A regression model for risk difference estimation in population-based case-control studies clarifies gender differences in lung cancer risk of smokers and never smokers

Stephanie A. Kovalchik, Sara De Matteis, Maria Teresa Landi, Neil E. Caporaso, Ravi Varadhan, Dario Consonni, Andrew W. Bergen, Hormuzd A. Katki, Sholom Wacholder

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Background: Additive risk models are necessary for understanding the joint effects of exposures on individual and population disease risk. Yet technical challenges have limited the consideration of additive risk models in case-control studies. Methods. Using a flexible risk regression model that allows additive and multiplicative components to estimate absolute risks and risk differences, we report a new analysis of data from the population-based case-control Environment And Genetics in Lung cancer Etiology study, conducted in Northern Italy between 2002-2005. The analysis provides estimates of the gender-specific absolute risk (cumulative risk) for non-smoking-and smoking-associated lung cancer, adjusted for demographic, occupational, and smoking history variables. Results: In the multiple-variable lexpit regression, the adjusted 3-year absolute risk of lung cancer in never smokers was 4.6 per 100,000 persons higher in women than men. However, the absolute increase in 3-year risk of lung cancer for every 10 additional pack-years smoked was less for women than men, 13.6 versus 52.9 per 100,000 persons. Conclusions: In a Northern Italian population, the absolute risk of lung cancer among never smokers is higher in women than men but among smokers is lower in women than men. Lexpit regression is a novel approach to additive-multiplicative risk modeling that can contribute to clearer interpretation of population-based case-control studies.

Original languageEnglish
Article number143
JournalBMC Medical Research Methodology
Volume13
Issue number1
DOIs
Publication statusPublished - 2013

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Case-Control Studies
Lung Neoplasms
Population
Smoking
Italy
History
Demography

Keywords

  • Absolute risk
  • Additive risk
  • Case-control study
  • EAGLE
  • Lung cancer
  • Risk assessment
  • Sex factors
  • Smoking

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics

Cite this

A regression model for risk difference estimation in population-based case-control studies clarifies gender differences in lung cancer risk of smokers and never smokers. / Kovalchik, Stephanie A.; De Matteis, Sara; Landi, Maria Teresa; Caporaso, Neil E.; Varadhan, Ravi; Consonni, Dario; Bergen, Andrew W.; Katki, Hormuzd A.; Wacholder, Sholom.

In: BMC Medical Research Methodology, Vol. 13, No. 1, 143, 2013.

Research output: Contribution to journalArticle

Kovalchik, Stephanie A. ; De Matteis, Sara ; Landi, Maria Teresa ; Caporaso, Neil E. ; Varadhan, Ravi ; Consonni, Dario ; Bergen, Andrew W. ; Katki, Hormuzd A. ; Wacholder, Sholom. / A regression model for risk difference estimation in population-based case-control studies clarifies gender differences in lung cancer risk of smokers and never smokers. In: BMC Medical Research Methodology. 2013 ; Vol. 13, No. 1.
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