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Induction
|
Chemo + RT 3-5 w
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
Page 238
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CDISC. © 2007. All rights reserved July 25, 2007
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
CBST
|
Addl Chemo + Rad Boost 4
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Induction CR
|
No Progression and eligible and consented to surgery 10
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
FU
|
Off Treatment Follow-up CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
up
|
The Trial Arms dataset for the trial is also simpler for the two-Arm version of the trial. Note that this version has rules in the TRANS column that appeared in the BRANCH column in the five-Arm version of the Trial Arms dataset. In the five-Arm view of the trial, these decision points are considered to be branches between Arms, while in the two-Arm view of the trial, these are considered to represent variations within an Arm. Trial Arms dataset for Example Trial 7, as a tow-Arm trial
|
[
"SDTM.pdf"
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SDTM.pdf
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pdf
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[
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pdf
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glossary.json
| null | null |
DEFINING EPOCHS
|
The series of examples in Section 7.2.2 provides a variety of scenarios and guidance about how to assign Epoch in those scenarios. In general, assigning Epochs for blinded trials is easier than for unblinded trials. The blinded view of the trial will generally make the possible choices clear. For unblinded trials, the comparisons that will be made between Arms can guide the definition of Epochs. For trials that include many variant paths within an Arm, comparisons of Arms will mean that subjects on a variety of paths will be included in the comparison, and this is likely to lead to definition of broader Epochs. 7.2.3.4
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
RULE VARIABLES
|
The Branch and Transition columns shown in the example tables are variables with a Role of 'Rule.' The values of a Rule variable describe conditions under which something is planned to happen. At the moment, values of Rule variables are text. At some point in the future, it is expected that these will become executable code. Other Rule variables are present in the Trial Elements and Trial Visits datasets. CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
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pdf
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glossary.json
| null | null |
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[
"SDTM.pdf"
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SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TAETORD
|
Orders the Elements within an Arm ETCD, ELEMENT Name an Element within the Arm
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TABRANCH
|
Indicate a branch in the trial design at the end of the Element. A branch may be a randomization or another method of assigning subjects to Arms
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TATRANS
|
Indicates how to decide where a subject should go at the end of the Element. The default rule is, 'go to the next Element in sequence.'
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Epoch
|
1 hour after start of Treatment
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TE
|
10 10 mg First dose of a treatment Epoch, where dose is 10 mg drug 2 weeks after start of Element
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TEENRL
|
Rule for End of Element Char
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
Page 244
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[
"SDTM.pdf"
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SDTM.pdf
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pdf
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glossary.json
| null | null |
Informed Consent
|
Screening assessments are complete, up to 2 weeks after start
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Eligibility confirmed
|
2 weeks after start of Element
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Placebo
|
1 2 3 4 5 CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
P14D
|
Trial Elements Dataset for Example Trial 2
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
P21D
|
The Trial Elements dataset for Example Trial 4 illustrates Element end rules for Elements that are not of fixed duration. The Screen Element in this study can be up to 2 weeks long, but may end earlier, so is not of fixed duration. The Rest Element has a variable length, depending on how quickly WBC recovers. Note that the start rules for the A and B Elements have been written to be suitable for a blinded study. Trial Elements Dataset for Example Trial 4
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Trt A
|
First dose of treatment in Element, where drug is
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Trt B
|
First dose of treatment Element, where drug is Treatment B 5 days after start of Element
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
P28D
|
CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
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[
"SDTM.pdf"
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pdf
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glossary.json
| null | null |
Step Question
|
How step question is answered by information in the Trial Design datasets 1 Should the subject leave the current Element? Criteria for ending the current Element are in TEENRL in the TE dataset. 2 Which Element should the subject enter next? • If there is a branch point at this point in the trial, evaluate criteria described in TABRANCH (e.g., randomization results) in the TA dataset • otherwise, if TATRANS in the TA dataset is populated in this Arm at this point, follow those instructions • otherwise, move to the next Element in this Arm as specified by TAETORD in the TA dataset. 3 What does the subject do to enter the next Element? The action or event that marks the start of the next Element is specified in TESTRL in the TE dataset Note that the subject is not "in limbo" during this process. The subject remains in the current Element until Step 3, at which point the subject transitions to the new Element. There are no gaps between Elements. From this table, it is clear that executing a transition depends on information that is split between the Trial Elements and the Trial Arms datasets. It can be useful, in the process of working out the Trial Design datasets, to create a dataset that supplements the Trial Arms dataset with the TESTRL, TEENRL, and TEDUR variables, so that full information on the transitions is easily accessible. However, such a working dataset is not an SDTM dataset, and should not be submitted. The following table shows a fragment of such a table for Example Trial 4. Note that for all records that contain a particular Element, all the TE variable values are exactly the same. Also, note that when both TABRANCH and TATRANS are blank, the implicit decision in Step 2 is that the subject moves to the next Element in sequence for the Arm.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
