed basis or condition-appropriate medications
EX Exposure
1
An interventions domain that contains the details of a subject’s exposure to protocol-specified study treatment.
Models for Events Domains
AE Adverse Events
1
An events domain that contains data describing untoward medical occurrences in a patient…
DS Disposition
1
An events domain that contains information encompassing and representing data related to subject disposition
An events domain that contains information encompassing and representing data related to subject disposition
Findings About Events or Interventions FA
1
– A findings domain that contains the findings about an event or intervention that cannot be represented within an events or interventions domain record or as a supplemental qualifier.
Models for Findings Domains
LB Laboratory Test Results
1
A findings domain that contains laboratory test data such as hematology, clinical chemistry and urinalysis.
Cardiovascular System Findings (CV)
1
A findings domain that contains physiological and morphological findings related to the cardiovascular system, including the heart, blood vessels and lymphatic
Vital Signs
1
A findings domain that contains measurements including but not limited to blood pressure, temperature,respiration, body surface area, body mass index, height and weight.
Models for Relating Peer Records
RELREC Dataset
1
A Relating Peer Records domain that represents data of relationship records.
Migration
1
A brief explanation of migration techniques in real world with unix commands via unix putty
ADaM : Analysis data model
Fundamentals of the ADaM Standard
Standard ADaM Variables
1
ADaM Variable Conventions
2
General Variable Conventions
3
Timing Variable Conventions
4
Date and Time Imputation Flag Variables
5
Flag Variable Conventions
6
Variable Naming Fragments
The ADaM Subject-Level Analysis Dataset (ADSL)
1
ADSL Identifier Variables
2
Subject Demographics Variables
3
ADSL Population Indicator Variables
4
ADSL Treatment Variables
5
ADSL Dose Variables
6
Treatment Timing Variables
7
Subject-Level Period, Subperiod, and Phase Timing Variables
8
ADSL Subject-Level Trial Experience Variables
9
More concepts on Extra variables
The ADaM (OCCDS)
1
Working with ADAE Conversions with additional variables
2
Working with ADDS Conversions with additional variables
3
Working with ADCM Conversions with additional variables
4
Working with ADEX Conversions with additional variables
The ADaM Basic Data Structure (BDS)
1
1.Identifier Variables for BDS Datasets
2
2. Record-Level Treatment and Dose Variables for BDS Datasets
3
Record-Level Dose Variables for BDS Datasets
4
Timing Variables for BDS Datasets
5
Period, Subperiod, and Phase Start and End Timing Variables
6
Suffixes for User-Defined Timing Variables in BDS Datasets
7
Analysis Parameter Variables for BDS Datasets
8
PARAM, AVAL, and AVALC
9
Analysis Parameter Criteria Variables for BDS Datasets
10
Analysis Descriptor Variables for BDS Datasets
11
Analysis Visit Windowing Variables for BDS Datasets
12
Time-to-Event Variables for BDS Datasets
13
Toxicity and Range Variables for BDS Datasets
14
Flag Variables for BDS Datasets
15
BDS Population Indicators
16
Datapoint Traceability Variables
17
SDTM and ADaM Population and Baseline Flags diference
18
Creation of Derived Columns versus Creation of Derived Rows
19
Rules for the Creation of Rows and Columns
Working with BDS Conversion specs
1
Working with ADVS Conversion with additional Variables
2
Working with ADLB Conversion with additional variables
3
Working with ADTTE Conversion with additional Variables
Business Logics
1
A parameter-invariant function of AVAL and BASE on the same row that does not involve a transform of BASE should be added as a new column.
2
Creation of a New Parameter to Handle a Transformation
3
Creation of a New Parameter to Handle a Second System of Units
4
Creation of a New Row to Handle a Derived Analysis Timepoint
5
Creation of New Rows to Handle a Derived Analysis Timepoint When There is Value-Level Population Flagging
6
Creation of New Rows to Handle Imputation of Missing Values by Last Observation Carried Forward and Worst Observation Carried Forward
7
Creation of New Rows to Handle Imputation of Missing Values by Baseline Observation Carried Forward and Last Observation Carried Forward
8
Creation of Endpoint Rows to Facilitate Analysis of a Crossover Design
ADaM Methodology and Examples When the Criterion Has Multiple Responses
Extra Topics
1
Paired lab variables
2
Lab visit window techniques
3
Raw/Standard Names/Units
4
ADaM – DTYPE
5
ADAM Metadata Excel file
6
ISO8601 Dates, Partial Dates, Durations and Periods
7
Study Validation Checklists
8
Baseline Values
9
Change, Percent Change from Baseline Imputation Methods
TLFS: Tables Listings and Figures
Listing
1
Demographics and Baseline Characteristics safety population
2
Ae listing of treatment emergent adverse event
3
Subject Disposition
4
Vital Signs Safety Population
5
Exposure to Study Medication Safety Population
Summary tables
1
Demographic: Subject Demographics and Baseline Characteristics Safety Population
2
Adverse event
3
Summary of Overall Treatment Emergent Adverse Event (TEAE) Information Safety Population
4
Summary of Treatment Emergent Adverse Events (TEAE) by System Organ Class and Preferred Term Safety Population
5
Concomitant medication: Concomitant Treatment Phase Medications Safety Population
6
Exposure: Exposure to Study Medication Safety Population
7
Laboratory: Laboratory shift table
8
Vitals: Summary of Change from Baseline in Vital Signs Safety Population
9
Disposition: Subject Disposition.
Figures
1
Summary of Treatment-Emergent Adverse Events by Maximum CTCAE Grade
2
Summary of vitals sign safety population
3
Coagulation values by (mean of +/- ) values by visit
4
Kaplan-meier plot of time to first abnormal laboratory test values
5
% change in tumor size from baseline
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