Storing Results Data

Clement McDonald, M.D.

Director, Lister Hill Center National Center for Biomedical Comm Communications unications

National Library of Medicine

February 11, 2008

Scope

• The focus is on summary data of the kind one sees in publication
• Characteristics of patients at base line
• Differences between the outcomes of the various study arms
• Not patient level data

Goals

• Represent this data in a generalized but “structured structured” format
• Take advantage of what is in the registry data base to ease entry of results data
• Minimize entry work
• Accommodate most study designs

Three parts to the problem

• Define the variables - used in the study
  • To characterize population
  • To measure outcomes
  • Etc.
  - E.g. Age, creatinine, PHQ PHQ-9

For each variable

• Name
• Description
• Data type (e.g. continuous, categorical, time to event)
• Additional informatino depending upon data type e.g.:
  • For categorical variables - the categories
  • For continuous variables - the units of measure

Define the study arms and phases.

• Name
• Description
• E.g.
  • Arm 1 - treat with new drug or device X
  • Arm 2 - placebo
• Statistical analyses – as descriptive text.

Define tables

• Rows variables
• Columns study arm phase - and one column for statistical analysis.
• List the discrete summary observations per cell depends on data type
  - E.g. for continuous
  • N
  • Mean
  • Coefficient of variation
  • (more)

Data structures

• XML for current testing phase

As relational data base - simplest incarnation

• Table for study – with record per study
• Table for variables - one record per variable
• Table for study arms/phases - one record per study arm phase
• Table for overview of each tables – one record per cell
• Table to define each table - one record per cell

Non trivial problem

• Especially for newer study designs