ArticleBMC medical research methodology2013
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.
Article in BMC medical research methodology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prediction models for early detection and diagnosis of lung cancer in people who have never smoked: a systematic review and critical appraisal.Cancer causes & control : CCC · 2026Pooled it
- Lung cancer screening: who pays? Who receives? The European perspectives.Translational lung cancer research · 2021Review
- Differences in the clinical management of women and men after detection of a solitary pulmonary nodule in clinical practice.European radiology · 2020Article
- The Relevance of Gender in Tumor-Influencing Epigenetic Traits.Epigenomes · 2019Review
- Implications of Nine Risk Prediction Models for Selecting Ever-Smokers for Computed Tomography Lung Cancer Screening.Annals of internal medicine · 2018Article
- Article
- Using group data to treat individuals: understanding heterogeneous treatment effects in the age of precision medicine and patient-centred evidence.International journal of epidemiology · 2016Article
- Hormone Use, Reproductive History, and Risk of Lung Cancer: The Women's Health Initiative Studies.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2015Article
- Time to smoke first morning cigarette and lung cancer in a case-control study.Journal of the National Cancer Institute · 2014Article
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9 authors.
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Abstract
backgroundAdditive 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.
methodsUsing 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.
resultsIn 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.
conclusionsIn 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.
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