What is it? Why is it important?

Variables are medical values or information of interest to a researcher. During study conduct, only variables defined in the study protocol can be collected and used for analysis.


Variables are either:

  • Quantitative based on the process of counting or measuring something (e.g. age, weight, lab values, health scores, percentage)
  • Qualitative which are non-numerical characteristics but can be fitted according to categories (e.g. eye colour, gender, education)


In studies one differentiates between:

  • An outcome or dependent variable: is a variable that researchers want to investigate (i.e. understand, explain, or predict)
  • A predictor or independent variable: is a variable that potentially has an effect on the outcome
  • A confounding variable: is a variable that can lead to the misinterpretation of study results


When addressing a research question, researchers study the association between a study outcome of interest and one (or several) predictor(s). It is important to identify confounding variables in order to control their potential impact on study outcome.



Reecommended guidelines to follow:

  • Collected variables should provide all necessary information needed by a researcher to answer the study question
  • Variables entered in the study database (eCRF) should be collected as completely as possible. Incomplete or missing variables should be avoided
  • Some variables are collected at different visits, and can therefore have different values based on the collection time point
  • Variable names should provide an idea of its content. A nomenclature integrating related events and the type of variable collected should be used (e.g. preop_temp_val)
  • In order to facilitate data analysis, qualitative variables can be coded (e.g. 1 for Yes, 0 for No)


What do I need to do?

As a SP-INV:

Define variables needed to answer your study question including:

  • The source (SD) from where the data is retrieved (e.g. laboratory reports, physical examination, medical history, patient file,  participant diary)
  • Means used to collect data (e.g. iPad/tablet, pCRF, questionnaires, physician interviews)


Consult a statistician to ensure variables are suitable for statistical analysis, such as:

  • The selection of appropriate and measurable study variables. This is especially important in order to ensure variables are useful in the interpretation of study results (e.g. study endpoint)
  • The implementation of harmonised data formats (e.g. implemented codes, classifications)


Document selected variables and the rational for their study inclusion in the study protocol, and as applicable the DMP


During study conduct the collection of variables might depend on study progress, such as:

  • Some study endpoint variables are only collected towards the end of a study (e.g. cancer status 6 months after treatment stop, % blood pressure improvement after 6 weeks treatment compared to baseline)
  • Descriptive variables might only be collected at the beginning of the study, such as during a screening- or baseline visit (e.g. age, gender, disease characteristics at study start, level of education, socioeconomic factors)


The visit-plan provides a good overview to study staff and ensures that no variables are forgotten during study conduct. Thus, the collection of study variables should be well structured:

  • List study visits in chronological order based on study progress (e.g. screening visit, baseline visit, followed by interim- until last study visit)
  • Group variables according to topic (e.g. lab data), collection time point, and entry operator

Where can I get help?

Your local CTU can support you with experienced staff regarding this topic


ICH GCP E6(R2) – see in particular guideline

  • 5.5. Trial Management, data handling, and record-keeping

Swiss Law

ClinO – see in particular article and annex

  • Art. 5 Rules of Good Clinical Practice
  • Annex 3 Application documents to be submitted to EC
  • ClinO – Clinical Trials Ordinance
  • CTU – Clinical Trials Unit
  • DMP – Data Management Plan
  • EC – Ethics Committee
  • CRF – Case Report Form
  • eCRF – electronic Case Report Form
  • pCRF – paper Case Report Form
  • ICH GCP – International Council for Harmonisation Good Clinical Practice
  • SD – Source Data
  • SP-INV – Sponsor-Investigator
Development ↦ Data Management ↦ Database Development ↦ Variables

Provides some background knowledge and basic definitions

Basic Monitoring
Basic Drug or Device

Starts with a study idea

Ends after having assessed and evaluated study feasibility

Concept Drug or Device

Starts with confidence that the study is feasible

Ends after having received ethics and regulatory approval

Development Drug or Device

Starts with ethics and regulatory approval

Ends after successful study initiation

Set-Up Ethics and Laws
Set-Up Quality and Risk
Set-Up Drug or Device

Starts with participant recruitment

Ends after the last participant has completed the last study visit

Conduct Drug or Device

Starts with last study visit completed

Ends after study publication and archiving

Completion Statistics
Completion Drug or Device
Current Path (click to copy): Development ↦ Data Management ↦ Database Development ↦ Variables

Please note: the Easy-GCS tool is currently under construction.