Abstract

Abstract Purpose: Cancer mortality is estimated using underlying cause of death. For instance, to estimate the risk of head and neck cancer (HNC) mortality attributed to smoking, ‘death by HNC’ is the outcome (ie, smoking → HNC death). This conventional approach has notable flaws. It relies on accurate reporting on cause of death, a potential source of misclassification, and it excludes any mortality effects in cancer patients who die from other causes, a potential source of selection bias. Regarding HNC, 80% of all patients are excluded using this approach. These potential biases may result in underestimating cancer mortality from important public health factors such as smoking, obesity and physical activity. To overcome these biases, we are proposing a new approach to estimate cancer mortality. The method uses a causal mediation model and we demonstrate it in a smoking and HNC example. Methods: The model estimates cancer mortality through a mediated pathway. In our example, smoking is the exposure, incident HNC is the mediator, and all-cause mortality is the outcome (smoking → HNC incidence → all deaths). The mediated effect is the risk of mortality attributed to HNC, which in turn, is attributed to smoking. We compare the results in the mediation model to the conventional approach using Aalen’s additive hazards, which estimates the absolute increase in deaths in smokers compared to non-smokers; the mediation model also uses logistic regression for the HNC mediator. Both models are adjusted for age, sex, race, body mass index, diet, alcohol use, physical activity, marital status, education, and reported health. We used the NIH-AARP Diet and Health cohort, which has smoking information at baseline, and cancer incidence and mortality during follow-up on 518,100 U.S. subjects. Results: In the study, 2,279 subjects developed HNC during follow-up, among whom, 508 (22%) died from HNC; 125,442 subjects died from any cause. Under the conventional method, 11.0 more deaths (per 100,000 person-years) are attributed to HNC from current smokers relative to never smokers (95% CI: 8.0, 13.9); 1.8 deaths in former smokers (95% CI: 0.4, 3.2). Under the mediation method, 13.4 more deaths are attributed to HNC from current smokers relative to never smokers (95% CI: 9.3, 16.8); 2.2 deaths in former smokers (95% CI: 1.2, 3.4). Comparing the two estimates, the conventional approach underestimates HNC mortality attributed to smoking by 18%. Noteworthy, the underestimate for current smokers manifests primarily in men, while the underestimate for former smokers manifests primarily in women. Conclusions: The mediation method overcomes limitations in prior approaches of cancer mortality. In our example, the method estimated a stronger effect on HNC mortality by smoking. Further study is warranted as published estimates of cancer mortality by notable public health risk factors (eg, smoking, obesity, physical activity) may be underestimating their impact. Citation Format: Ronald C. Eldridge, W. Dana Flanders, Colin Adler, Deborah W. Bruner, Canhua Xiao. Are we underestimating cancer mortality? A mediation model shows a larger impact from smoking [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2418.

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