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SDTM IG 3.1.2 PDF

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This User Guide follows version (V) of the CDISC Submission Data Standards and domain models. Revision History. Date. Version. CDISC SDTM Implementation Guide (SDS Version ) This is the approved implementation guide for Version 1 of the CDISC Study Data. With the evolution of changes to the SDTM data standards model which respective assumptions in SDTMIG version has played a great deal of efforts for.


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CDISC SDTM Implementation Guide (Version ) This information, which historically has been submitted as a pdf document named. The Standard can be downloaded as a zip file here. Please ensure you read all the documentation carefully. SDTM V & SDTM IG V Private Files: PDF. SDTMIG v provides the following enhancements, key additions and revisions to prior versions: Revised . SDTM V & SDTMIG V Release Date: 22 May File SDTMIG v Conformance Rules v, KB. PDF icon.

Human Clinical Trials Prepared by the. This is the implementation guide for Human Clinical Trials corresponding to Version 1. This Implementation Guide comprises version 3. Summary of Changes Released version reflecting all changes and corrections identified during comment period. Draft for comment. Released version reflecting all changes and corrections identified during comment period.

A Permissible variable should be used in a domain as appropriate when collected or derived. The order of variables in the CDISC domain models has been chosen to facilitate the review of the models and application of the models.

SDTMIG V SDTM Implementation Guide

Variables for the three general observation classes should be ordered with Identifiers first. The sponsor does not have the discretion to not submit permissible variables when they contain data.

Within each role. Should a permissible variable used in one or more split datasets not be included in the first dataset used in a SAS Set statement. Care is advised. The four-character dataset-name limitation allows the use of a Supplemental Qualifier dataset associated with the split dataset. For example.. QS36 for SF In such cases. See Section 6. If splitting Findings About by parent domain. Exceptions to this rule are described in Section 4. To eliminate any risk of a sponsor using a name that CDISC later determines to have a different meaning.

Should the datasets be appended in SAS. Page 22 November Note the use of codes beginning with X. Any letter or number may be used in the second position.

The nomenclature would include the additional one-to-two characters used to identify the split dataset e. QS Domains qscg. Note that submission of split SDTM domains may be subject to additional dataset splitting conventions as defined by regulators via technical specifications e.

All rights reserved Final Page 25 November This algorithm is applied across all values and may reference other SDTM datasets. Sponsors may specify additional details about the origin that may be helpful to the Reviewer e. Sponsors may specify additional details about the origin that may be helpful to the Reviewer in the Comments section of the define.

This does not apply to derived lab test results performed directly by labs or by devices. An origin of eDT refers to data collected via data streams such as laboratory.

Its purpose is to unambiguously communicate to the reviewer whether data was collected on a CRF and thus should be traceable to an annotated CRF. The designation of "eDT" as an origin in the define. Derived data are not directly collected on the CRF but are calculated by an algorithm or reproducible rule. The derivation is assumed to be performed by the Sponsor. The important concept here is that a domain is not limited by physical structure. A domain may be comprised of more than one physical dataset.

In some cases. This may include third party attributions by an adjudicator. Sponsor B then defines the following natural key for the PE domain. The word QNAM must be used as the first part of the name to indicate that the contributing variable exists in a dataset and this can be either a domain-specific SUPP-. Sponsor A chooses the following natural key for the PE domain: A value that is defined as part of the Trial Design preparation see Section 7.

When both derived and collected values are reported in a field. The following examples are illustrations of how to do this. A value that is determined by individual judgment by an evaluator other than the subject or investigator. Supplemental Qualifiers variables should be referenced in the natural key by using a two-part name.

Sponsor B might have used ultrasound as a method of measurement and might have collected additional information such as the makes and models of ultrasound equipment employed. These may include domain variables --LOC. Expressing the natural key becomes very important in this situation in order to communicate the variables that contribute to the uniqueness of a test.

In studies where multiple repetitive tests or measurements are being made.

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As a result. This domain includes both domain variables and Supplemental Qualifier variables that contribute to the natural key of each row and to describe the uniqueness of the test. The natural key is then defined as follows: Continuing with the PE domain example above. Taking just the phalanges. Using this approach in the above example. The sponsor considers the make and model information to be essential data that contributes to the uniqueness of the test result.

