Methods for Assessing Familial Aggregation: Family History Measures and Confounding in the Standard Cohort, Reconstructed Cohort and Case-Control Designs

Zimmerman, Regina; Pal, Deb K.; Tin, Adrienne; Ahsan, Habibul; Greenberg, David A.

doi:10.1159/000224640

Cited by 15 publications

(16 citation statements)

References 10 publications

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“…Two complementary approaches were used to examine the association between familial aggregation of cancer and risk of pediatric/adolescent HL. 25,26 The first approach was a traditional case-control analysis, wherein we used conditional logistic regression to model the association between a positive family cancer history, overall and for specific relative and/or cancer subgroups, and HL in the index child, overall and by tumor EBV status (EBV1 or EBV2); odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate risk. In addition to accounting for matching fac-tors, we adjusted for maternal education level (<high school (HS) graduate, HS graduate or >HS) to control for confounding due to differences in SES levels between cases and controls, and for number of first-and second-degree relatives, respectively, to minimize confounding by family size/ structure.…”

Section: Discussionmentioning

confidence: 99%

“…Two complementary approaches were used to examine the association between familial aggregation of cancer and risk of pediatric/adolescent HL . The first approach was a traditional case–control analysis, wherein we used conditional logistic regression to model the association between a positive family cancer history, overall and for specific relative and/or cancer subgroups, and HL in the index child, overall and by tumor EBV status (EBV+ or EBV−); odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate risk.…”

Section: Methodsmentioning

confidence: 99%

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Family history of cancer and risk of pediatric and adolescent Hodgkin lymphoma: A Children's Oncology Group study

Linabery

Erhardt

Richardson

et al. 2015

Intl Journal of Cancer

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Family history of lymphoid neoplasms (LN) is a strong and consistently observed Hodgkin lymphoma (HL) risk factor, although it has been only marginally examined in pediatric/adolescent patients. Here healthy control children identified by random digit dialing were matched on sex, race/ethnicity, and age to HL cases diagnosed at 0-14 years at Children's Oncology Group institutions in 1989-2003. Detailed histories were captured by structured telephone interviews with parents of 517 cases and 783 controls. Epstein-Barr virus RNA detection was performed for 355 available case tumors. Two analytic strategies were applied to estimate associations between family cancer history and pediatric/adolescent HL. In a standard case-control approach, multivariate conditional logistic regression was used to calculate odds ratios and 95% confidence intervals (CIs). In a reconstructed cohort approach, each relative was included as a separate observation and multivariate proportional hazards regression was used to produce hazard ratios (HRs) and 95% CIs. Using the latter, pediatric/adolescent HL was associated with a positive family history (HR=1.20, 95%CI: 1.06-1.36), particularly early onset cancers (HR=1.30, 95%CI: 1.06-1.59) and those in the paternal lineage (HR=1.38, 95%CI: 1.16-1.65), with a suggested association for LN in first-degree relatives (HR=3.61, 95%CI: 0.87-15.01). There were no discernable patterns for EBV+ versus EBV– HL. The clustering of LN within pedigrees may signal shared genetic susceptibility or common environmental exposures. Heritable genetic risk variants have only recently begun to be discovered, however. These results are consistent with other studies and provide a compelling rationale for family-based studies to garner information about genetic susceptibility to HL.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Family history of cancer and risk of pediatric and adolescent Hodgkin lymphoma: A Children's Oncology Group study

Linabery

Erhardt

Richardson

et al. 2015

Intl Journal of Cancer

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“…8 Moreover, this study was the first to use a reconstructed cohort design and obtain data directly from relatives and spouses 8 , thereby reducing misclassification and enhancing power. 7,14,15 In summary, this study provides evidence of strong familial aggregation of insomnia. The main implication of these findings is that future studies should evaluate the impact of early prevention or intervention programs in preventing the development of insomnia among at-risk individuals.…”

Section: Limitations Strengths and Future Directionsmentioning

confidence: 54%

“…The risk of insomnia in relatives can then be estimated and compared between exposed and unexposed cohorts of relatives. 13 This design is deemed advantageous, as it yields unbiased risk estimates of a disease 14,15 and allows for the identification and assessment of disease risk factors (e.g., age of onset) in relatives and probands.…”

