Quantitative Bias Analysis of the Association between Occupational Radiation Exposure and Ischemic Heart Disease Mortality in UK Nuclear Workers

• Published in: Radiation research Vol. 196; no. 6; pp. 574 - 586
• Main Authors: de Vocht, Frank, Martin, Richard M, Hidajat, Mira, Wakeford, Richard
• Format: Journal Article
• Language: English
• Published: United States Radiation Research Society 01-12-2021
• Subjects: Bias; Cohort Studies; Confounding Factors, Epidemiologic; Dose-Response Relationship, Radiation; England - epidemiology; Humans; Monte Carlo Method; Myocardial Ischemia - etiology; Myocardial Ischemia - mortality; Nuclear Power Plants; Occupational Exposure; Radiation Exposure; Radiometry; REGULAR ARTICLE; Tobacco Smoking; England
• ISSN: 0033-7587; 1938-5404
• DOI: 10.1667/RADE-21-00078.1

The scientific question of whether protracted low-dose or low-dose-rate exposure to external radiation is causally related to the risk of circulatory disease continues to be an important issue for radiation protection. Previous analyses of a matched case-control dataset nested in a large cohort of UK nuclear fuel cycle workers indicated that there was little evidence that observed associations between external radiation dose and ischemic heart disease (IHD) mortality risk [OR = 1.35 (95% CI: 0.99–1.84) for 15-year-lagged exposure] could alternatively be explained by confounding from pre-employment tobacco smoking, BMI or blood pressure, or from socioeconomic status or occupational exposure to excessive noise or shiftwork. To improve causal inference about the observed external radiation dose and IHD mortality association, we estimated the potential magnitude and direction of non-random errors, incorporated sensitivity analyses and simulated bias effects under plausible scenarios. We conducted quantitative bias analyses of plausible scenarios based on 1,000 Monte Carlo samples to explore the impact of exposure measurement error, missing information on tobacco smoking, and unmeasured confounding, and assessed whether observed associations were reliant on the inclusion of specific matched pairs using bootstrapping with 10% of matched pairs randomly excluded in 1,000 samples. We further explored the plausibility that having been monitored for internal exposure, which was an important confounding factor in the case-control analysis for which models were adjusted, was indeed a confounding factor or whether it might have been the result of some form of selection bias. Consistent with the broader epidemiological evidence-base, these analyses provide further evidence that the dose-response association between cumulative external radiation exposure and IHD mortality is non-linear in that it has a linear shape plateauing at an excess risk of 43% (95% CI: 7–92%) on reaching 390 mSv. Analyses of plausible scenarios of patterns of missing data for tobacco smoking at start of employment indicated that this resulted in relatively little bias towards the null in the original analysis. An unmeasured confounder would have had to have been highly correlated (rp > 0.60) with cumulative external radiation dose to importantly bias observed associations. The confounding effect of “having been monitored for internal dose” was unlikely to have been a true confounder in a biological sense, but instead may have been some unknown factor related to differences over time and between sites in selection criteria for internal monitoring, possibly resulting in collider bias. Plausible patterns of exposure measurement error negatively biased associations regardless of the modeled scenario, but did not importantly change the shape of the observed dose-response associations. These analyses provide additional support for the hypothesis that the observed association between external radiation exposure and IHD mortality may be causal.