Use of variable names other than domain prefixes. Sponsors must use the predefined SDTM-standard labels in all standard domains. When creating custom domains based on the General Observation Classes. Variable descriptive names labels. Special-Purpose domains see Section 5. The two-character domain code is limited to A to Z for the first character. This limitation will be in effect until the use of other formats such as XML becomes acceptable to regulatory authorities.

Page 28 November Trial Design domains see Section 7 and Relationship datasets see Section 8 already specify the complete variable names. These values should be short for ease of use in programming. No special characters are allowed for compatibility with SAS version 5 transport files. Standard domains see Section 6. Sample Rows from individual study dm. To identify a subject uniquely across all studies for all applications or submissions involving the product. This means that no two or more subjects.

Many sponsors concatenate values for the Study. Exceptions may include long text data such as comment text. Study ACME01 dm. All rights reserved Final Page 29 November As an example.

Cases where multiple domains are necessary to capture data that was collected together and have an implicit relationship. Cases where multiple datasets are necessary to capture data in the same domain.

Adverse Events AE. For the subject 1. Stress Test data collection. Some limited cases where they will have meaning across domains within the same general observation class.

MH and AE. Vital Signs recorded during the stress test VS domain iii. Information about the occurrence. When values are used across domains. Page 30 November Treatments e. In domains based on the Findings general observation class. Groups of medications taken to treat an SAE. When applicable. Differences between Grouping Variables A.

All rights reserved Final Page 31 November TORSO depending on the sponsor's coding practice and analysis requirements. Several options are available for submission of this data: If specific tests are not prespecified on the CRF and the investigator has the option of writing free text for tests. Note that the Disposition dataset DS is an exception to the general rule of splitting multiple topic values into separate records.

Assumption 5 for additional information. For cases of multiple reasons for discontinuation see Section 6. For example: Acetaminophen Aspirin Ibuprofen Naproxen Other: For DS.

By the time of submission. All rights reserved Final Page 33 November The following example includes selected variables from the ae.

It is recommended that the SUPP-. Dependent variables such as result Qualifiers should never be part of the natural key. Some sponsors may elect to keep this variable in a Supplemental Qualifier record. Page 34 November If multiple values exist e. QNAM value reference the corresponding standard domain variable with an appended number or letter. The controlled terminology used should be documented as part of value-level metadata. The values stored in QVAL should be consistent with the controlled terminology associated with the standard variable.

Please check current controlled terminology at this link: Note that a null value should not be included in the permissible value set. Deviations to this rule should be described in the define. All rights reserved Final Page 35 November All values in the permissible value set for the study should be included. This association must be clearly documented in the metadata and annotated CRF. For V3. If the external reference for the controlled terminology is not in upper case then the data should conform to the case prescribed in the external reference e.

Separate code values may be submitted as Supplemental Qualifiers and may be necessary in analysis datasets.

If coding to multiple classes. These may be provided in a Supplemental Qualifiers dataset see Section 8. HLGT or relationships should be stored in the dataset. The sponsor is expected to provide the dictionary name and version used to map the terms by utilizing the define. For an Interventions domain. In most cases other than PE. By knowing the dictionary and version used. For a Findings domain. For an Events domain. In situations such as these. If the verbatim topic variable in an Interventions or Event domain is modified to facilitate coding.

Page 36 November The variables used in each of the defined domains are: For concomitant medications. If a dictionary is multi-axial. ISO represents times as a text string using the notation hh: In the Events or Interventions general observation class this could be the start date of the event or intervention. In general. In the Findings observation class where data are usually collected at multiple visits. All rights reserved Final Page 37 November The ISO basic format.

Every component except year is represented as two digits. Examples of this method of omitted component representation are shown in the table below: ISO represents missing intermediate components through the use of a hyphen where the missing component would normally be represented. Missing components are represented by right truncation or a hyphen for intermediate components that are missing.

According to ISO If the date and time values are completely missing the SDTM date field should be null. Years are represented as four digits.

Note that if no time component is represented. To represent these intervals while applying the ISO standard. As mentioned above. When components are omitted. This may be useful if data are collected in formats such as "one and one-half years".

Both duration and duration units can be provided in the single --DUR variable. All rights reserved Final Page 39 November These variables represent the two instants that bound an interval of time. The use of the character P is based on the historical use of the term "period" for duration. Since most data is collected as part of a visit.