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confidence: 99%

Familial Aggregation of Insomnia

Jarrin

Morin

Rochefort

et al. 2016

Sleep

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Study Objectives: There is little information about familial aggregation of insomnia; however, this type of information is important to (1) improve our understanding of insomnia risk factors and (2) to design more effective treatment and prevention programs. This study aimed to investigate evidence of familial aggregation of insomnia among first-degree relatives of probands with and without insomnia. Methods: Cases (n = 134) and controls (n = 145) enrolled in a larger epidemiological study were solicited to invite their first-degree relatives and spouses to complete a standardized sleep/insomnia survey. In total, 371 first-degree relatives (M age = 51.9 years, SD = 18.0; 34.3% male) and 138 spouses (M age = 55.5 years, SD = 12.2; 68.1% male) completed the survey assessing the nature, severity, and frequency of sleep disturbances. The dependent variable was insomnia in first-degree relatives and spouses. Familial aggregation was claimed if the risk of insomnia was significantly higher in the exposed (relatives of cases) compared to the unexposed cohort (relatives of controls). The risk of insomnia was also compared between spouses in the exposed (spouses of cases) and unexposed cohort (spouses of controls). Results: The risk of insomnia in exposed and unexposed biological relatives was 18.6% and 10.4%, respectively, yielding a relative risk (RR) of 1.80 (p = .04) after controlling for age and sex. The risk of insomnia in exposed and unexposed spouses was 9.1% and 4.2%, respectively; however, corresponding RR of 2.13 (p = .28) did not differ significantly. Conclusions: Results demonstrate evidence of strong familial aggregation of insomnia. Additional research is warranted to further clarify and disentangle the relative contribution of genetic and environmental factors in insomnia.

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“…Also, no significant differences were observed between the two groups with regard to the degree of astigmatism in a study by Cagigrigoriu et al 11. On the other hand, case–control studies are associated with some degrees of bias 2728. Furthermore, a detailed discussion is presented on how to determine the proband when there is more than one proband in each group by Matthews et al 29.…”

Section: Discussionmentioning

confidence: 99%

Analysis of familial aggregation in total, against-the-rule, with-the-rule, and oblique astigmatism by conditional and marginal models in the Tehran eye study

Rakhshani

Mohammad

Zeraati

et al. 2012

Middle East Afr J Ophthalmol

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Purpose:The purpose was to determine the familial aggregation of the total, against-the-rule (ATR), with-the-rule (WTR), and oblique astigmatism by conditional and marginal models in the Tehran Eye Study.Materials and Methods:Total, ATR, WTR, and oblique astigmatism were studied in 3806 participants older than 5 years from August 2002 to December 2002 in the Tehran Eye Study. Astigmatism was defined as a cylinder worse than or equal to −0.5 D. WTR astigmatism was defined as 0 ± 19°, ATR astigmatism was defined as 90 ± 19°, and oblique when the axes were 20–70° and 110–160°. The familial aggregation was investigated with a conditional model (quadratic exponential) and marginal model (alternating logistic regression) after controlling for confounders.Results:Using the conditional model, the conditional familial aggregation odds ratios (OR) (95% confidence interval) for the total, WTR, ATRs, and oblique astigmatism were 1.49 (1.43–1.72), 1.91 (1.65–2.20), 2.00 (1.70–2.30), and 1.86 (1.37–2.54), respectively. In the marginal model, the marginal OR of the parent-offspring and sib-sib in the total astigmatism were 1.35 (1.13–1.63) and 1.54 (1.13–2.11), respectively; WTR 1.53 (1.06–2.20) and 1.94 (1.21–3.13) and; ATR 2.13 (1.01–4.50) and 2.23 (1.52-3.30). The model was statistically significant in sib-sib relationship only for oblique astigmatism with OR of 3.00 (1.25–7.20).Conclusion:The results indicate familial aggregation of astigmatism in the population in Tehran adjusted for age, gender, cataract, duration of education, and body mass index, so that the addition of a new family member affected with astigmatism, as well as having a sibling or parents with astigmatism, significantly increases the odds of exposure to the disease for all four phenotypes. This aggregation can be due to genetic and/or environmental factors. Dividing astigmatism into three phenotypes increased the odds ratios.

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Methods for Assessing Familial Aggregation: Family History Measures and Confounding in the Standard Cohort, Reconstructed Cohort and Case-Control Designs

Cited by 15 publications

References 10 publications

Family history of cancer and risk of pediatric and adolescent Hodgkin lymphoma: A Children's Oncology Group study

Family history of cancer and risk of pediatric and adolescent Hodgkin lymphoma: A Children's Oncology Group study

Familial Aggregation of Insomnia

Analysis of familial aggregation in total, against-the-rule, with-the-rule, and oblique astigmatism by conditional and marginal models in the Tehran eye study

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