Update from the I4C International Data Coordinating Centre

Gabriella Tikellis (PhD)Murdoch Childrens Research Institute6th International I4C Meeting, IARC5-6th October, 2013

CPP - USA60,000 JPS - Israel

92,408

ALSPAC - UK 14,042

TIHS 10,627

DNBC - Denmark 101,042

MoBa - Norway 109,981

BDSS - China 247,831

JECS - Japan 100,000

NCS - USA 100,000

CFCS – China 300,000

CIHS - Brazil 100,000

BCS - UK 100,000

GEHBC – Germany 200,000

MCRI - VIC 100,000

Wuhan - China 120,000

ELFE – France 20,000

Bradford - UK 10,000NINFEA – Italy 7,500

I4C member cohorts

Murdoch Childrens Research Institute

I4C International DataCoordinating Centre

Role of the IDCC

• Coordinate the transfer of cohort data to a central location (i.e. MCRI)

• Maintain and ensure the data is kept secure • In collaboration with cohort representatives, work on the cleaning, validation and

harmonization of variables from each dataset

• Develop pooled datasets for analysis

• Provide statistical support where required

• Work with cohorts, Working Groups and other members to assist and facilitate the various research and day-to-day activities

• Provide scientific input into the development of research proposals

I4C draft policies_March2013

Welcome to our BiostatisticiansProf Stanley Lemeshow Dr Gary Phillips

Center for Biostatistics

Childhood cancer cases

Total number of cancer cases at I4C IDCC: Oct 2013based on all live births

(545)

MoBa: Results from latest linkage to cancer registry in May 2013, found 127 cases of CC. Awaiting details on cancer types to be made available to IDCC

Progress in last 12 months• Ascertainment of follow-up years for each child

• Established age of child at last contact time- for cancer cases and non-cancer subjects across 6 cohorts

Significant amount of work carried out to determine amount of follow up for each subject

Communication with cohorts to establish dates of linkage with cancer registries or last dates of contact

Transfer of questionnaire data

6 cohorts contributing data to the pooled dataset

• ALSPAC, UK• CPP, USA• DNBC, Denmark,• JPS, Israel• MoBa, Norway• TIHS, Australia

Tally of available data at IDCC

380,427- mothers and babies*

* Includes 10% subsample from DNBC and MoBa

Pooled variables provide a ‘core’ dataset which we have used to

examine birth weight and childhood cancer association

Pooled dataset- Birth weight

X = data not collected

? = to be verified

VARIABLE ALSPAC CPP DNBC JPS MoBa TIHS

Maternal age √ √ √ √ √ √Paternal age, years √ √ √ √ √ √

Maternal education, years √ √ √ √ √ √Paternal education, years √ √ √ √ √ √

Single, married, divorced, living together etc. √ √ √ √ √ √

Maternal, prenatal smoking √ √ √ √ √ √Passive smoking, prenatal √ X √ √ √ √

Maternal, prenatal alcohol consumption √ X √ X √ √

Maternal prepregnancy BMI, kg/m2 √ √ √ √ √ √(includes height and prepregnancy weight separately)

Maternal pregnancy weight change, kg √ √ √ √ √ √

Maternal DM √ √ √ √ √ XPaternal DM √ √ √ √ √ X

Parity (number of prior live births) √ √ √ √ √ XPrior miscarriage √ √ √ ? √ X

Xray exposure, prenatal √ √ X √ √ X

MATERNAL ADIPOSITY

DIABETES

REPRODUCTIVE HISTORY

RADIATION EXPOSURE

AGE

EDUCATION

MARITAL STATUS

SMOKING

ALCOHOL

Not all variables included in final models, Variables included were focused on prenatal time period

Birth-related variables VARIABLE ALSPAC CPP DNBC JPS MoBa TIHS

Gestation age, weeks √ √ √ √ √ √Birth weight, grams √ √ √ √ √ √Placental weight, grams √ √ √ X √ √Gender of index child √ √ √ √ √ √Caeserean section delivery √ √ √ √ √ √Length at birth, cm √ √ √ X √ √Head circumference at birth, cm √ √ √ √ √ √Congential abnormality √ √ √ √ √ √Breastfeeding √ √ √ X ? √First born √ √ √ √ √ √

X = data not collected

Focus on additional variables

VARIABLE ALSPAC CPP DNBC JPS MoBa TIHSPrenatal folic acid supplementation √ X √ X √ √Previous fetal loss √ √ √ √ √ XAny child infections √ √ ? ? ? √Use of paid childcare √ X √ X √ √Pesticide expsoure √ X √ X √ X

X = data not collected ? = still being worked on

Cleaning and harmonizing of data on previous fetal loss required over 4 months of work to verify data and document the decisions made

New exposure data

Next steps• Incorporate additional cases of CC from updated linkages to

cancer registries (e.g. MoBa) or new cohorts

• Create new datasets for analysis of other hypotheses to be examined : Parity and birth order Previous fetal loss Parental age

• Identify what data is available on exposures relating to new areas of interest such as infections

Web-based Data Pooling Application at IDCC

(developed by Luke Stevens)

Data Pooling Application• MCRI’s secure e-Research

portal• Restricted access

• I4C team only • Can restrict user access at dataset

level

• Ongoing development

Data Pooling Application• Run a query• Select variables to download• Select from any dataset• Database joins the datasets

returning a combined data file

Data Pooling Application• Select variables to download• Select from any dataset• Database joins the datasets

returning a combined data file

Data Pooling Application

• Edit or Save your query• Download

– Raw data file

Information on I4C• NIH/NCI- I4C portalhttps://communities.nci.nih.gov/i4c/default.aspx

• MCRI- websitehttp://www.mcri.edu.au/research/international-partnerships-collaborations/

i4c

• National Children’s Study websitehttp://www.nationalchildrensstudy.gov/research/internationalinvolvement/

pages/default.aspx

Many thanks to ...• MCRI Terry Dwyer Luke Stevens Karen Lamb

• ALSPAC Jean Golding Kate Northstone

• CPP Mark Klebanoff Logan Spector

• NIH/NCI Martha Linet Somdat Mahabir

• DNBC Sjurdur Olsen Jorn Olsen Marin Ström Charlotta Granström

• JPS Ora Paltiel Elena Polanker

• MoBa Camilla Stoltenberg Siri Eldevik Håberg Therese Bakke