...
Ejection Fraction
- change in ejection fraction, would expect a decline in EF of 2-3% per year, concerning if rapid progression, i.e., 10% decline or more
NTproBNP
- % change over a period of time – a decrease is correlated with improvement, measured annually
...
Measuring LVEF regularly can show the rate of decline in left ventricle function for a patient with DMD. Therefore, it was selected as an endpoint for this example to measure whether a course of therapy may slow the progression of heart failure for the patient. The second endpoint chosen, NT-proBNP, is a biomarker that may be used to predict or diagnose heart failure.
This section illustrates example analysis datasets for the following endpoints:
- Percent change in ejection fraction over time (1 year)
- Decline in ejection fraction over a time period (1 year) grouped by a decline greater than 10-5.0%
- Percent change in NTproBNP over a period of time NT-proBNP over time (1 year)
Source Data
The SDTM examples used as the source data are from Section 2.1, Basic CMR Tests for Systolic Function. The records in the CV dataset contains 16 rows, 1-8 for visit 1 and 9-16 for visit 6. Of these rows, the for which CVTESTCD = "LVEF_C" and CVTESTCD = "RVEF_C" representing the Ventricular Ejection Fraction, Calculated (%) for left and right were selected for the analysis. The records in the LB dataset test where LBTESTCD = "BNPPRONT" was were used to add the value of BNPPRONT to compute the percent change over time , and then it was added as a potential covariate in each row for the last analysis. As in all ADaM datasets, the Subject Level Analysis Dataset (ADSL) was merged in to the SDTM datasets to capture all the necessary demographics, treatments and other required variables for analysis of the dataand as a potential covariate. Both SDTM domains are used in one analysis dataset to demonstrate the flexibility of ADaM and to show that the various SDTM domains can be combined into one dataset both as rows and also as covariates.
Example Analysis Datasets
The analysis datasets for this example include treatment and demographic information drawn from the Subject Level Analysis Dataset (ADSL), defined in the Metadata Tables below. Only some of the required variables from ADSL are shown for illustrative purposes. The ADSL incorporates demographics, treatment groups, study dates, and stratification variables. Additional information on the ADSL can be found in Section 2.3.1 of the ADaM Implementation Guide (ADaMIG) v1.3.following tables show the analysis dataset metadata and parameters used for this example.
-
Definexmltable | ||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||||||||||||||||||
|
ADSL
The ADSL contains subject characteristics and covariates that are important for analyses. Stratification The ADSL is combined with other SDTM dataset to create the analysis datasets. More than one SDTM dataset can be combined in this way. Also, stratification variables can be created in the ADSL to subset by, or to add variables needed in the analyses. For instance, stratification variable might be type of concomitant medications, such as an ACE inhibitors. for this we added a flag ACEMEDFL, which is coded Y or N. Another variable added; body surface area (BSABL), is derived from the LB dataset at the baseline visit and added to ADSL. However, when the subjects are children, the body surface area changes over time. Therefore, an additional non-standard variable is added to the analysis dataset with the subject's current BSA by visit. the data. More than one SDTM dataset may be used as input to the ADSL. This is a simplified example ADSL dataset; the ADaMIG should be referenced for additional variables.
For this example:
- Analysis age (AAGE) was included to provide age with more precision.
- A flag indicating the use of ACE inhibitors (ACEINHFL) is shown with example derivation from the CM dataset.
- Body surface area at screening (BSASC) was derived from the VS dataset using height and weight at the screening visit. There are many possible calculations for BSA; for this example, the Du Bois method was used.[11] Note that the screening visit and visit 1 occurred at the same time in this example.
Definexmltable | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Dataset wrap | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
ADEFNTP
The ADEFNTP includes tests pertinent to analyses. The records from CV (CVTESTCD = "LVEF_C" and "RVEF_C") and the records from LB (LBTESTCD = "BNPPRONT") were selected. Many The ADCVNTP dataset includes tests pertinent to these analyses. The record LB are selected where CVTESTCD is equal to "LVEF_C" or "RVEF_C". It also includes a subset of the Laboratory Results (LB) SDTM dataset, for which LBTESTCD is equal to "BNPPRONT". The relationship dataset RELREC illustrates the relationship between datasets. In this case, many lab draws may occur throughout the year, but only those linked to a specific visit are were included. By subsetting the LB dataset with by LBLNKID not missing, laboratory data that aligns with CV data can be filtered out and sorted using USUBJID and VISIT. If LBLNKID is not available, a windowing strategy could be used to select the laboratory draw closest to that visit for merging with CV, computed in AVISIT. In the example, only two LB records are shown which are linked to CV where CVTESTCD = "LVEF_C" or CVTESTCD = "R.VEF_C"
ADCVMR is an efficacy analysis dataset with only a few records for more complex modeling of changes in ejection fraction, plus the ProB-type test results. It is an ADaM Basic Data Structure (BDS) dataset, with additional variables added from ADCVNTP.