Screening assessments
|
are complete, up to 2
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Last dose of previous
|
treatment cycle + 24 hrs 16 days after start of
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
P5D
|
Note that both the first and fourth rows of this dataset involve the same Element, Trt A, and so TESTRL is the same for both. The activity that marks a subject's entry into the fourth Element in Arm A is "First dose of treatment Element, where drug is Treatment A." This is not the subject's very first dose of Treatment A, but it is their first dose in this Element, which is in the Second Treatment Epoch. 7.3.4 RECAP OF TRIAL ELEMENTS VARIABLES
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TESTRL
|
Describe the "transition event" that defines the start of the Element TEENRL, TEDUR Describe when the Element should end (TEDUR is used only if the Element is of fixed duration) CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
Page 248
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[
"SDTM.pdf"
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SDTM.pdf
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pdf
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glossary.json
| null | null |
TV
|
5 2 weeks after start of Treatment
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Start of Screen Epoch
|
1 hour after start of Visit 2
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
At Trial Exit
|
Although the start and end rules in this example reference the starts and ends of Epochs, the start and end rules of some Visits for trials with Epochs that span multiple Elements will need to reference Elements rather than Epochs. When an Arm includes repetitions of the same Element, it may be necessary to use TAETORD as well as an Element name to specify when a Visit is to occur. 7.4.3 TRIAL VISITS ISSUES 7.4.3.1 IDENTIFYING TRIAL VISITS In general, a trial's Visits are defined in its protocol. The term 'Visit' reflects the fact that data in out-patient studies is usually collected during a physical Visit by the subject to a clinic. Sometimes a Trial Visit defined by the protocol may not correspond to a physical Visit. It may span multiple physical Visits, as when screening data may be collected over several clinic Visits but recorded under one Visit name (VISIT) and number (VISITNUM). A Trial Visit may also represent only a portion of an extended physical Visit, as when a trial of in-patients collects data under multiple Trial Visits for a single hospital admission. Diary data and other data collected outside a clinic may not fit the usual concept of a Trial Visit, but the planned times of collection of such data may be described as 'Visits' in the Trial Visits dataset if desired. 7.4.3.2
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TRIAL VISIT RULES
|
Visit start rules are different from Element start rules because they usually describe when a Visit should occur, while Element start rules describe the moment at which an Element is considered to start. There are usually gaps between Visits, periods of time that do not belong to any Visit, so it is usually not necessary to identify the moment when one Visit stops and another starts. However, some trials of hospitalized subjects may divide time into Visits in a manner more like that used for Elements, and a transition event may need to be defined in such cases. Visit start rules are usually expressed relative to the start or end of an Element or Epoch, e.g., '1-2 hours before end of First Wash-out' or '8 weeks after end of 2nd Treatment Epoch.' Note that the Visit may or may not occur during
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
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glossary.json
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[
"SDTM.pdf"
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pdf
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glossary.json
| null | null |
CONTINGENT VISITS
|
Section 5.3.1, which describes the Subject Visits dataset, describes how records for unplanned Visits are incorporated. It is sometimes difficult to decide exactly what constitutes an "unplanned Visit" versus a "contingent Visit, " a Visit that is contingent on a "trigger" event, i.e., a Visit that the protocol says should take place under certain circumstances. Also, for certain contingent assessments, it can be difficult to decide whether performing that assessment constitutes a Visit. Contingent Visits can be included in the Trial Visits table, with start rules that describe the circumstances under which they will take place. Since values of VISITNUM must be assigned to all records in the Trial Visits dataset, a contingent Visit must be assigned a value of VISITNUM, but that value may not be a "chronological" value, due to the uncertain timing of the Visit. 7.4.4 RECAP OF TRIAL VISITS VARIABLES
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Identifiers
|
VISIT, VISITNUM, VISITDY Name and order the Visits ARM, ARMCD Blank if Visit schedule does not depend on Arm. Name of the ARM if Visit schedule does depend on Arm.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TVSTRL
|
Rule describing when the Visit should start. Usually expressed relative to the start or end of an Epoch or Element.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TVENRL
|
Rule describing when the Visit should end. Usually expressed relative to the start of an Epoch or Element. CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
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pdf
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glossary.json
| null | null |
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[
"SDTM.pdf"
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SDTM.pdf
