Bruce Wolffenbuttel

Joost Keers

LifeLines

LifeLines

• ‘Broad spectre’ Biobank: Genes, physical examinations, lifestyle, environment,

psychological.

• 165,000 people

• 3 generations

• 30 years follow-up

Focus

Ag

eing

•Metabolic disease & Diabetes

•Cardiovascular & Renal

•Asthma, COPD, Allergy

•‘ Psychiatry’ (Depression & Cognitive)

•Musculoskeletal & Joint

1st generation 2nd generation 3rd generation

80 + 50 25 0 jr

Father

Mother

Partner’s father

Partner’s mother

‘Index’

Partner

Child 1

Child 2

45,000

30,000

55,000 35,000

Total number of participants:

165,000

Datacollecting: 5-year cycle

Baseline

1 year

General &Thematic

2 year

General &Thematic

3year

General &Thematic

4 year

General &Thematic

LifeLines gegevens verzameling

LifeLines Datacenter

Life

Lin

es

La

b &

Arc

hiv

e, Q

A/Q

C

GP Records

GP Health RecordSymptomsDiagnosesReferralsMedicationsProcedures

Hospital RecordsICD-10/ICD-9 (Diagnoses) OPCS4 (procedure)Primary Diagnosis

Questionnaire e.g.DietCircumstancesFamily HistoryEmploymentSmoking, alcoholLifestyleMedicationsCognitive FunctionHealth

Measurements e.g.Height, WeightRespiratory FunctionSightBlood Pressure

ResultsBiochemistryHaematologyAdvanced testingBiomarkersGenomics

Yearly

First step

• Asking all departments (UMCG) what they need/ want to be measured in lifeLines

• Categorizing wishes and needs Outcome – predictor Related to central focus? Looking for overlap Determine multiple interests

Second step

• Selection of baseline measures based on 1st step

• Comparing this selection to other biobanks using the Datashaper

• Adapting selection based on Datashaper

Third step

• Selection or composing measures to collect data (Questionnaires, procedures, lab, etc.). Using Datashaper/ catalogue

• Feedback to departments

• Monitoring during use (pilot study, interviews)

How we used Datashaper

• Making sure we measured the most important domains

• As a support to select a variable

• Making sure our ‘data-items’ can be converted into variables that can be shared.

• Extra focus on registrating data-collection procedures and cirumstances, using SOPs

When we did not follow datashaper

• With respect to some variables we used more detailled instruments to collect data, e.g. quality of life and well-being.

• ‘unique’ interests (cognitive functioning, personality).