Browsing by Author "Peters S"

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    Heirarchical regression for multiple comparisons in a case-control study of occupational risks for lung cancer.
    (Public Library of Science, 11/06/2012) Corbin M; Richiardi L; Vermeulen R; Kromhout H; Merletti F; Peters S; Simonato L; Steenland K; Pearce NE; Maule M
    Background Occupational studies often involve multiple comparisons and therefore suffer from false positive findings. Semi-Bayes adjustment methods have sometimes been used to address this issue. Hierarchical regression is a more general approach, including Semi-Bayes adjustment as a special case, that aims at improving the validity of standard maximum-likelihood estimates in the presence of multiple comparisons by incorporating similarities between the exposures of interest in a second-stage model. Methodology/Principal Findings We re-analysed data from an occupational case-control study of lung cancer, applying hierarchical regression. In the second-stage model, we included the exposure to three known lung carcinogens (asbestos, chromium and silica) for each occupation, under the assumption that occupations entailing similar carcinogenic exposures are associated with similar risks of lung cancer. Hierarchical regression estimates had smaller confidence intervals than maximum-likelihood estimates. The shrinkage toward the null was stronger for extreme, less stable estimates (e.g., “specialised farmers”: maximum-likelihood OR: 3.44, 95%CI 0.90–13.17; hierarchical regression OR: 1.53, 95%CI 0.63–3.68). Unlike Semi-Bayes adjustment toward the global mean, hierarchical regression did not shrink all the ORs towards the null (e.g., “Metal smelting, converting and refining furnacemen”: maximum-likelihood OR: 1.07, Semi-Bayes OR: 1.06, hierarchical regression OR: 1.26). Conclusions/Significance Hierarchical regression could be a valuable tool in occupational studies in which disease risk is estimated for a large amount of occupations when we have information available on the key carcinogenic exposures involved in each occupation. With the constant progress in exposure assessment methods in occupational settings and the availability of Job Exposure Matrices, it should become easier to apply this approach.
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    Lung cancer risk in painters: results from the SYNERGY pooled case-control study consortium
    (BMJ Publishing Group Ltd, 2021-04) Guha N; Bouaoun L; Kromhout H; Vermeulen R; Brüning T; Behrens T; Peters S; Luzon V; Siemiatycki J; Xu M; Kendzia B; Guenel P; Luce D; Karrasch S; Wichmann H-E; Consonni D; Landi MT; Caporaso NE; Gustavsson P; Plato N; Merletti F; Mirabelli D; Richiardi L; Jöckel K-H; Ahrens W; Pohlabeln H; TSE LA; Yu IT-S; Tardón A; Boffetta P; Zaridze D; 't Mannetje A; Pearce N; Davies MPA; Lissowska J; Świątkowska B; McLaughlin J; Demers PA; Bencko V; Foretova L; Janout V; Pándics T; Fabianova E; Mates D; Forastiere F; Bueno-de-Mesquita B; Schüz J; Straif K; Olsson A
    OBJECTIVES: We evaluated the risk of lung cancer associated with ever working as a painter, duration of employment and type of painter by histological subtype as well as joint effects with smoking, within the SYNERGY project. METHODS: Data were pooled from 16 participating case-control studies conducted internationally. Detailed individual occupational and smoking histories were available for 19 369 lung cancer cases (684 ever employed as painters) and 23 674 age-matched and sex-matched controls (532 painters). Multivariable unconditional logistic regression models were adjusted for age, sex, centre, cigarette pack-years, time-since-smoking cessation and lifetime work in other jobs that entailed exposure to lung carcinogens. RESULTS: Ever having worked as a painter was associated with an increased risk of lung cancer in men (OR 1.30; 95% CI 1.13 to 1.50). The association was strongest for construction and repair painters and the risk was elevated for all histological subtypes, although more evident for small cell and squamous cell lung cancer than for adenocarcinoma and large cell carcinoma. There was evidence of interaction on the additive scale between smoking and employment as a painter (relative excess risk due to interaction >0). CONCLUSIONS: Our results by type/industry of painter may aid future identification of causative agents or exposure scenarios to develop evidence-based practices for reducing harmful exposures in painters.