Improvements in diagnosis and changes in the diagnosis and treatment of elderly patients provide likely explanations for the observed patterns in brain cancer trends.
Background:There are few modifiable risk factors for Hodgkin lymphoma (HL), the most common cancer among young adults in Western populations. Some studies have found a reduced risk with exposure to ultraviolet radiation (UVR), but findings have been inconsistent and limited to HL as a group or the most common subtypes.Methods:We evaluated UVR and incidence of HL subtypes using data from 15 population-based cancer registries in the United States from 2001 to 2010 (n=20 021). Ground-based ambient UVR estimates were linked to county of diagnosis. Incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were calculated for UVR quintiles using Poisson regression models adjusted for age, sex, race/ethnicity, diagnosis year, and registry.Results:Hodgkin lymphoma incidence was lower in the highest UVR quintile for nodular sclerosis (IRR=0.84, 95% CI=0.75–0.96, P-trend<0.01), mixed cellularity/lymphocyte-depleted (IRR=0.66, 95% CI=0.51–0.86, P-trend=0.11), lymphocyte-rich (IRR=0.71, 95% CI=0.57–0.88, P-trend<0.01), and nodular lymphocyte predominant HL (IRR=0.74, 95% CI=0.56–0.97, P-trend<0.01), but ‘not otherwise specified' HL (IRR=1.19, 95% CI=0.96–1.47, P-trend=0.11).Conclusions:This is the largest study of UVR and HL subtypes covering a wide range of UVR levels; however, we lack information on personal UVR and other individual risk factors. These findings support an inverse association between UVR and HL.
In this paper, we describe recent methodological enhancements and findings from the dose reconstruction component of a study of cancer risks among U.S. radiologic technologists. An earlier version of the dosimetry published in 2006 (Simon et al., Radiat. Res. 166, 174-192, 2006) used physical and statistical models, literature-reported exposure measurements for the years before 1960, and archival personnel monitoring badge data from cohort members through 1984. The data and models were used to estimate unknown occupational radiation doses for 90,000 radiological technologists, incorporating information about each individual's employment practices based on a survey conducted in the mid-1980s. The dosimetry methods presented here, while using many of the same methods as before, now estimate annual and cumulative occupational badge doses (personal dose equivalent) to about 110,000 technologists for each year worked from 1916 to 2006, but with numerous methodological improvements. This dosimetry, using much more comprehensive information on individual use of protection aprons, estimates radiation absorbed doses to 12 organs and tissues (red bone marrow, ovary, colon, brain, lung, heart, female breast, skin of trunk, skin of head and neck and arms, testes, thyroid and lens of the eye). Every technologist's annual dose is estimated as a probability density function (pdf) to account for shared and unshared uncertainties. Major improvements in the dosimetry methods include a substantial increase in the number of cohort member annual badge dose measurements, additional information on individual apron use obtained from surveys conducted in the 1990s and 2005, refined modeling to develop annual badge dose pdfs using Tobit regression, refinements of cohort-based annual badge pdfs to delineate exposures of highly and minimally exposed individuals and to assess minimal detectable limits more accurately, and extensive refinements in organ dose conversion coefficients to account for uncertainties in radiographic techniques employed. For organ dose estimation, we rely on well-researched assumptions about critical exposure-related variables and their changes over the decades, including the peak kilovoltage and filtration typically used in conducting radiographic examinations and the usual body location for wearing radiation monitoring badges. We have derived organ dose conversion coefficients based on air-kerma weighting of photon fluences from published X-ray spectra and derived energy-dependent transmission factors for protective aprons of different thicknesses. We tailor bone marrow dose estimates to individual cohort members by using an individual-specific body mass index correction factor. To our knowledge the models and reconstructed doses presented herein represent the most comprehensive dose reconstructions undertaken for a cohort of medical radiation workers.
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