Radio-biologically motivated modeling of radiation risks of mortality from ischemic heart diseases in the Canadian fluoroscopy cohort study.
Helmut SchöllnbergerJan Christian KaiserMarkus EidemüllerLydia B ZablotskaPublished in: Radiation and environmental biophysics (2019)
Recent analyses of the Canadian fluoroscopy cohort study reported significantly increased radiation risks of mortality from ischemic heart diseases (IHD) with a linear dose-response adjusted for dose fractionation. This cohort includes 63,707 tuberculosis patients from Canada who were exposed to low-to-moderate dose fractionated X-rays in 1930s-1950s and were followed-up for death from non-cancer causes during 1950-1987. In the current analysis, we scrutinized the assumption of linearity by analyzing a series of radio-biologically motivated nonlinear dose-response models to get a better understanding of the impact of radiation damage on IHD. The models were weighted according to their quality of fit and were then mathematically superposed applying the multi-model inference (MMI) technique. Our results indicated an essentially linear dose-response relationship for IHD mortality at low and medium doses and a supra-linear relationship at higher doses (> 1.5 Gy). At 5 Gy, the estimated radiation risks were fivefold higher compared to the linear no-threshold (LNT) model. This is the largest study of patients exposed to fractionated low-to-moderate doses of radiation. Our analyses confirm previously reported significantly increased radiation risks of IHD from doses similar to those from diagnostic radiation procedures.
Keyphrases
- cardiovascular events
- radiation induced
- human health
- heart failure
- risk factors
- end stage renal disease
- newly diagnosed
- small cell lung cancer
- oxidative stress
- ejection fraction
- cardiovascular disease
- mycobacterium tuberculosis
- high intensity
- squamous cell carcinoma
- magnetic resonance
- type diabetes
- magnetic resonance imaging
- chronic kidney disease
- hepatitis c virus
- quality improvement
- prognostic factors
- patient reported outcomes
- human immunodeficiency virus
- neural network
- drug induced