ISO also allows that the "lowest-order components" of duration being represented may be represented in decimal format. The letter "P" must precede other values in the ISO representation of duration. P6W represents 6 weeks of calendar time. ISO allows an interval to be represented in multiple ways.

One representation. Duration is frequently used during a review. This algorithm for determining Study Day is consistent with how people typically describe sequential days relative to a fixed reference point. Study Day is not suited for use in subsequent numerical computations.

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As such. The raw date values should be used rather than Study Day in those calculations. This is the recommended representation of elapsed time. The table below provides some examples of ISOcompliant representations of durations: Page 40 November Remember that this is ONLY allowed in the lowest-order right-most component in any duration representation.

The calculation of additional study days within subdivisions of time in a clinical trial may be based on one or more sponsor-defined reference dates not represented by RFSTDTC.

For domains in the Events or Interventions observations classes. For studies that are designed with a prospectively defined schedule of visit-based activities. For planned visits: For planned visits. The following table shows an example of how the visit identifiers might be used for lab data: All rights reserved Final Page 41 November Page 42 November If the reference time point corresponds to the date of collection or assessment: Note that in this example.

Note also that the information collected is relative to the study treatment period. In many cases. If the reference time point is prior to the date of collection or assessment: Sponsors wishing to do such derivations are instead encouraged to use supplemental variables or analysis datasets for this derived data.

Sponsors should use the set of variables that allows for accurate representation of the collected data. Prior and Concomitant Medications Assumptions: All rights reserved Final Page 43 November Adverse Events Assumptions: Example when both "Prior" and "Continuing" are checked: The medical event may or may not have ended at any time after that.

Prior refers to screening visit and Continuing refers to final study visit. Medical History Assumptions: The interrelationship of these variables is shown in Figure 4. Consider the following cases: The table below illustrates the proper use of these variables.. Note that using a date as a result to a Findings question is unusual and atypical. For any domain based on the Findings general observation class. For timed lab collections e.

In order to ensure that the critical timing information is always represented in the same variable. Note that time-point data will usually have an associated --DTC value. Figure 4. All rights reserved Final Page 45 November For instance.

For trials with many time points. Not all time points will require all three variables to provide uniqueness. For instance: Values for these variables for Urine Collections taken pre-dose.

The fact that time points are related to a reference time point. If the protocol describes the scheduling of a dose using a reference intervention or assessment. In fact. Within the context that defines uniqueness for a time point. In other words. If a new record is derived for a dataset. Sponsors may. An example is included in Section 4. If the QTc Intervals are received from a vendor the derived flag is not populated.

In some cases where the code values in the codelist are statistically meaningful standardized values or scores.

All rights reserved Final Page 47 November For example in ECG data. The rules for modifying the value for analysis purposes should be defined in the analysis plan and only changed in the ADaM datasets. Conventions for populating --ELTM should be consistent the examples just given would probably not both be used in the same trial.

Occasionally data that are intended to be numeric are collected with characters attached that cause the character-to-numeric conversion to fail. When the derived record comes from more than one visit. It would be good practice to indicate the range of intended timings by some convention in the values used to populate --TPT.

The variable. Rows 11 and If a group of tests were not done: Row 6. Certain required and expected variables are omitted. The reason for the missing information may or may not have been collected. Vital Signs. Page 48 November Note that the standard units are populated by sponsor decision. PR interval. Note that the original collected data are not shown in this example. See the examples below for submitting groups of tests not done.

A sponsor has two options. The changes are directed at decreasing the amount of sponsor subjectivity in converting original results to standard results. ECG Examples: IETEST values in IE and TI are exceptions to the above character rule and are limited to characters since they are not expected to be transformed to a column labels.

Sponsors should include the full description for these variables in the study metadata in one of two ways: Note that the Comments domain is not based on a general observation class and has different rules. For further details see IE domain Section 6.

In the define. Because of the current requirement for Version 5 SAS transport file format. All rights reserved Final Y. The records for the original collected results are not shown in this example. See Section 5. Example 1: In this case. For observations that have primary and supplemental evaluations of specific qualifier variables. AEACN with characters. In cases where the standard domain variable name is already eight characters in length.

