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This section illustrates example analysis datasets for the following endpoints:

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This section illustrates example analysis datasets for the following endpoints:

• Percent change in ejection fraction over time
• Decline in ejection fraction over a time period (1 year) grouped by a decline greater than 10.0%
• Percent change in NTproBNP over a period of 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 CV dataset contains 16 rows, 1-8 for visit 1 and 9-16 for visit 6. Of these rows, the CVTESTCD = "LVEF_C" and CVTESTCD = "RVEF_C" representing the Ventricular Ejection Fraction, Calculated (%) for left and right were selected for the analysis. The LB dataset test where LBTESTCD = "BNPPRONT" was 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 data.

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.

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

Source Data

The SDTM examples used as the source data are from Section 2.1, Basic CMR Tests for Systolic Function. The CV dataset contains 16 rows, 1-8 for visit 1 and 9-16 for visit 6. Of these rows, the CVTESTCD = "LVEF_C" and CVTESTCD = "RVEF_C" representing the Ventricular Ejection Fraction, Calculated (%) for left and right were selected for the analysis. The LB dataset test where LBTESTCD = "BNPPRONT" was 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 data.

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.

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. 

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Ejection Fraction

• change in ejection fraction, would expect a decline in EF 2-3% per year, would prefer an improvement or no change. Concerning if rapid progression, 10% decline or more, for example.

NTproBNP

• % change over a period of time – a decrease would mean improvement, annually is appropriate

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