What is it? Why is it important?

Study data is ready for analysis and ready for export to a statistical software system, once data collection is complete and all open issues are resolved (e.g. resolution of data queries during data monitoring).

 

Prior to data analysis the study data must be prepared (i.e. by a statistician). Preparatory tasks may include the appropriate:

  • Recording of variables (e.g. the labelling of missing data as NA, substitute text with numbers: Male=1, Female=2)
  • Formatting of time and date (e.g. day comes before month)
  • Generation of variables (e.g. compute participant age based on birth-year and date at study inclusion, or BMI based on height and weight)
  • Configuration of data. Example: a variable is collected at several time points, and data can either be documented in a:
    • Wide format: one line per participant with several columns showing values collected at time-point 0, 1, 2…
    • Long format: each participant occupies several lines, with each time point represented by an added line

What do I need to do?

As a SP-INV:

  • Instruct the data manger to export the data (ready for analysis) from the study database to a statistical software system
  • Ensure the exported data does not contain any participant identifying variables
  • For blinded study, ensure procedures are in place to protect the blind (e.g. exported data does not contain variables disclosing participant treatment (i.e. whether a participant belongs to the intervention or control group)

 

For data analyses to be traceable and reproducible, requires that study staff working with the study data (e.g. data manager, statistician, SP-INV) have access to the same data-set. Therefore, data corrections are done:

 

In the event corrections are required on exported data, the statistician must seek approval from the SP-INV. In addition:

  • The SP-INV must approve any corrections/changes to the study data
  • The statistician retains the audit trail by documenting any changes/corrections

More

The statistician can start to prepare the data for analysis, once data is accessible in a statistical software system.

 

Where can I get help?

Your local Research Support Centre can assist you with experienced staff regarding this topic

  • Basel, Departement Klinische Forschung (DKF), dkf.unibas.ch

  • Lugano, Clinical Trials Unit (CTU-EOC), ctueoc.ch

  • Bern, Department of Clinical Research (DCR), dcr.unibe.ch

  • Geneva, Clinical Research Center (CRC), crc.hug.ch

  • Lausanne, Clinical Research Center (CRC), chuv.ch

  • St. Gallen, Clinical Trials Unit (CTU), h-och.ch

  • Zürich, Clinical Trials Center (CTC), usz.ch

References

ICH GCP E6 (R3) – see in particular:

  • 3.11.3 Quality control
  • 3.16.2 Statistical Programming and Data Analysis
  • 3.16.2 c Sponsor should ensure traceability of data transformation and derivations
  • 4.2.4 Data corrections
  • 4.2.6 Finalisation of data sets prior to analysis

ICH Topic E9 – see in particular

  • 5.2.1 Full analysis set
  • 5.2.2 Per protocol set
  • 5.3 Missing values and outliers
  • 5.4 Data transformation

Swiss Law

ClinO – see in particular article

  • Art. 2b Definition of intervention

ClinO-MD – see in particular article

  • Art. 2a Definition of clinical intervention
  • Art. 2a Definition of performance study

HRO – see in particular article

  • Art. 3a Definition of research
Abbreviations
  • BMI – Body Mass Index
  • ClinO – Clinical Trials Ordinance
  • ClinO-MD – Ordinance on Clinical Trials of Medical Devices
  • CTU – Clinical Trials Unit
  • HRO – Human Research Ordinance
  • ICH – International Council for Harmonisation
  • ICH-GCP – International Council for Harmonisation - Good Clinical Practice
  • NA – Not available
  • SP-INV – Sponsor Investigator
Completion ↦ Statistic Methodology ↦ Data Preparation ↦ Procedures
Study
Basic

Provides some background knowledge and basic definitions

Basic Monitoring
Concept

Starts with a study idea

Ends after having assessed and evaluated study feasibility

Concept Statistic Methodology
Concept Drug or Device
Development

Starts with confidence that the study is feasible

Ends after having received ethics and regulatory approval

Development Drug or Device
Set-Up

Starts with ethics and regulatory approval

Ends after successful study initiation

Set-Up Ethics and Laws
Set-Up Statistic Methodology
Set-Up Quality and Risk
Set-Up Drug or Device
Conduct

Starts with participant recruitment

Ends after the last participant has completed the last study visit

Conduct Statistic Methodology
Conduct Drug or Device
Completion

Starts with last study visit completed

Ends after study publication and archiving

Completion Drug or Device
Current Path (click to copy): Completion ↦ Statistic Methodology ↦ Data Preparation ↦ Procedures

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