All rights reserved Final Page 51 November Only the Comments CO and Trial Summary TS domains are allowed to add variables for the purpose of handling text exceeding characters. Within each SUPP-record. Please see section 5. In cases where the standard domain variable name is already 8 characters in length. When splitting a text string into several records. In this dataset. The following is an example of how to represent the case where an adjudication committee evaluates an adverse event in SUPPAE.

For the Interventions and Events observation classes. The adverse event data as determined by the primary investigator would reside in the standard AE dataset. If multiple reasons are reported. It could also have a SUPP-. Since the method of solicitation for information on treatments and terms may affect the frequency at which they are reported. The standard SUPP-. Examples of the latter include the following: It is a permissible variable. For the Findings general observation class.

For the Interventions general observation class.. It is a permissible variable and may be omitted from the dataset if no topic-variable values were pre-specified. As in Findings. If a study collects both pre-specified interventions and events as well as free-text events and interventions. All rights reserved Final Page 53 November The --OCCUR variable is used to indicate whether a pre-specified intervention or event occurred or did not occur.

One record per subject. Char DM Identifier Two-character abbreviation for the domain. Topic Subject identifier. Record Unique identifier for a site within a study.

Demographics — Version 3. This must be a unique number. Required for all randomized subjects. Synonym Name of the investigator for a site. Qualifier Record An identifier to describe the Investigator for the study. September for guidance regarding the collection of ethnicity http: Req Exp Race of the subject. Exp Sex of the subject. Record The ethnicity of the subject. All rights reserved Final Page 55 November Synonym Name of the Arm to which the subject was assigned.

Qualifier Record Country of the investigational site in which the subject participated in the Qualifier trial. Units associated with AGE. September for guidance regarding the collection of race http: Subjects withdrawn from a trial before assignment to an Arm. See ICH E9 for more information and definitions. In some cases a subject may participate in more than one study. When H Page 56 November The Supplemental Qualifiers dataset may be used if appropriate to provide additional information.

Investigator and site identification: Companies use different methods to distinguish sites and investigators. Multiple Responses for a Non-Result Qualifier. Such subjects will not be assigned to one of the planned Arms described in the Trial Arms dataset. This should be done consistently and the meaning of the variable made clear in the define. Subjects occasionally change sites during the course of a clinical trial.

Example Trial 1 in Section 7. Example Trial 3. If multiple races were collected and one was designated as primary. Controlled terms for these subject-level population flags. Sponsors may include a record in the Disposition dataset indicating when the screen failure event occurred.

When study population flags are included in SDTM. This variable is included in the Demographics model in the event that a sponsor intends to submit it.

Qualifier and Timing Variables Only the following Timing variables are permissible and may be added as appropriate: Examples 2 through 5 display various scenarios for representing race and ethnicity information.

Example 1 is a general Demographics example showing typical data recorded for a clinical trial. If a subject refuses to provide race information. They are not considered to be Timing Variables because they are not intended for use in the general observation classes. DM Example 1 — General Demographics dm. Example 1 displays the all Required and Expected variables.

Sponsors should refer to Section 4. Additional Permissible Identifier. Examples are provided below in Section 5.

Pdf sdtm ig 3.1.2

Row 2: Subject was Hispanic and White. Sample CRF: Subject was Not-Hispanic and Asian. Other Race 1 Race 2 Race 3 Race. Multiple Race Choices In this example. Row 2 DM and Rows 2. Row 4 DM: Synonym Qualifiers specify an alternative name for a particular variable in an observation.

Record Qualifiers define additional attributes of the observation record as a whole rather than describing a particular variable within a record. Variable Qualifiers are used to further modify or describe a specific variable within an observation and is only meaningful in the context of the variable they qualify. The Identifier variable is the subject identifier, ''. The Timing variable is the study day of the start of the event, which captures the information, 'starting on Study Day 6', while an example of a Record Qualifier is the severity, the value for which is 'MILD'.

Additional Timing and Qualifier variables could be included to provide the necessary detail to adequately describe an observation. Datasets and domains[ edit ] Observations are normally collected for all subjects in a series of domains. A domain is defined as a collection of logically-related observations with a topic-specific commonality about the subjects in the trial.

