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The Analysis dataset (ADaM) is created from the collected data stored in SDTM. It should have full traceability back to the input datasets. For this example we show This example illustrates example analysis datasets for the following endpoints:

• From CV domain
  • Percent change in ejection fraction over time
  • Decline in ejection fraction over a time period (yearly) grouped by a decline greater than 10.0%.
• From the LB domain
  • Percent change in NTproBNP over a period of time (yearly).

The SDTM example datasets from which this data is drawn are in the section "examples used as the source data are from Section 2.1, Basic CMR tests - Systolic Function" (make link). The example datasets show visits 1 and 6 for one subject. As mentioned in the SDTM text, for the purposes of this example, the participant was The subject was enrolled in the study on 20-May-2021 and the study visits were every two months. Visit 1 represents the visit at day 1 of the study, and visit 6 represents the visit at month 12 of the study. The associated laboratory test, N-Terminal ProB-type Natriuretic Peptide, is used in conjunction with ejection fraction as a biomarker and is important for diagnosis and treatment. It is also used separately to identify the percent change over a period of time.

The example analysis dataset includes treatment and demographic information drawn from the ADSL, defined in the Metadata Table below. In this example, we only show some of the required variables, plus important stratification variables from ADSL, are shown. One variable mentioned body surface area (BSA), can be computed and added to ADSL. However, since the subjects are children, their body surface area changes over time. Therefore, it would probably be better to have a separate dataset to capture this over time.

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Analysis Datasets

The table below presents shows the sample example analysis datasets and unique parameters generated for this example. The Subject Level Analysis Dataset (ADSL)  is a necessary component in the creation process of subsequent analysis datasets for human trials. The ADSL incorporates demographics, treatment groups, study dates, and stratification variables. In this example, the ADSL is not displayed directly illustrated, but serves as a source for standard ADaM variables. Additional information on this can be found in Section 2.3.1 of the ADaM Implementation Guide (ADaMIG) v1.3.

The second and third datasets follow the naming convention for ADaM by starting with the letters 'AD' representing 'Analysis Dataset'. There is flexibility in the use of the other 6 letters allowed in the dataset name, and also the Dataset description which is also the label. In this example, the ADCVEF dataset selectively captures tests pertinent ADCVEF dataset includes tests pertinent to this analysis, specifically those with for which CVTESTCD is equal to "LVEF_C" or "RVEF_C". The relationship dataset RELREC illustrates the connections between datasets. There exists a many-to-one relationship between cardiovascular tests (CV) and laboratory data collected during the same visitsrelationship between datasets. 

The ADCVNTRP dataset is a subset of LB selecting for LBTESTCD the Laboratory Results (LB) SDTM dataset, for which LBTESTCD is equal to "BNPPRONT". In this case, many lab draws may occur throughout the year, but we are only interested in the ones only those linked to a specific visit are included. By subsetting the Laboratory Results ( LB ) dataset with LBLNKID not missing, we can select laboratory data that aligns with CV data can be filtered out and sort sorted using USUBJID and VISIT. If LBLNKID were is not available, a windowing strategy could be employed used to select the laboratory draw closest to that visit for merging with CV, computed in AVISIT.

ADCMRI 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 a an ADaM Basic Data Structure (BDS) dataset, with additional variables added from ADCVEF.

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Analysis Datasets

The subsequent section provides the data structures for the example ADaM datasets. In this example, columns for derived variables BASE, and CHG, PCHG and CHGCAT1 have been added f to facilitate analyses of the efficacy endpoints. Specifically, example demographic data for ADSL were created for an 8 year old male child. Also, a custom variable for BSA at baseline (BSABASE), an example of a custom variable, was added from ADSL.The ADaM standard only suggests variable order, so the demographics and treatment variables are shown at the right of the dataset.

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The variables transposed and merged to the rows created from CV are:

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This table may be included in the submission package for regulatory agencies. It describes the analyses conducted for the study (usually limited to primary and secondary  endpoints) with details on data and analysis procedures used. The first example uses the dataset ADCVNTPR, selecting for the parameter "N-Terminal ProB-type Natriuretic Peptide (IU/L)" .

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