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pdf
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glossary.json
| null | null |
Char TS
|
Identifier Two-character abbreviation for the domain.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
OBJPRIM
|
Trial Primary Objective TO INVESTIGATE THE SAFETY AND EFFICACY OF TWO DOSES 14
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Trial Title
|
No controlled terminology. Included as a value in the list of controlled terms, codelist Trial Summary Parameter Test Code (C66738)
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
TRT
|
Reported Name Of Test Product Investigational New Drug 15
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
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[
"SDTM.pdf"
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SDTM.pdf
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pdf
|
glossary.json
| null | null |
and Safety of New
|
Drug (up to 16 mg/day) in the
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
SAFETY
|
CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ADDON
|
Test Product Is Added On To
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
DOSE
|
Dose Per Administration 200 9
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
OBJSEC
|
Trial Secondary Objective COMPARE SAFETY PROFILES
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
PLANSUB
|
Planned Number Of Subjects 210 16
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
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glossary.json
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THE --GRPID VARIABLE
|
The optional grouping identifier variable --GRPID is permissible in all domains that are based on the general observation classes. It is used to identify relationships between records within a USUBJID within a single domain. An example would be Intervention records for a combination therapy where the treatments in the combination varies from subject to subject. In such a case, the relationship is defined by assigning the same unique character value to the --GRPID variable. The values used for --GRPID can be any values the sponsor chooses; however, if the sponsor uses values with some embedded meaning (rather than arbitrary numbers), those values should be consistent across the submission to avoid confusion. It is important to note that --GRPID has no inherent meaning across subjects or across domains. Using --GRPID in the general-observation-class datasets can reduce the number of records in the RELREC, SUPP--, and CO datasets when those datasets are submitted to describe relationships/associations for records or values to a ‘group’ of general-observation-class records. 8.1.1 --GRPID EXAMPLE The following table illustrates how to use --GRPID in the Concomitant Medications (CM) domain to identify a combination therapy. In this example, both subjects 1234 and 5678 have reported two combination therapies, each consisting of three separate medications. Each component of a combination is given the same value for CMGRPID. Note that for USUBJID 1234, the medications for CMGRPID = ‘COMBO THPY 1’ (Rows 1-3) are different from the medications for CMGRPID = ‘COMBO THPY 2 (Rows 4-6). Likewise, for USUBJID 5678, the medications for CMGRPID = ‘COMBO THPY 1’ (Rows 7-9) are different from the medications for CMGRPID = ‘COMBO THPY 2’ (Rows 10-12). Additionally, the medications for Subject 1234 CMGRPID = ‘COMBO THPY 1’ and CMGRPID = ‘COMBO THPY 2’ (Rows 1-6) are different from the medications for Subject 5678 CMGRPID = ‘COMBO THPY 1’ and CMGRPID = ‘COMBO THPY 2’ (Rows 7-12). This example illustrates how CMGRPID groups information only within a subject within a domain. Row STUDYID DOMAIN USUBJID CMSEQ CMGRPID
|
[
"SDTM.pdf"
] |
SDTM.pdf
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pdf
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glossary.json
| null | null |
mg
|
2004-03-21 2004-03-22 CDISC, © 2007. All rights reserved
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[
"SDTM.pdf"
] |
SDTM.pdf
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pdf
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glossary.json
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[
"SDTM.pdf"
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pdf
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glossary.json
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Study Identifier Char
|
Unique identifier for a study
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
In the sponsor's operational database, these datasets may have existed as either separate datasets that were merged
|
for analysis, or one dataset that may have included observations from more than one general observation class (e.g., Events and Findings). The value in IDVAR must be the name of the key used to merge/join the two datasets. In the above example, the --SPID variable is used as the key to identify the related observations. The values for the --SPID variable in the two datasets are sponsor defined. Although other variables may also serve as a single merge key when the corresponding values for IDVAR are equal, --SPID or --REFID are typically used for this purpose. The variable RELTYPE identifies the type of relationship between the datasets. The allowable values are ONE and MANY. This information defines how a merge/join would be written, and what would be the result of the merge/join. The possible combinations are: 1. ONE and ONE. This combination indicates that there is NO hierarchical relationship between the datasets and the records in the datasets. Only One record from each dataset will potentially have the same value of the IDVAR within USUBJID. 2. ONE and MANY. This combination indicates that there IS a hierarchical (parent/child) relationship between the datasets. One record within USUBJID in the dataset identified by RELTYPE=ONE will potentially have the same value of the IDVAR with many (one or more) records in the dataset identified by RELTYPE=MANY. 3. MANY and MANY. This combination is unusual and challenging to manage in a merge/join, and may represent a relationship that was never intended to convey a usable merge/join (such as in described for PC and PP in Section 6.3.10.5). Since IDVAR identifies the keys that can be used to merge/join records between the datasets, the root values (i.e., SPID in the above example) for IDVAR must be the same for both records with the same RELID. --SEQ cannot be used because --SEQ only has meaning within a subject within a dataset, not across datasets.
