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Birth Weight and Childhood Cancer and Leukemia

Birth Weight and Childhood Cancer and Leukemia. Update from the I4C Environmental Working Group on Birth Weight and Childhood Cancer. Ora Paltiel, Hadassah-Hebrew University, School of Pubic Health, Jerusalem , Israel. Lyon, November, 2012. Background- Big babies and leukemia.

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Birth Weight and Childhood Cancer and Leukemia

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  1. Birth Weight and Childhood Cancer and Leukemia • Update from the I4C Environmental Working Group onBirth Weight and Childhood Cancer Ora Paltiel, Hadassah-Hebrew University, School of Pubic Health, Jerusalem , Israel Lyon, November, 2012

  2. Background- Big babies and leukemia

  3. Beyond birth weight… fetal growth and leukemia • Gestational age • "proportion of optimal birth weight derived from a regression equation including gestational age, maternal height, parity and infant sex

  4. Birth certificate data of 2,254 children with cancer <5 years old at diagnosis and registered at Texas Cancer Registry 1995-2003 were compared to 11,734 age-matched controls. • Using model diagnostics, the model containing BW corrected-for-gestational age was a better predictor than the model with BW alone

  5. Determinants of birth weight SES ethnicity Smoking Gestational diabetes Maternal height Pre-pregnancy BMI Gestational weight gain • Gestational age • Birth length • Child gender • Altitude • Birth order

  6. Identified new case for action…. Prevalence of obesity in 20-29 yo females US 1960-2004 Prevalence of obesity among pregnant women

  7. Stated Aim Of I4C study • To investigate the association between birth weight (BW) and other measures of fetal growth and childhood cancer, specifically leukemia, with specific attention to determinants of BW such as maternal obesity, weight gain in pregnancy, pregnancy complications, in a pooled analysis of childhood cancer cohorts.

  8. Stated Specific objectives • To examine the pattern of the association between BW and other measures of fetal growth and the risk of childhood AML, ALL, all leukemia, other cancers: U, linear, threshold effect, and examining BW both as a continuous and categorical variable • To examine these associations in specific age groups: Infant (up to age 1 year); Early childhood (1-4); Later childhood (5-9); Early adolescence (10-14), controlling for and in strata of maternal prepregnancy BMI, and weight gain during pregnancy.

  9. Participating cohorts MoBa DNBC ALSPAC CPP JPS TIHS

  10. Steps in data analysis • I. Getting to final data set: • 1. Obtaining data • 2. Data checking • 3. Data harmonizing I. Looking at descriptive characteristics and covariates II.Model birth weight III. Univariate models, then bivariate, then multivariate IV. Stratified analyses

  11. Decisions along the way Not to analyse AML or solid tumor subtypes JPS, choose only from sub-cohort with gestational age, and adjust all analyses for GA Remove all postnatal exposures from the analysis Report on covariates when reported in >5 cohorts Concentrate on maternal anthropometrics as control and stratification variable Report on BW as categories; deciles; continuous At this point –not report POBW

  12. Basic data analysis strategy • Exclude multiple births and Down syndrome • Include all cancer cases besides above • Case-cohort design with subcohort approx 1:10 for cancer/leukemia cases • Cox regression • Report HR and 95% CI • Always adjust for study • STATA

  13. TABLE 1: Descriptive characteristics of sub-cohorts in pooled database

  14. Table 2:  Distribution of All Cancers, Leukemia and ALL by cohort, gender and age of diagnosis, used in analysis of pooled dataset. based on singleton births, Down Syndrome excluded

  15. Coviariates and Birth WeightParental demographic and habits Data for 5 cohorts only*

  16. Covariates and Birth WeightInfant characteristics Data for 5 cohorts only*

  17. Covariates and Birth WeightMaternal anthropometrics and diabetes Data for 5 cohorts only*

  18. Main Findings1. Linear association of all outcomes with BWadjusted for GA ALL All leukemia All cancer

  19. Associations between BW measures and All Cancer adjusted for study

  20. BW associations with leukemia All leukemia ALL

  21. Relationship between BW and CC, Leukemia, and ALL • Is it consistent: • Across gender? • Across age groups (at diagnosis)? • Across study? • Across strata of maternal BMI? • Across strata of weight gain in pregnancy?

  22. Relationship between BW and CC, Leukemia, and ALL Is it consistent: Across gender?- no difference, not shown Across age groups (at diagnosis)? Across study? Across strata of maternal BMI? Across strata of weight gain in pregnancy?

  23. Main FindingsHeterogeneity among cohorts

  24. Stratified analyses:Different pattern of BW cancer association by age group HR HR All cancer Leukemia ALL Age at dx. 0-<5 Age at dx. 5-15

  25. Stratified analysis by maternal anthropometrics for all cancer Pre-pregnancy BMI • <25kg/m2 • HR 1.33 (1-3.59) • >25 kg/m2 • HR 1.24 (0.8-1.92) (Continuous per kg( Pregnancy weight gain • <16kg • HR 1.29 (0.95-1.77) • >16 kg: • HR 1.27 (0.79-2.03) (Continuous per kg(

  26. Coherence with literature?High Birth weight (categorical) and childhood leukemiaCaughey and Michels International Journal of Cancer 2009 1.36 (1.24-1.49)

  27. Birth weight per kg and childhood leukemia: Millions of observations International Journal of CancerVolume 124, Issue 11, pages 2658-2670, Samuelsen (Epidemiology 2009) Norwegian Cancer Registry including 1,842,113 live-born infants born 1967 -1998 demonstrated an increase in leukemia risk of 29% per 1000g increase in birth weight, increase for all cancers was 23% after adjustment for gestational age

  28. High Birth weight and childhood ALL 1.24 (1.16-1.33) International Journal of CancerVolume 124, Issue 11, pages 2658-2670, 18 DEC 2008 DOI: 10.1002/ijc.24225http://onlinelibrary.wiley.com/doi/10.1002/ijc.24225/full#fig2

  29. Summary • Pooled analysis confirms BW-cancer and BW- leukemia association • Pattern varies by age at diagnosis • Heterogeneity among cohorts observed but less for linear measure • Maternal obesity and weight gain do not appear to alter the association, which is significant for All Cancer, Leukemia and ALL in the stratum of offspring of non-obese mothers • Comparable to literature

  30. Major limitations • Small sample size –still! • Limited power for MV analysis • Missing variables (Parity), missing values (many) • Inconsistencies in measures (parity, paternal age) • Uncertainty regarding follow up in some cohorts (CPP) • Cancer ascertainment not uniform- CPP

  31. Thoughts…. • Extensive data set exists – needs to be used to study questions of birth order, maternal and paternal age, parental smoking etc • Very rich data set exists for determinants of BW – should be separate publication?

  32. Gabriella Tikellis • Karen Lamb • Terry Dwyer • Working group members • All participating cohorts • Mothers and babies

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