yamaa / Benchmark

ADaM.ADAE

Carry Subject-Level Variables onto Adverse Events by Name

input files
2
subjects
3
expected rows
6
Review ask

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Summary

Lifecycle: draftEditUnder reviewWhat this benchmark means
README.md

Public entries: Python and R. Passing coverage requires an installed inventory.

Goal: give every adverse event record its subject's age (AGE), sex (SEX), planned arm (ARM) and date of first exposure to treatment (TRTSDT) from the subject-level analysis dataset (ADSL), each under the name, type and label ADSL gives it.

Input: two spec files, run in order:

  • spec_adsl.yaml builds ADSL from collected demographics, one record per subject with the first exposure date as text, and saves it as adsl.csv;
  • spec_adae.yaml is the entry: it reads adverse event records carrying the reported term (AETERM) and the saved adsl.csv, and names the four variables to take from it without declaring them again.

Variables:

  • AGE, SEX and ARM are the subject's age in years, sex and planned arm, repeated on each of the subject's events;
  • TRTSDT is the date of the subject's first exposure to treatment, still a date on the events; it stays empty for a subject never exposed, such as a screen failure.

Note: a variable taken by name from ADSL keeps everything the spec that builds ADSL declares for it, so the two datasets cannot disagree on its type or label. Each event finds its subject's one ADSL record by the study and subject identifiers; a subject without adverse events adds no event record.

Inputs

Under review2 source files

input/ae.csv

Edit3 rows
STUDYIDUSUBJIDAESEQAETERM
YAMAA-011HEADACHE
YAMAA-012NAUSEA
YAMAA-011DIZZINESS

input/dm.csv

Edit3 rows
STUDYIDUSUBJIDAGESEXARMRFXSTDTC
YAMAA-0164FDrug A2026-02-02
YAMAA-0147MPlacebo2026-02-04
YAMAA-0158FScreen Failure—

Expected output

Under review6 expected rows

expected/adae.csv

Edit3 rows
STUDYIDUSUBJIDAESEQAETERMAGESEXARMTRTSDT
YAMAA-011HEADACHE64FDrug A2026-02-02
YAMAA-012NAUSEA64FDrug A2026-02-02
YAMAA-011DIZZINESS58FScreen Failure—

expected/adsl.csv

Edit3 rows
STUDYIDUSUBJIDAGESEXARMTRTSDT
YAMAA-0164FDrug A2026-02-02
YAMAA-0147MPlacebo2026-02-04
YAMAA-0158FScreen Failure—
Shaded columns are derived— = missing value

Human review and assessment

Your review

2 questions and your comments · View benchmark discussions

Mapping spec

Generated from the benchmark YAML; do not edit by hand

Dataset NameVariable NameVariable LabelTypeCodelist/Controlled TermsCoreComputational MethodOrigin
ADAESTUDYIDStudy IdentifiercharacterCopy value from AE.STUDYID.Predecessor
ADAEUSUBJIDUnique Subject IdentifiercharacterCopy value from AE.USUBJID.Predecessor
ADAEAESEQSequence NumbernumericCopy value from AE.AESEQ.Predecessor
ADAEAETERMReported Term for the Adverse EventcharacterCopy value from AE.AETERM.Predecessor
VersionDateAuthorDescriptionReviewerSign-off
1.72026-10-20yamaa docs buildRead a specification in the 1.0 surface as its 0.5 counterpart; state that missing values stay missing where a mapping declares no missing handler, and leave out a declared missing answer that restates a handler's default
1.62026-10-17yamaa docs buildDescribe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.52026-10-17yamaa docs buildName collected precision in words instead of letter codes; state imputation fallbacks, minimum source precision, bounds ignored outside the collected period, and invalid text with no handler as an error; describe date and datetime shifts, imputation flag codes, and partial text giving no date part
1.42026-10-15yamaa docs buildState datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.32026-09-29yamaa docs buildShow study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.22026-09-29yamaa docs buildClassify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.12026-09-29yamaa docs buildResolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0yamaa docs buildInitial generation from spec.yaml

yamaa code

Public calls generated from benchmark.yaml; results must match the expected output

R

Edit4 lines
library(yamaa)yamaa_spec("spec_adsl.yaml")$run()$save()yamaa_spec("spec_adae.yaml")$run()$output

Python

Edit4 lines
import yamaayamaa.spec("spec_adsl.yaml").run().save()yamaa.spec("spec_adae.yaml").run().output