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"SDTM.pdf"
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pdf
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glossary.json
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Abbreviation
|
Char * Domain Abbreviation of the Parent record(s).
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[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
Variable
|
Char * Identifying variable in the dataset that identifies the related record(s). Examples: --SEQ, --GRPID.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Variable Name
|
Char * The short name of the Qualifier variable, which is used as a column name in a domain view with data from the parent domain. The value in QNAM cannot be longer than 8 characters, nor can it start with a number (e.g., '1TEST'). QNAM cannot contain characters other than letters, numbers, or underscores. This will often be the column name in the sponsor’s operational dataset.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
Evaluator
|
Char * Used only for results that are subjective (e.g., assigned by a person or a group). Should be null for records that contain objectively collected or derived data. Some examples include ADJUDICATION COMMITTEE, STATISTICIAN, DATABASE ADMINISTRATOR, CLINICAL COORDINATOR, etc.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
SPUNFL
|
Any Time in Spec. Unit?
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
RLCNDF
|
Visit Related to Study Med Cond.?
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
SUPPQUAL Variables
|
HO Events General Observation Class Custom Dataset with SUPPHO Supplemental Qualifiers dataset: The shading in the two datasets below is used to differentiate the three hospitalization records for which data are shown. Note that for Rows 1-7 in the SUPPHO dataset, RDOMAIN= HO, USUBJID = 0001, IDVAR = HOSEQ, and IDVARVAL = 1. These three values (along with STUDYID and USUBJID) allow these seven SUPPHO records to be linked to the HO dataset record in Row 1 which has value in HOSEQ = 1 for Subject 0001. Likewise, SUPPHO dataset rows 8-14 are linked to the HO dataset record where HOSEQ = 2 for the same subject, and SUPPHO dataset rows 15-21 are linked to the HO dataset record where HOSEQ =1 for Subject 0002. ho.xpt: Hospitalization (modeled as a custom Events general-observation-class domain) Row STUDYID DOMAIN USUBJID HOSEQ
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
HO
|
0002 1 Hospitalization 2004-01-21 2004-01-22 P1D
|
[
"SDTM.pdf"
] |
SDTM.pdf
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pdf
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glossary.json
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[
"SDTM.pdf"
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pdf
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glossary.json
| null | null |
HOSEQ
|
1 RLCNDF Visit Related to Study Med Cond.?
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Comments Examples
|
The table below shows the following: • A comment unrelated to any specific domain or record, because it was collected on a separate comments page/screen (Row 1) • A comment related to a specific domain (PE in this example), but not to any specific record because it was collected on the bottom of the PE page without any indication of specific records it applies to. COREF is populated with the text ‘VISIT 7’ to show this comment came from the VISIT 7 PE page (Row 2) • Comments related to parent records:
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
A comment related to multiple VS records with VSGRPID=’VS2’
|
• Three options are available for representing a comment unrelated to any specific general observation class record(s) because it was collected on a separate comments page/screen, but the page was associated with a specific visit:
|
[
"SDTM.pdf"
] |
SDTM.pdf
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pdf
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glossary.json
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CDISC. © 2007. All rights reserved July 25, 2007
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SDTM.pdf
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pdf
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A comment related to a Subject Visit record in SV (Row 6). The RDOMAIN variable is populated
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with SV (the Subject Visits domain) and the variables IDVAR and IDVARVAL are populated with the key variable name and value of the parent Subject-Visit record.