The logic of the relationship may relate to the scientific matter of the data, or to its role in the trial. Typically, each domain is represented by a dataset, but it is possible to have information relevant to the same topicality spread among multiple datasets. For the Findings general observation class. Since the method of solicitation for information on treatments and terms may affect the frequency at which they are reported. The standard SUPP-. It is a permissible variable. It is a permissible variable and may be omitted from the dataset if no topic-variable values were pre-specified.

One record per subject, Tabulation Variable Name. Char DM Identifier Two-character abbreviation for the domain. Identifier Identifier used to uniquely identify a subject across all studies for all applications or submissions involving the product. Topic Subject identifier, which must be unique within the study. Required for all randomized subjects; will be null for all subjects who did not meet the milestone the date requires, such as screen failures or unassigned subjects.

Required for all randomized subjects; null for screen failures or unassigned subjects. Record Unique identifier for a study site. Qualifier Record An identifier to describe the Investigator for the study. Synonym Name of the investigator for a site. Age expressed in AGEU. Units associated with AGE. Race of the subject. If multiple race responses are collected and one is designated as the primary race, RACE should hold the primary race. The ethnicity of the subject. Short name for ARM may be up to eight characters.

Req Name of the Arm to which the subject was assigned. Country of the investigational site in which the subject participated in the Req trial. Perm Study day of collection measured as integer days. Investigator and site identification: Companies use different methods to distinguish sites and investigators. This should be done consistently and the meaning of the variable made clear in the Define data definition document.

In some cases a subject may participate in more than one study. To identify a subject uniquely across all studies for all applications or submissions involving the product, a unique identifier USUBJID must be included in all datasets. Subjects occasionally change sites during the course of a clinical trial. The Supplemental Qualifiers dataset may be used if appropriate to provide additional information.

This variable is included in the Demographics model in the event that a sponsor intends to submit it; however, sponsors should follow regulatory guidelines and guidance as appropriate. Some subjects may leave the trial before they can be assigned to an Arm, or, in the case of trials where Arm is assigned by two or more successive allocation processes, may leave before the last of these processes.

Sponsors may include a record in the Disposition dataset indicating when the screen dropout event occurred. Some trial designs include Elements after screening but before Arm assignments are made, and so may have subjects who are not screen failures, but are not assigned to an Arm. Example Trial 1 in Section 7. In trials where Arm assignment is done by means of two or more allocation processes at separate points in time, subjects who drop out after the first allocation process but before the last allocation process, should be assigned values of ARMCD that reflect only the allocation processes they underwent.

Example Trial 3, Section 7. Sponsors are expected to include appropriate study population flags as Supplemental Qualifiers see Section 8. See ICH E9 for more information and definitions. Additional data collected about the data represented in the Demography domain e. Other characteristics describing the subject may be reported in another domain such as Subject Characteristics see Section 6.

Submission of multiple race responses should be represented in the Demographics domain and Supplemental Qualifiers dataset as described in assumption 4. Examples are provided below in Section 5.

They are not considered to be Timing Variables as described in Section 2. Additional Permissible Identifier, Qualifier and Timing Variables The following Timing variables are permissible and may be added as appropriate: Examples of using the DM domain for typical scenarios are provided below.

Certain Required or Expected variables may be omitted in these examples due to space considerations. Example 1 is a general Demographics example showing typical data recorded for a clinical trial. Examples 2 through 5 display various scenarios for representing race and ethnicity information. DM Example 1 — General Demographics dm. Sample CRF: Row 1 - Subject was Non-Hispanic and Asian.

Row 2 - Subject was Hispanic and White. The specified information describing other race for is submitted in the same manner as subject Row 3 DM Subject did not provide information on race. Row 2 DM and Rows 2. Multiple Race Choices In this example. Other Race 1 Race 2 Race 3 Race. Sponsors may choose not to map race data.

Also read: MAGIC HOUR PDF

Mapping Predefined Races In this example. Row 2 DM. Sample CRF and Data: In this example. Row 1: Subject was randomized to Arm A.

Row 4: Subject withdrew during the Run-in Element. The sponsor is submitting data on screenfailure subjects. They were not considered a screen failure. Row 2: Subject was randomized to Arm B. Row 3: Subject was a screen failure. All rights reserved Draft Page 67 July Row 7 of SE dataset shows that they passed through only the Screen Element.