The tableS below showsthe example analysis dataset metadata and parameters used for the analysis.
...
Multiple | true |
---|---|
Level | Dataset |
Purpose | Analysis |
...
Dataset Name
...
Dataset Description
...
Structure
...
Location
...
Keys
...
ADSL
...
Subject-Level Analysis Dataset
...
One record per subject
...
BASIC DATA STRUCTURE
...
Analysis Dataset
...
BASIC DATA STRUCTURE
...
Analysis Dataset
ADSL Analysis Dataset
This is a simplified example ADSL dataset; it is expected that additional variables for stratification or of interest for analysis would be included.
...
Dataset | ADSL |
---|---|
Level | Variable |
Purpose | Analysis |
Name | Variable |
...
DM.STUDYID
...
DM.USUBJID
...
ADSL.BRTHDTC
...
Planned Treatment for Period 01
...
ITTFL
...
Intent-To-Treat Population Flag
...
Char
...
Y; N
...
ADSL.ITTFL
...
Set to VS.VSSTRESN in ADSL where VS.VSTESTCD = "BSA" and select for baseline visit.
out and sorted using USUBJID and VISIT. If LBLNKID is not available or the LB dataset does not contain VISIT, a windowing strategy could be used to select the laboratory draw closest to that visit using date of lab draw (LB.LBDTC.).
Jira | ||||||||
---|---|---|---|---|---|---|---|---|
|
Definexmltable | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
In this example, variables BASE, CHG, PCHG, and CHGCAT1 were added to facilitate analyses of the efficacy endpoints. the variables SRCDOM, SRCVAR, and SRCSEQ provide traceability to the combined source datasets. The tables below represent parameter value level lists for applicable variables.
Definexmltable | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||
|
Definexmltable | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||
|
Definexmltable | ||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||||
|
In this table the ADaM parameters are used rather than the source SDTM data.
Definexmltable | ||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||||||||||||||||||||||||||||||||||
|
Dataset wrap | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
ADEFMRI
The ADEFMRI is an efficacy analysis dataset with only a few records for more complex modeling of changes in ejection fraction, plus the proB-type test results. It is an ADaM Basic Data Structure (BDS) dataset
, with additional variables added from ADEFNTP dataset. Jira showSummary false server Issue Tracker (JIRA) serverId 85506ce4-3cb3-3d91-85ee-f633aaaf4a45 key TAUGDMDCIS-15
The dataset can can be used for analyses with multiple covariates
Jira | ||||||||
---|---|---|---|---|---|---|---|---|
|
Definexmltable | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Dataset wrap | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
...
ACEINHFL
...
ACE Inhibitor Medications Flag
...
Char
...
Y
...
Select a list of ACE inhibitor medications from concomitant medications (CM) domain, and from treatment (EX or EC) domains. Code "Y" if the medication was taken during the study. Can be used to subset or to exclude the population who took ACE inhibitors.
...
Show | true |
---|---|
Name | ADSl |
...
tableid | adcvcmr |
---|
...
Dataset | ADCVNTP |
---|---|
Level | Value |
Purpose | Analysis |
OID | AVAL |
...
Analysis Datasets for Ejection Fraction
The subsequent section provides the data structures for the example ADaM datasets. In this example, columns for derived variables BASE, CHG, PCHG and CHGCAT1 have been added to facilitate analyses of the efficacy endpoints. Specifically, example demographic data for ADSL were created for an 8 year old male. Also, a custom variable for BSA at baseline (BSABASE), and an example of a stratification variable for subjects with was added from ADSL.
...
Dataset | ADCVNTP |
---|---|
Level | Variable |
Purpose | Analysis |
Name | Variable |
...
CV.STUDYID
...
CV.USUBJID
...
CV.CVSEQ
...
ADSL.BRTHDTC
...
Planned Treatment for Period 01
...
ITTFL
...
Intent-To-Treat Population Flag
...
Char
...
Y; N
...
ADSL.ITTFL
...
ACEINHFL
...
ACE Inhibitor Medications Flag
...
Char
...
Y
...
Select a list of ACE inhibitor medications from concomitant medications (CM) domain, and from treatment (EX or EC) domains. Code "Y" if the medication was taken during the study. Can be used to subset or to exclude the population who took ACE inhibitors.
...
Compute from VS.HEIGHT and VS.WEIGHT by visit, using the Du Bois method. Note that there are multiple methods to compute, and the study protocol should describe which one to use. (e.g. other methods may be Mosteller, Haycock, Gehan & George, Boyd, Fujimoto, Takahira, and Schlich)
...