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[
"SDTM.pdf"
] |
SDTM.pdf
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pdf
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glossary.json
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COREF is populated to indicate that the comment reference is “VISIT 4”. RDOMAIN, IDVAR,
|
and IDVARVAL are not populated.
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[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
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VISIT 4
|
PRINCIPAL INVESTIGATOR PRINCIPAL INVESTIGATOR 4 8.6 RELATING FINDINGS OBSERVATIONS TO EVENTS OR INTERVENTIONS USING --OBJ The Clinical Findings domain introduces the --OBJ variable. A record in CF may have a parent record in an event or intervention domain, although a parent record in another domain is not required. When there is a parent-child relationship between an event or intervention record and a CF record, --OBJ establishes that relationship. See the following for further information: • Section 2.4.3 for a definition of the --OBJ variable • Section 6.3.11 for the Clinical Findings domain definition and examples illustrating the use of the --OBJ variable. CDISC, © 2007. All rights reserved
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"SDTM.pdf"
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FINDINGS ABOUT EVENTS
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This section discusses events, findings, and findings about events. The relationship between interventions, findings, and findings about interventions is similar. The names of the new Clinical Events (Section 6.2.5) and Clinical Findings (Section 6.3.11) domains are similar because both are intended to hold data about "clinical" events or conditions. The Clinical Findings domain was specially created to store findings about events. This section discusses events and findings generally, but it is particularly useful for understanding the distinction between the CE and CF domains. There may be several sources of confusion about whether a particular piece of data belongs in an event record or a findings record. One generally thinks of an event as something that happens spontaneously, and has a beginning and end; however, one should consider the following: • Events of interest in a particular trial may be pre-specified, rather than collected as free text. • Some events may be so long lasting in that they are perceived as "conditions" rather than "events", and their beginning and end dates are not of interest. • Some variables or data items one generally expects to see in an Events record may not be present. For example, a post-marketing study might collect the occurrence of certain adverse events, but no dates. • Properties of an Event may be measured or assessed, and these are then treated as findings about events, rather than as events. • Some assessments of events (e.g., severity, relationship to study treatment) have been built into the SDTM Events model as qualifiers, rather than being treated as findings about events. • Sponsors may choose how they define an Event. For example, adverse event data may be submitted using one record that summarizes an event from beginning to end, or using one record for each change in severity. The structure of the data being considered, although not definitive, will often help determine whether the data represent an Event or a Finding. The structural questions below may assist sponsors in deciding where data should be placed in SDTM.
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"SDTM.pdf"
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SDTM.pdf
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CDISC. © 2007. All rights reserved July 25, 2007
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glossary.json
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Appendices
|
APPENDIX A: CDISC SDS TEAM *
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
Company
|
Fred Wood, Team Leader Octagon Research Solutions, Inc. Wayne Kubick, Past Team Leader
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
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glossary.json
| null | null |
FDA Observer
|
* Individuals having met membership criteria as of publication date. CDISC, © 2007. All rights reserved
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ATC code
|
Anatomic Therapeutic Chemical code from WHO Drug
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
AUC
|
Area under the curve (PK and PD)
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
BID
|
Twice a Day (Latin: bis in die)
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
CDISC
|
Clinical Data Interchange Standards Consortium
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
CMAX
|
Concentration maximum; used in pharmacokinetics and bioequivalence testing to indicate maximum plasma concentration for a drug
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
CTCAE
|
Common Terminology Criteria for Adverse Events
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Dataset
|
A collection of structured data in a single file
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
Health Level 7
|
HPLC/MS High Performance Liquid Chromatography/Mass Spectrometer
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ICD9
|
International Classification of Diseases, 9th revision. See also MedDRA.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ICH
|
International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ICH E2A
|
ICH guidelines on Clinical Safety Data Management : Definitions and Standards for Expedited
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ICH E3
|
ICH guidelines on Structure and Content of Clinical Study Reports
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ICH E9
|
ICH guidelines on Statistical Principles for Clinical Trials
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ISO 3166
|
ISO country codes. The SDTM uses the three-character format.
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
ISO 8601
|
ISO character representation of dates, date/times, intervals, and durations of time
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
LOINC
|
Logical Observation, Identifiers, Names, and Codes
|
[
"SDTM.pdf"
] |
SDTM.pdf
|
pdf
|
glossary.json
| null | null |
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