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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 the following endpoints:

  • From CV domain
    • Percent change in ejection fraction
    • Decline in ejection fraction over a time period (yearly) grouped by a decline greater than x.x%.
  • 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 "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 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 analysis dataset  includes treatment and demographic information drawn from the ADSL. In this example, we only show some of the required variables plus important stratification variables from ADSL. 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. In this example, we will show one variable for BSA with the variable "Baseline Body Surface Area (m2)" which can be added to ADSL.


Questions. 

Is screening considered visit 1, or is it to include the subject into the study? SDTM team agreed to change to VISIT 1 instead of SCREENING.

Are these Real World Evidence (RWE) studies only or clinical trials?

Should both endpoints be shown in one efficacy dataset or two?  I will be showing 3 datasets.

What is a good surface area to use for the child subject?

Should i use Male and 6 years? please advise.

Analysis Datasets

Below is the table of analysis datasets and unique parameters created for the example. The ADSL is required as part of the process of creating the subsequent analysis datasets.

The ADSL includes demographics, treatment groups, study dates and stratification variables. For this example, the ADSL is not shown other than as a source for standard ADaM variables. See Section 2.3.1 of the ADaMIG v1.3 for additional information.

ADCVEF is a dataset capturing only the tests required for this analysis, selecting for CVTESTCD equal to "LVEF_C" or "RVEF_C".  The relationship dataset RELREC shows the datset relationships. There is a many to one relationship between the tests from CV and the laboratory data collected at the same visits. Therefore by subsetting the LB with LBLNKID not missing, this selects the laboratory data that can be merged with CV by USUBJID and VISIT  (or USUBJID and AVISIT in ADaM)  In ADaM analysis datasets we can also use a windowing strategy to select the laboratory draw closest to that visit to merge with CV which is computed in AVISIT in which case all LB records would be kept for the tests of interest.

ADLBNTRP is a subset of LB selecting for LBTESTCD  equal to "BNPPRONT", and LBLINKID not missing. In this case, many lab draws may occur throughout the year, but we are only interested in the ones linked to a specific visit.

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 Basic Structure dataset with additional variables added from ADCVEF.

Analysis Datasets

Parameter Value List - ADCEF, ADLBNTRP

Analysis Datasets

The following are the data structures for the example ADaM dataset. Note that the columns for derived variables, BASE, and CHG, PCHG and CHGCAT1 have been added for the efficacy analysis of endpoints. The example demographics for ADSL were created for a xx year old male child.









ADCV Variable Metadata



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

SDTM Examples: Basic CMR tests - Systolic Function



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