Completion↦Statistic Methodology↦Data Preparation↦Procedures
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:
- Exclusively in the study database
- Prior to data export to a statistical software
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