At the end of the Double Blind Treatment Epoch. They were lost to follow-up during the Double Blind Epoch. Subject was randomized to Drug A. See Section 7. Note that A is not one of the Arm code values in the Trial Arms dataset for this trial.

See assumption 5. Record Identifying variable in the parent dataset that identifies the record s to which the Qualifier comment applies. Comments —Version 3. Timing Trial Epoch of the Exposure record. Topic The text of the comment.

Protocol-defined description of clinical encounter. Used only when individual Qualifier comments are related to domain records. Should be null if this is a child record of another domain or if comment date was not collected. Record Sponsor-defined reference associated with the comment. All rights reserved Draft Page 69 July Null for comments collected on a Qualifier general comments or additional information CRF page.

Record Used to describe the originator of the comment. References SDTM 2. Identifier Sequence Number given to ensure uniqueness of subject records within a domain. May be the CRF page Qualifier number e. Clinical encounter number.

SDTM V1.2 & SDTM IG V3.1.2

May be any valid number. July Record Domain abbreviation of the parent record s. Used only when individual comments are related to domain records.

Null for comments collected on separate CRFs. Timing 1. Record Value of identifying variable of the parent record s. One record per comment per subject. Those related to a specific parent record or group of parent records. See example. Rows Rows 1.

Rows 1 and 5. The CO dataset accommodates three sources of comments: Comments are generally not responses to specific questions. CODTC should be populated if captured. When the comment text is longer than characters.

Row 2. Page 70 July The Comments special-purpose domain provides a solution for submitting free-text comments related to data in one or more SDTM domains as described in Section 8.

The following Identifier and Timing variables are permissible and may be added as appropriate when comments are not related to other domain records: CODTC should be null because the timing of the parent record s is inherited by the comment record.

Those unrelated to a specific domain or parent record s. Those related to a domain but not to specific parent record s. EX and VS domains. Synonym The name of the Element. Subject Elements — Version 3. Actual Elements and Visits data for each subject are described in two additional datasets: Trial Arms. One record per actual Element per subject. Should be assigned to be consistent chronological order. If an encountered Element differs from the planned Element to the point that it is considered a new Element.

Char SE Identifier Two-character abbreviation for the domain. Synonym Description of what happened to the subject during this unplanned Element. Topic 1. All rights reserved Draft Page 73 July For instance. If a subject actually received a dose of 7 mg when they were scheduled to receive 5 mg.

If the sponsor decides that the subject's experience for a particular period of time cannot be represented with one of the planned Elements. We assume that if it is known that a subject passed through a particular Element. The purpose of the dataset is to record the Elements a subject actually passed through.

The rationale for this decision should be documented in the Comments column of the Define data definition document. For subjects who follow the planned sequence of Elements for the Arm to which they were assigned.

The Subject Elements domain allows the submission of data on the timing of the trial Elements a subject actually passed through in their participation in the trial.

If the subject actually started the next treatment Epoch see Section 7. Judgment may be needed to match actual events in a subject's experience with the definitions of transition events the events that mark the starts of new Elements in the Trial Elements table. For any particular subject.

Judgment will also have to be used in deciding how to represent a subject's experience if an Element does not proceed or end as planned. The sponsor's methods for such decisions should be documented in the define document.

Please read Section 7. If a subject was assigned to receive the sequence of Elements A. SESEQ should be assigned to be consistent with the chronological order. The sponsor will have to decide what value. Drug B was assigned to receive Drug A. This should not be confused with the actual order of the Elements. Note that the requirement that SESEQ be consistent with chronological order is more stringent than in most other domains.

Since there are. Only the date. The record for the IV Element for subject Subject was treated incorrectly. Example 1 This example shows data for two subjects for a crossover trial with four Epochs. Subject completed the trial. Subject completed only two Elements of the trial. The double-blind treatment Epoch starts with the start of dosing. When sponsors choose to collect only dates.

Note that. This has been represented by treating the period when the subject received the wrong drug as an unplanned Element. One record per subject per actual visit. Char SV Identifier Two-character abbreviation for the domain. Perm Num Timing Actual study day of end of Visit. Decimal numbering may be useful for inserting unplanned visits. Subject Visits — Version 3. Qualifier 2. Synonym 1. For unplanned visits. For many studies.. When data are collected outside a planned visit.

