Count Treatment Days From a Saved Demographics File

Review ask

As a clinical trial statistician or programmer, answer two short questions in Your review: the task and the inputs and outputs. Agreeing with both approves this benchmark; disagreeing with either needs a comment. Propose a fix with the Edit button on any source file, or add it to your comments.

We suggest spending no more than 5 minutes on a review. The other tabs beside Your review are background for assessment, not under review.

Summary

EditUnder reviewWhat this benchmark means

README.md

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

Goal: derive each subject's first and last treatment dates (TRTSDT, TRTEDT) and the number of days on treatment (TRTDURD) in ADSL, from the demographics (DM) file that an earlier step builds and saves.

Input: two spec files, run in order:

spec_dm.yaml builds DM from one comma-separated record per subject and saves it as dm.csv, carrying the first (RFXSTDT) and last (RFXENDT) treatment dates as dates;
spec_adsl.yaml is the entry: it reads the saved dm.csv, whose fields hold what the spec that wrote it declares, so its dates are dates without being declared again.

Variables:

TRTSDT and TRTEDT are DM's first and last treatment dates;
TRTDURD counts the days from TRTSDT to TRTEDT, both included, so a single treatment day gives one; it stays empty when either date is missing.

Note: a comma-separated file stores every value as text. The dates in dm.csv are still dates when the entry reads it back, because the spec that wrote it declares them so, and the day count works on them directly.

YAML specification

2 spec files

spec_dm.yaml
Edit32 lines
1yamaa: "1.0"2type: spec3model: ADaM4domain: DM5keys: [STUDYID, USUBJID]6input:7  SUBJECTS: {path: input/subjects.csv, types: {RFXSTDT: date, RFXENDT: date}}89output:10  path: dm.csv11  columns: [STUDYID, USUBJID, RFXSTDT, RFXENDT]1213columns:14  - name: STUDYID15    type: str16    label: Study Identifier17    derivation: SUBJECTS.STUDYID1819  - name: USUBJID20    type: str21    label: Unique Subject Identifier22    derivation: SUBJECTS.USUBJID2324  - name: RFXSTDT25    type: date26    label: Date of First Study Treatment27    derivation: SUBJECTS.RFXSTDT2829  - name: RFXENDT30    type: date31    label: Date of Last Study Treatment32    derivation: SUBJECTS.RFXENDT
spec_adsl.yaml
Edit49 lines
1yamaa: "1.0"2type: spec3model: ADaM4domain: ADSL5keys: [STUDYID, USUBJID]6input:7  # DM is the artifact spec_dm.yaml saves before this entry is built. The8  # link types its fields: RFXSTDT and RFXENDT are dates, although a CSV9  # file stores them as text.10  DM:11    path: dm.csv12    schema: spec_dm.yaml1314output:15  path: adsl.csv16  columns: [STUDYID, USUBJID, TRTSDT, TRTEDT, TRTDURD]1718columns:19  - name: STUDYID20    type: str21    label: Study Identifier22    derivation: DM.STUDYID2324  - name: USUBJID25    type: str26    label: Unique Subject Identifier27    derivation: DM.USUBJID2829  - name: TRTSDT30    type: date31    label: Date of First Exposure to Treatment32    derivation: DM.RFXSTDT3334  - name: TRTEDT35    type: date36    label: Date of Last Exposure to Treatment37    derivation: DM.RFXENDT3839  # Reads the linked dates themselves, so their type comes from the link.40  - name: TRTDURD41    type: int42    label: Total Treatment Duration (Days)43    derivation:44      diff:45        type: date46        start: DM.RFXSTDT47        end: DM.RFXENDT48        unit: day49        closed: both

Inputs

Under review1 source file

input/subjects.csv

Edit5 rows

input/subjects.csv
STUDYID	RFXSTDT	RFXENDT
YAMAA-01	2024-01-10	2024-03-09
YAMAA-01	2024-02-01	2024-02-01
YAMAA-01	2024-02-28	2024-03-01
YAMAA-01	2024-03-05	—
YAMAA-01	—	—

Expected output

Under review10 expected rows

expected/adsl.csv

Edit5 rows

expected/adsl.csv
STUDYID	TRTSDT	TRTEDT	TRTDURD
YAMAA-01	2024-01-10	2024-03-09	60
YAMAA-01	2024-02-01	2024-02-01	1
YAMAA-01	2024-02-28	2024-03-01	3
YAMAA-01	2024-03-05	—	—
YAMAA-01	—	—	—

expected/dm.csv

Edit5 rows

expected/dm.csv
STUDYID	RFXSTDT	RFXENDT
YAMAA-01	2024-01-10	2024-03-09
YAMAA-01	2024-02-01	2024-02-01
YAMAA-01	2024-02-28	2024-03-01
YAMAA-01	2024-03-05	—
YAMAA-01	—	—

Shaded columns are derived— = missing value

Human review and assessment

Dataset Name	Variable Name	Variable Label	Type	Codelist/Controlled Terms	Computational Method	Origin
ADSL	STUDYID	Study Identifier	character		Copy value from DM.STUDYID.	Predecessor
ADSL	USUBJID	Unique Subject Identifier	character		Copy value from DM.USUBJID.	Predecessor
ADSL	TRTSDT	Date of First Exposure to Treatment	numeric	ISO 8601	Copy value from DM.RFXSTDT.	Predecessor
ADSL	TRTEDT	Date of Last Exposure to Treatment	numeric	ISO 8601	Copy value from DM.RFXENDT.	Predecessor
ADSL	TRTDURD	Total Treatment Duration (Days)	numeric		Whole days from DM.RFXSTDT to DM.RFXENDT, counting both endpoints.	Derived

Version	Date	Author	Description
1.7	2026-10-20	yamaa docs build	Read 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
1.6	2026-10-17	yamaa docs build	Describe collected date parts written as ISO 8601 date text and times of day counted in seconds since midnight
1.5	2026-10-17	yamaa docs build	Name 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
1.4	2026-10-15	yamaa docs build	State datetime precision codes through the hour and minute, and complete only the time parts a collected datetime lacks
1.3	2026-09-29	yamaa docs build	Show study codelist names, external dictionaries, and ISO 8601 formats in variable rows; list the document's codelist values and metadata
1.2	2026-09-29	yamaa docs build	Classify ADaM copies from a declared input as Predecessor and recodes as Derived, and SDTM recodes of locally derived columns as Derived
1.1	2026-09-29	yamaa docs build	Resolve lookups into the donor record they select, and give every derivation shape a plain-language rule instead of its raw YAML
1.0		yamaa docs build	Initial generation from spec.yaml

R

Edit4 lines

1library(yamaa)23yamaa_spec("spec_dm.yaml")$run()$save()4yamaa_spec("spec_adsl.yaml")$run()$output

Python

Edit4 lines

1import yamaa23yamaa.spec("spec_dm.yaml").run().save()4yamaa.spec("spec_adsl.yaml").run().output

input/subjects.csv

expected/adsl.csv

expected/dm.csv

Your review

Mapping spec

yamaa code

R

Python