Data collection, storage and presentation

1
Data collection, storage and presentation

• ASNEMGE, Young Investigators Meeting
• Interactive course
• Daisy Jonkers
• University Hospital Maastricht

2
Performing the study

• Study protocol
• Define outcome parameter
• Define best assay / method to measure
• Perform and validate method BEFORE start study
• Standardised procedures

3
Standardised procedures

• Collection of biological samples storage
  conditions, small portions, codes)
• Lab stick to protocol
• work accurate
• control conditions
• limit inter-test variation
• Animals one batch (animals, food)
• housing conditions, stress
• Clinical assessment one person, same
  equipment, etc.
• Questionnaires validated
• Include controls !!!

4
Before start of study

• Standardised and validated procedures
• Flow-chart
• Pilot to test your methods in advance
• Ethics

5
Ethics

• Declaration of Helsinki
• Ethical principles for medical research
  involving humans subjects
• - importance of objectives must be in proportion
  to risk
• - scientific quality
• - concern for subject must always prevail over
  scientific interest
• - detailed information
• - written informed consent
• - right to withdraw
• - data confidentiality
• etc.
• Medical Ethics Committee
• In research proposal / manuscript -gt compliance
  with declaration

6
GCP/ GLP

• Good Clinical practice (GCP)
• - guidelines for all studies with medication
• -gt to protect trial subjects
• -gt to obtain reliable results (accurate,
  complete, verifiable)
• - International guidelines
• FDA (www.fda.gov/oc/gcp/guidance.html)
• Europe (www.efpia.org/6_publ/document/clinical.p
  df)
• Good laboratory practice (GLP)
• - to ensure quality and reliability
• - work according to protocols and write down all
  deviations
• - www.oecd.org
• Animal experiment committees
• respect for animals replacement, reduction and
  refinement

7
Data collection

• Case-record form uniform registration
• all variables (in logical order)
• Stick to standardised procedures
• Handle all samples the same
• Work accurate/ be complete
• Document every deviation!!!
• Do what your write and write what you do!

8
Creating a data base I

• Spread-sheets such as excel
• -gt easy to import to statistics and graphic
  programs
• Discuss with statistician before start
• Enter data in a standardised way
• manual
• scanning
• connection with computerised
• Code-book

9
Creating a data base II

• Check, check, check (double entry, parallel
  files)
• Check for mistakes lowest-highest
• diagram of distribution
• etc.
• Archive /back up
• Privacy

10

• When all data are complete -gt code can be broken
• and then statistics...
• Be sure to use the right statistical test
• (go to see a statistician.)

11
Interpreting results I

• Start with answering hypothesis
• Know your data
• Obtained values in expected range?
• If not, possible reasons for mistakes?
• Observed statstical differences expected/logic?
• Compare findings with others
• think about mechanisms behind findings
• Discuss with others
• Check literature
• Consequences of findings

12
Interpreting results II

• Other remarkable / unexpected findings?
• Negative findings are also important
• Always keep limitations of your study in mind

13
Presentation of results

• . Show your results to the world...

14
.
Title Effect of anti-inflammatory drug
x variable group I group II weight 70
3 80 9 age 56 5 50 4 CRP 200
50 2000 300 MPO 0.08 0.01 0.09
0.02 GST 0.100 (0.050-0.200) 0.50
(0.020-0.080) TEAC 120 (80-140) 130 (70-200)

Table / figures should be - clear without
context - title - group definition and
numbers - what samples - variables
units, uniform - accurate
15
Presentation of results

• . Show your results to the world...
• abstracts
• presentations
• manuscript
• guidelines for writing