It should not be populated for unplanned visits. The sponsor's rules for making such decisions should be documented in the define document. Records for unplanned visits should be included in the SV dataset. If the occasion is considered a visit. The identification of an actual visit with a planned visit sometimes calls for judgment.

Differentiating between planned and unplanned visits may be challenging if unplanned assessments e. Note that it is fairly common for screening data to be collected over several days. The Subject Visits domain allows the submission of data on the timing of the trial visits a subject actually passed through in their participation in the trial.

Algorithms for populating SVSTDTC and SVENDTC from the dates of assessments performed at a visit may be particularly challenging for screening visits since baseline values collected at a screening visit are sometimes historical data from tests performed before the subject started screening for the trial. Some judgment may be required to determine what constitutes an unplanned visit.

All rights reserved Draft Page 77 July Row 5 shows an unscheduled visit. Row 6 shows that this subject had their last visit. Row 3 shows that the visit scheduled for Day 8 occurred one day early. Row 1 shows that data for the screening visit was actually gathered over the course of five days. Topic Verbatim medication name that is either pre-printed or collected on a CRF. Char CM Identifier Two-character abbreviation for the domain.

One record per recorded intervention occurrence or constant-dosing interval per subject. Identifier Used to tie together a block of related records in a single domain for a subject. Identifier Sponsor-defined reference number. All rights reserved Draft Char Char Identifier Identifier used to uniquely identify a subject across all studies for all applications or submissions involving the product.

Codelist or Format Char Identifier Unique identifier for a study. Concomitant Medications — Interventions. Qualifier single class. Char NY Record When the use of specific medications is solicited. When coding to a single class. If using a dictionary and coding to multiple classes. Equivalent to the generic medication name in WHO Drug. Qualifier answered.

Q12H every 12 hours. BID twice daily. Identifies the start of the medication with respect to the sponsor-defined Perm reference period. Total dose over a period other than day could be recorded in a separate Supplemental Qualifier variable.

It is a required variable and must have a value. The structure of the CM domain is one record per medication intervention episode. This definition may vary based on the sponsor's requirements for review and analysis. Concomitant Medications Description and Coding a. The metadata will specify which dictionary is applied to each category. If a sponsor chooses to use more than one dictionary to code different types of data within the same dataset e.

Since the solicitation of information on specific concomitant medications may affect the frequency at which they are reported. Presence or Absence of Concomitant Medications a. A value of Y indicates that the medication was used and N indicates that it was not.

Information on concomitant medications is generally collected in two different ways. One common approach is to submit a new record when there is a change in the dosing regimen. If data in the CM domain were coded using multiple versions of a dictionary.

Other approaches may also be reasonable as long as they meet the sponsor's evaluation requirements. The submission dataset structure may differ from the structure used for collection. Another approach is to collapse all records for a medication to a summary level with either a dose range or the highest dose level. CMPRESP is a permissible variable and should only be used when the medications were collected using a pre-specified list. It is the sponsor's responsibility to define an intervention episode.

The sponsor is expected to provide the dictionary name and version used to map the terms in the metadata using the Comments column in the Define document. All rights reserved Draft Page 83 July This approach assumes that knowing exactly when aspirin was used is not important for evaluating safety and efficacy in this study Row 1 2 3 4 5 6 7 8 9 10 Page 84 July The example below shows three subjects who took the same medication on the same day.

Spontaneous concomitant medications with dosing information Sponsors collect the timing of concomitant medication use with varying specificity. The frequency is also included for the other daily records to avoid confusion.

It is often unnecessary to record every unique instance of medication use. The subject has used the same medication for many years and continues to do so. Any additional qualifiers from the Interventions Class may be added to this domain. If appropriate. Row 10 are collapsed this is shown as an example only. Additional Permissible Interventions Qualifiers a.

The example below is for a study that has a particular interest in the antidepressant medications that subjects use. The medication history. The medication details e. Spontaneous concomitant medications without dosing information The example below is for a study that has a particular interest in whether subjects use any anticonvulsant medications. Exposure — Interventions. BIW twice a week. Perm Qualifier Example: One record per constant dosing interval per subject.

