Investigations of familial aggregation of disease can provide important clues for genetic mechanisms, and many such studies have been published in the epidemiological literature using various statistical methods. We developed a unified model for familial risk by extending a Cox regression model to enable estimation of the detailed effects of kinship. By appropriate parameterisation of the model, we show how the risks to all specific first-degree kinships can be estimated and formally compared using simple interaction terms and how the model can be extended to accommodate higher-degree relatives. The correlation due to observations from family members and from the potential for repeated observations is accommodated by a robust sandwich variance estimator or a bootstrap estimate. Hazard ratios for different kinships are formally compared using a robust Wald test. We illustrate the method with applications to studies of adult leukemia and non-Hodgkin's lymphoma in the Swedish population and display our results on a pedigree diagram. Our estimates are consistent with published work that used simpler stratified methods, and our model enabled the detection of a number of statistically significant effects of kinship. The recognition of such kindred-specific disease risk could be a first step in the design of more informative genetic biomarker studies. © 2013 John Wiley & Sons, Ltd.

Lee, M., Rebora, P., Valsecchi, M., Czene, K., Reilly, M. (2013). A unified model for estimating and testing familial aggregation. STATISTICS IN MEDICINE, 32(30), 5353-5365 [10.1002/sim.6025].

A unified model for estimating and testing familial aggregation

REBORA, PAOLA;VALSECCHI, MARIA GRAZIA;
2013

Abstract

Investigations of familial aggregation of disease can provide important clues for genetic mechanisms, and many such studies have been published in the epidemiological literature using various statistical methods. We developed a unified model for familial risk by extending a Cox regression model to enable estimation of the detailed effects of kinship. By appropriate parameterisation of the model, we show how the risks to all specific first-degree kinships can be estimated and formally compared using simple interaction terms and how the model can be extended to accommodate higher-degree relatives. The correlation due to observations from family members and from the potential for repeated observations is accommodated by a robust sandwich variance estimator or a bootstrap estimate. Hazard ratios for different kinships are formally compared using a robust Wald test. We illustrate the method with applications to studies of adult leukemia and non-Hodgkin's lymphoma in the Swedish population and display our results on a pedigree diagram. Our estimates are consistent with published work that used simpler stratified methods, and our model enabled the detection of a number of statistically significant effects of kinship. The recognition of such kindred-specific disease risk could be a first step in the design of more informative genetic biomarker studies. © 2013 John Wiley & Sons, Ltd.
Articolo in rivista - Articolo scientifico
bootstrap, kindred-specific risk, leukemia, non-Hodgkin's lymphoma, robust sandwich variance, survival analysis
English
30-dic-2013
32
30
5353
5365
none
Lee, M., Rebora, P., Valsecchi, M., Czene, K., Reilly, M. (2013). A unified model for estimating and testing familial aggregation. STATISTICS IN MEDICINE, 32(30), 5353-5365 [10.1002/sim.6025].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/51994
Citazioni
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
Social impact