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The association of active smoking with multiple cancers: National census-cancer registry cohorts with quantitative bias analysis

机译:主动吸烟与多种癌症的关系:国家人口普查癌症登记人群与定量偏倚分析

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Purposes (1) Determine the association of multiple cancers with smoking, focusing on cancers with an uncertain association; and (2) illustrate quantitative bias analysis as applied to registry data, to adjust for misclassification of smoking and residual confounding by alcohol and obesity. Methods New Zealand 1981 and 1996 censuses, including smoking questions, were linked to cancer registry data giving 14.8 million person-years of follow-up. Rate ratios (RR) for current versus never smokers, adjusting for age, sex, ethnicity and socioeconomic factors were calculated and then subjected to quantitative bias analysis. Results RR estimates for lung, larynx (including ear and nasosinus), and bladder cancers adjusted for measured confounders and exposure misclassification were 9.28 (95 % uncertainty interval 8.31-10.4), 6.14 (4.55-8.30), and 2.22 (1.94-2.55), respectively. Moderate associations were found for cervical (1.82; 1.51-2.20), kidney (1.29; 1.07-1.56), liver cancer (1.75; 1.37-2.24; European only), esophageal (2.14; 1.73-2.65), oropharyngeal (2.30; 1.94-2.72), pancreatic (1.68; 1.44-1.96), and stomach cancers (1.42; 1.22-1.66). Protective associations were found for endometrial (0.67; 0.56-0.79) and melanoma (0.72; 0.65-0.81), and borderline association for thyroid (0.76; 0.58-1.00), colon (0.89; 0.81-0.98), and CML (0.66; 0.44-0.99). Remaining cancers had near null associations. Adjustment for residual confounding suggested little impact, except the RRs for endometrial, kidney, and esophageal cancers were slightly increased, and the oropharyngeal and liver (European/other) RRs were decreased. Conclusions Our large study confirms the strong association of smokingwithmany cancers and strengthens the evidence for protective associations with thyroid cancer and melanoma. With large data sets, considering and adjusting for residual systematic error is as important as quantifying random error
机译:目的(1)确定多种癌症与吸烟的关系,重点是不确定性的癌症; (2)说明应用于注册表数据的定量偏差分析,以调整吸烟的误分类以及酒精和肥胖引起的残留混杂。方法将新西兰1981年和1996年的人口普查(包括吸烟问题)与癌症登记数据联系起来,进行1480万人年的随访。计算年龄,性别,种族和社会经济因素的当前吸烟者和从未吸烟者的比率(RR),然后进行定量偏差分析。结果经校正的混杂因素和暴露分类错误,肺癌,喉癌(包括耳和鼻窦)和膀胱癌的RR估计值分别为9.28(95%不确定区间8.31-10.4),6.14(4.55-8.30)和2.22(1.94-2.55) , 分别。宫颈癌(1.82; 1.51-2.20),肾癌(1.29; 1.07-1.56),肝癌(1.75; 1.37-2.24;仅欧洲),食道癌(2.14; 1.73-2.65),口咽癌(2.30; 1.94)有中等程度的关联。 -2.72),胰腺癌(1.68; 1.44-1.96)和胃癌(1.42; 1.22-1.66)。发现子宫内膜(0.67; 0.56-0.79)和黑色素瘤(0.72; 0.65-0.81)的保护性关联,甲状腺(0.76; 0.58-1.00),结肠(0.89; 0.81-0.98)和CML(0.66; 0.44-0.99)。其余的癌症几乎没有关联。残余混杂的调整几乎没有影响,除了子宫内膜癌,肾癌和食管癌的RR略有增加,口咽和肝脏(欧洲/其他)的RR有所降低。结论我们的大型研究证实了吸烟与多种癌症之间的密切联系,并加强了与甲状腺癌和黑色素瘤之间的保护性联系的证据。对于大数据集,考虑和调整残余系统误差与量化随机误差同等重要

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