Exp Qualifier Record Dosing amounts or a range of dosing information collected in text form. Grouping Used to define a category of related records. Identifier Used to tie together a block of related records in a single domain for a Perm subject. Q4W once every four weeks. Grouping A further categorization of treatment. Identifier Sequence Number given to ensure uniqueness of subject records within a Req domain.

Line number on a CRF Page. Total dose over a Perm Qualifier period other than day could be recorded in a separate Supplemental Qualifier variable. Char EX Identifier Two-character abbreviation for the domain. Topic Name of the intervention treatment — usually the verbatim name of the Req investigational treatment given during the dosing period for the observation. Describes vehicle used for treatment.

Number that gives the order of the Element within the Arm. May be used for variations from protocol-specified doses. Previous Dose.. Text Description of time when a dose should be given. Represented as an ISO duration. Examples include but are not limited to placebo. Not a clock time. Study treatment may be any intervention that is prospectively defined as a test material within a study. Exposure Treatment Description a.

EXTRT should only include the treatment name and should not include dosage.

Perm 2. This domain should contain one record per constant dosing interval per subject. Or if the sponsor monitors each treatment administration and deviations in treatment or dose occur. Categorization and Grouping a. Start or 5 min post. EXTRT captures the name of the investigational treatment and it is the topic variable. Page 88 July Treatments that are not protocol-specified should be recorded in the Concomitant Medication CM domain.

Additional Interventions Qualifiers a. With respect to timing of doses. However if the beginning and end of a constant dosing interval is not confined within the time limits of a clinical encounter e. Note below that Subject missed taking study medications on Study Days 23 and If the subject is only exposed to study medication within a clinical encounter e.

This is an example of an Exposure dataset for a parallel-design study. Drug A 20 mg QD.. Drug A 40 mg QD.. The study included 8 weeks of treatment. Timing Variables a. This is because EX is designed to capture the timing of exposure to treatment.

The SDTM does not have any provision for recording "start visit" and "end visit. Drug C was assigned as supplemental therapy for both groups. There was a 6-day washout period between treatments. This is an example of an Exposure dataset for a single crossover study comparing once daily oral administration of Drug A 20 mg capsules with Drug B 30 mg coated tablets.

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Study drug was taken for 3 consecutive mornings 30 minutes prior to a standardized breakfast. Dose adjustments were allowed as needed in response to tolerability or efficacy issues. Study drug was taken daily for three months. All rights reserved Draft Page 91 July This is an example of an Exposure dataset for an open-label study examining the tolerability of different doses of Drug A.

This is an example of a titration Exposure dataset for a study that gradually increases dosage while simultaneously evaluating efficacy and toleration of the treatment regimen. The schedule specifies that Drug A be administered twice daily starting with mg for 3 days. The sponsor should specify the dictionary name and version in the Sponsor Comments column of the Define document. Values are null for substances not specifically solicited. Substance Use — Interventions. Grouping A further categorization of substance use.

Topic Substance name. One record per substance type per reported occurrence per subject. Identifier Two-character abbreviation for the domain.

Describes the reason substance use was not collected. If sponsor needs to aggregate the data over a period other than day. Collected duration of substance use in ISO format. When there is no pre-specified list on the CRF. All rights reserved Draft Page 95 July Identifies the end of the substance use with respect to the sponsor-defined Perm reference period.

In many clinical trials. Page 96 July This information may be independent of planned study evaluations.

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Where deemed necessary by the sponsor. SUTRT is a required variable and must have a value. This categorization might differ from the categorization derived from the coding dictionary. SU may contain responses to questions about use of pre-specified substances as well as records of substance use collected as free text. That is. It is the topic variable for the SU dataset. Additional Categorization and Grouping a.

SU Definition. SUTRT captures the verbatim or the pre-specified text collected for the substance. Substance Use Description and Coding a. Row 6: Subject has missing data for the smoking questions.

Not shown: Subject has never smoked. The same subject drank tea Row 4 and coffee Row 5 on the day of the assessment. Row 7: The same subject also had missing data for all of the caffeine questions. The subject did not drink any caffeinated drinks on the day of the assessment so does not have any caffeine records. All rights reserved Draft Page 97 July The same subject drank three cups of coffee on the day of the assessment. The date the subject began smoking is unknown but we know that it was sometime before the assessment date.

Therefore this subject does not appear in the data. Both the beginning and ending reference time points for this question are the date of the assessment.