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  • Include PARCAT1 in ADQRS datasets in case multiple instruments are subsequently combined into a single dataset.  PARCAT1 contains the name of the instrument, and may come from QS.QSCAT.
  • PARCAT2 is allowed if needed, and should contain the subscale name (may come from QS.QSSCAT, but is driven by analysis/reporting needs).
  • Bring QSTEST and QSTESTCD directly into PARAM and PARAMCD, respectively, for maximum traceability back to QS.
  • Keep QSORRES, and use AVALC only if it differs from QSORRES.
  • Set ANLxxFL and ABLFL only on total score and sub-score records, unless individual items are also summarized.
  • Include at least one treatment variable (TRTP/TRT01P/TRTA/TRT01A) in examples for now, to conform to the latest ADaM IG.
  • Use a completely different PARAMCD value for the computed total score than the SDTM QSTESTCD values.  That makes it easier to spot in the data set, and also distinguishes it from a collected total score that may be stored in SDTM.  For the GDS-SF, this will be called GDS02TS.  A new Controlled Terminology request should be submitted for computed score records.
  • Do not include QS, FT or RS in the ADaM dataset names.  That releases 2 more characters for use in the dataset names.  The GDS-SFdata set will be ADGDSSF.
  • Whether to include responses to all items in the ADQRS datasets, or only summary records being analyzed will be decided on a per-instrument basis, so this information will be included in the ADQRS supplements on a per-instrument basis.  However, the FDA has expressed a preference for including both the individual items and summary records in the same dataset.  They recalculate all of the scores to compare against values provided by the sponsor, and it's easier for them if both individual items and summary records are all in the same dataset.
  • Document instrument scoring instructions in define.xml.
  • Even if SDTM has computed a total score, keep a separate ADaM total score record in the analysis dataset. Also keep the total score from SDTM which has a different parameter.
  • When creating PARAMCD values for subscale scores, keep the SDTM QSTESTCD value, and abbreviate any published subscale codes.  Select values for PARCATy and PARAMCD such that the items are grouped in a logical order.
  • Use of "concept domain" and "dimension" in a supplement should be consistent with any published scoring instructions or other references. However, if "dimension" appears in the published references, add "(concept domain)" in parentheses to the supplement the first time "dimension" is used so an individual reviewing and familiar with that terminology will understand that the two terms can be used interchangeably (or vice versa, if "concept domain" or "domain" appears in the published references).
  • Standards can be developed for QS, RS or FT domain instruments, as priorities dictate.
  • Baseline definitions are analysis-specific, and thus are outside the scope of ADQRS supplements.

Tabled Items

  • Need to decide if ASEQ should be required, and if so, should it be unique across all ADQRS datasets, in case they are later combined.
  • Need to develop list of expected variables for all ADQRS datasets.
  • How to handle data sent from a vendor with all scores computed, so there are no separate SDTM/ADaM datasets.
  • Do we need to define baseline in our Best Practices?
  • Should we recommend that each questionnaire be stored in a separate dataset, or leave that up to the sponsor to decide?
  • How much manipulation can be done on AVAL for records coming from SDTM before a new parameter should be used instead of copying QSTEST/QSTESTCD into PARAM/PARAMCD?  For example, what if SDTM only collects character values (<=15 minutes, 15-30 minutes, etc.), but numeric codes are required for analysis- can those go into AVAL?  What would be imputed- the character or the numeric value?  Does this change if we are transforming or reversing collected scores for analysis?
  • How should author codes (question codes pre-printed on the instruments) be handled?  Sometimes the same question can be used on different instruments that are related;  if the data is being pooled across studies for integration, and some of the items are the same, it may be possible to combine data from those items via the author codes.