Left Ventricular Ejection Fraction, Calculated (%);
Right Ventricular Ejection Fraction, Calculated (%);
N-Terminal ProB-type Natriuretic Peptide (pg/mL)
...
For tests from CV, set to the values of CV.CVTEST plus CV.CVTESTU with spaces and parentheses as shown.
For tests from LB, set to the value of LB.LBTEST plus LB.LBTESTU with spaces and parentheses as shown.
...
LVEFC;
RVEFC;
BNPPRONT
...
If CV.CVTESTCD = "LVEF_C" then PARAMCD = "LVEFC"
If CV.CVTESTCD = "RVEF_C" then PARAMCD = "RVEFC"
If LB.LBTESTDC = "BNPPRONT" then PARAMCD = "BNPPRONT
Note: for this example dataset, select the records where the test values shown above are included.
...
Number PARAMCD as follows:
LVEFC = "1"
RVEFC = "2"
BNPPRONT = "3"
...
See Parameter Value List
...
If CV.VISIT = "VISIT 1" then AVISIT = "Visit 1 (Baseline)".
Else if CV.VISIT = "VISIT 6" then AVISIT = "Visit 6 (1 Year)".
...
CV.VISIT
LB.VISIT
...
If CV.VISIT = 1 then ABLFL = "Y".
...
Set BASE to AVAL from the record for that subject and parameter where ABLFL = "Y".
Populate BASE for additional visits by carrying forward the value of BASE in the baseline record by USUBJID and AVISIT.
...
Decline >=10.0;
Decline < 10.0;
Increase
...
CV; LB
...
CV.CVSEQ
LB.LBSEQ
...
Example 1
This example dataset shows the findings and additional analysis variables associated with:
- Left Ventricular Ejection Fraction, Calculated (%)
- Right Ventricular Ejection Fraction, Calculated (%)
- N-Terminal ProB-type Natriuretic Peptide (pg/mL)
...
Name | adcvntp |
---|
...
tableid | adcvntp |
---|
...
Example 2
The dataset above can also be set up to provide multivariate analyses by taking the lab tests of interest, transposing and merging with the ADCVNTP dataset. In that case, the records from LB are not needed as a row.
...
Name | adcvcmr |
---|
...
tableid | adcvcmr |
---|
...
Example Analysis Results Metadata (ARM) Tables
For more details on ARM, see the ADaMIG and the Analysis Results Metadata (ARM) v1.0 for Define-XML v2.0 (https://www.cdisc.org/standards/foundational/adam).
Table 1
...
Display
...
Table 14.xx.xx Percent Change in Left Ventricular Ejection Fraction Over Time
...
Data References
(incl. selection criteria)
...
PARAMCD = "LVEFC"
Where ITTFL = "Y"
...
The mixed model using lsmeans to compare treatment groups
...
Programming Statements
(Add programming language statements here: SAS, R, etc.)
...
PROC MIXED DATA=ADCVCMR;
CLASS STUYDID TRT01P AVISITN;
MODEL PCHG=AVISITN*TRT01P/Solution;
RANDOM INTERCEPT / SUBJECT=STUYDID TYPE=UN;
LSMEANS TRT01P*AVISITN/ CL PDIFF;
RUN;
Table 2, ADD SOME COVARIATES TO THE MODEL
...
Display
...
Table 14.xx.xx Percent Change in Left Ventricular Ejection Fraction Over Time
...
Data References
(incl. selection criteria)
...
PARAMCD = "LVEFC"
Where ITTFL = "Y"
...
The mixed model using lsmeans to compare treatment groups
...
Programming Statements
(Add programming language statements here: SAS, R, etc.)
...
PROC MIXED DATA=ADCVNTP;
CLASS STUYDID TRT01P AVISITN;
MODEL PCHG=AVISITN*TRT01P/Solution;
RANDOM INTERCEPT / SUBJECT=STUYDID TYPE=UN;
LSMEANS TRT01P*AVISITN/ CL PDIFF;
RUN;
Move to table 3 This example uses the dataset ADCVNTP, selecting for the parameter "N-Terminal ProB-type Natriuretic Peptide (IU/L)".
...
Display
...
Table 14.xx.xx Percent change in NTproBNP over a period of time (yearly)
...
Data References
(incl. selection criteria)
...
PARAMCD = "BNPPRONT"
Where ITTFL = "Y"
...
The mixed model using lsmeans to compare treatment groups
...
Programming Statements
(Add programming language statements here: SAS, R, etc.)
PROC MIXED DATA=ADCVNTP;
WHERE PARAMCD = "BNPPRONT";
CLASS STUYDID TRT01P AVISITN;
MODEL PCHG=AVISITN*TRT01P/Solution;
RANDOM INTERCEPT / SUBJECT=STUYDID TYPE=UN;
LSMEANS TRT01P*AVISITN/ CL PDIFF;
...
Pagenav2