1 Testing and developing statistical models for adoption studies of genetic and environmental influences of premature death Introduction and summary Paper.

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1 Testing and developing statistical models for adoption studies of genetic and environmental influences of premature death Introduction and summary Paper I: Case-control study of genetic and environmental influences on premature death of adult adoptees. Genetic Epidemiology Paper II: Comparison of case-cohort estimators based on data on premature death of adult adoptees. Statistics in Medicine Paper III: Premature death of adult adoptees, analyses of a case-cohort sample. To appear in Genetic Epidemiology Paper IV: Inference methods for correlated left truncated lifetimes: parent and offspring relations in an adoption study. Submitted

2 Main aims: Epidemiological: Quantify genetic and environmental effects on premature overall and cause-specific death among adult Danish adoptees Statistical: Investigate and compare different study designs and statistical methods that may be used in such adoption studies

3 Data from Danish adoption register All non-familial adoptions Pedigree established and mortality traced through a number of different registers. Quite time consuming and costly for the early years. Different periods of follow-up in the four papers (paper I: July 8th 1982; papers II and III: April 1st 1993; paper IV: December 31st 1998)

4 Aim at studying the dependence between life times of the adoptees and their four parents (biological and adoptive). Options: Consider simultaneously the life time of an adoptee and the life times of all its four parents Consider the life time of an adoptee and the life times of its two biological/adoptive parents (papers I-III) Consider the life times of an adoptee and the life time of each of its four types of parents (paper IV)

5 Simultaneous or conditional modelling: Consider the joint distribution of the life time of an adoptee and the life time(s) of one or more of its parents (paper IV, one parent) Consider the conditional distribution of the life time of an adoptee given the life time(s) of one or more of its parents, or the other way around (papers I-III)

6 Options for conditional modelling: Study the conditional distribution of life time of the adoptees by univariate survival analysis methods using dichotomized information on the life time of the parents (biological or adoptive) as covariates Study the conditional distribution of the lifetime of the parents (biological or adoptive) by univariate survival analysis methods using dichotomized information on the lifetime of the adoptee Study the conditional distribution of dichotomized life time of the adoptees by conditional logistic regression using dichotomized information on the lifetimes of the parents (biological or adoptive) as covariates

7 Paper I: Select case and control families according to whether adoptee was dead or alive 8 July 1982, matched by gender and date of birth of adoptee Break the matching and analyse the data as a cohort of "case parents" and a cohort of "control parents" (biological or adoptive), concentrating on the age span years

8 Adopt a Cox model with separate baselines for mothers and fathers, and use a robust standard deviation to account for dependence between the life times of the parents

9 A supplementary analysis use conditional logistic regression to analyze dichotomized life times of the adpotees with dichotomized life times of the parents as covariates

10 Also a reanalysis of the cohort of adoptees born (as in Sørensen et al, 1988) with dichotomized life times of parents as covariates

11 Paper I, p. 130: Under which assumptions are the results comparable? Could these have been investigated?

12 Paper II: Aim: Use simulations to study estimators for the regression coefficient and its variance for case-cohort data of the adoptees lifetimes using dichotomized information on parental life times as covariates

13 Pseudo-likelihood for case-cohort:

14 Results for estimation of the regression coefficient:

15 Results for estimation of variances: The bad results for the S&P variance estimator are surprising.

16 Paper III: Premature death of adult adoptees, analyses of a case-cohort sample Liselotte Petersen. Per K. Andersen and Thorkild I. A. Sørensen Aim: Analyse case-cohort data of the adoptees lifetimes using dichotomized information on parental life times as covariates using the methods studied in Paper II Supplementary aim: Analyse the data as a cohort of "case parents" and a cohort of "control parents" (biological or adoptive) using dichotomized information on adoptees life times as covariates cf. paper I

17 _ Case-cohortCohorts of paren _ Total1.27 (1.06, 1.52)1.16 (1.05, 1.27) Natural1.31 (1.04, 1.63)1.08 (0.96, 1.23) Infections1.67 (0.94, 2.96)1.10 (0.75, 1.61) Respiratory1.59 (0.61, 4.00) 1.12 (0.59, 2.10) Vascular1.79 (1.20, 2.68)1.45 (1.14, 1.84) Cancer1.01 (0.69, 1.48)0.91 (0.70, 1.20) "Analysing parents' lifetimes, using adoptees' death as covariate gave the same overall picture, and, as expected, with more narrow confidence limits" (p. 78) Results for biological parents (cf. tables 2 and 3):

18 "The proportional hazards assumption was tested based on Schoenfeld's residuals [Schoenfled, 1982; Grambsch & Therneau, 1994] and could not be rejected" (p 77) Are some modifications needed for case-cohort data?

19 Paper IV: Premature death of adult adoptees, analyses of a case-cohort sample Liselotte Petersen. Per K. Andersen and Thorkild I. A. Sørensen Aim: Analyse case-cohort data of the adoptees lifetimes using dichotomized information on parental life times as covariates using the methods studied in Paper II Supplementary aim: Analyse the data as a cohort of "case parents" and a cohort of "control parents" (biological or adoptive) using dichotomized information on adoptees life times as covariates cf. paper I

20 Dependence between life times T a = life time of adoptee T p = life time of one of the parents Main interest is in the dependence between T a and T p The study of this dependence is complicated by censoring and the available data

21