• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.323-335
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• 2016

Breast cancer risk assessment has developed during years and evaluation of genetic factor affecting risk of breast cancer is an important component of this risk assessment. The aim of this meta-analysis was to investigate the role of XRCC1 polymorphisms (Arg194Trp, Arg280His and Arg399Gln) in risk of breast cancer among different population and categories of menopausal status.PubMed, Medline, Web of Science, and PubMed Central were systematically searched to identify studies evaluating association between breast cancer and XRCC1 gene polymorphisms (Arg194Trp, Arg280His and Arg399Gln). Two authors independently extracted required information. Odds Ratios were pooled for four genetic inheritance models using both fixed and the DerSimonian and Laird random-effect models. Egger's test and contour-enhanced funnel plot was used to evaluate publication bias and small study effect. Additional subgroup analysis was performed for menopausal status, ethnicity, and source of controls. After evaluation and applying inclusion criteria on extracted studies, fifty three studies were included in this meta-analysis. For polymorphisms of Arg194Trp and Arg280His, no significant association was observed in all genetic models. Arg194Trp had a protective effect in post-menopausal status only in homozygote model (OR=0.57 [0.37-0.88]). Arg399Gln showed significant association with breast cancer in homozygote (OR=1.21 [1.10-1.34]), dominant (OR=1.09 [1.03-1.15]) and recessive (OR=1.21 [1.09- 1.35]) genetic models. Arg399Gln was associated with higher risk in post-menopausal status for homozygote and heterozygote models. Our findings suggest that XRCC1 gene polymorphisms modify breast cancer risk in different populations and different categories of menopausal status.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2713-2717
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• 2015

Background: Possible associations between the single nucleotide polymorphism (SNP) rs8034191 in the aminoglycosidephosphotransferase domain containing 1 (AGPHD1) gene and lung cancer risk have been studied by many researchers but the results have been contradictory. Materials and Methods: A computerized search for publications on rs8034191 and lung cancer risk was performed. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess the association between rs8034191 and lung cancer risk with 13 selected case-control studies. Sensitivity analysis, test of heterogeneity, cumulative meta-analysis, and assessment of bias were also performed. Results: A significant association between rs8034191 and lung cancer susceptibility was found using the dominant genetic model (OR=1.344, 95% CI: 1.285-1.406), the additive genetic model (OR=1.613, 95% CI: 1.503-1.730), and the recessive genetic model (OR=1.408, 95% CI: 1.319-1.503). Moreover, an increased lung cancer risk was found with all genetic models after stratification of ethnicity. Conclusions: The association between rs8034191 and lung cancer risk was significant using multiple genetic models, suggesting that rs8034191 is a risk factor for lung cancer. Further functional studies of this polymorphism and lung cancer risk are warranted.

• Journal of Radiation Protection and Research
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• v.48 no.2
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• pp.90-99
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• 2023

Background: Quantitative risk assessments should be accompanied by uncertainty analyses of the risk models employed in the calculations. In this study, we aim to develop a computational code named SUMRAY for use in cancer risk projections from radiation exposure taking into account uncertainties. We also aim to make SUMRAY publicly available as a resource for further improvement of risk projection. Materials and Methods: SUMRAY has two versions of code written in R and Python. The risk models used in SUMRAY for all-solid-cancer mortality and incidence were those published in the Life Span Study of a cohort of the atomic bomb survivors in Hiroshima and Nagasaki. The confidence intervals associated with the evaluated risks were derived by propagating the statistical uncertainties in the risk model parameter estimates by the Monte Carlo method. Results and Discussion: SUMRAY was used to calculate the lifetime or time-integrated attributable risks of cancer under an exposure scenario (baseline rates, dose[s], age[s] at exposure, age at the end of follow-up, sex) specified by the user. The results were compared with those calculated using another well-known web-based tool, Radiation Risk Assessment Tool (RadRAT; National Institutes of Health), and showed a reasonable agreement within the estimated confidential interval. Compared with RadRAT, SUMRAY can be used for a wide range of applications, as it allows the risk projection with arbitrarily specified risk models and/or population reference data. Conclusion: The reliabilities of SUMRAY with the present risk-model parameters and their variance-covariance matrices were verified by comparing them with those of the other codes. The SUMRAY code is distributed to the public as an open-source code under the Massachusetts Institute of Technology license.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.450-468
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• 1994

Scientists have long used conventional toxicological methods to establish 'safe levels of exposure' for chemicals presumed to have threshold health effects or doses below which significant effects are unlikely to occur. These same methods cannot be used to establish safe levels of exposure for non-threshold pollutants. such as carcinogens. Therefore. Federal regulatory agencies in the United States are using risk assessment methods to provide information for public health policy decisions concerning increases in risk associated with increases in exposure to carcinogenic and other non-threshold pollutants. Acceptable exposure/risk levels are decided by policymakers who consider descriptions and estimates of risks together with social and economic benefits from the uses of the chemical. 1bis paper focuses on the development of quantitative risk assessment approaches by Federal regulatory agencies in the United States, and identifies the mathematical models currently being used for risk extrapolation. including their inherent uncertainties. The uncertainties and limitations of these methods have led some scientists to question the utility of quantitative risk extrapolation. The experience of the; U.S. Environmental Protection Agency (EPA). as summarized in this paper. can provide a realistic basis for evaluating the pros and cons. Finally. shortcomings in current risk assessment methods and their use in policy decisions are explored. and areas for possible improvement. given current scientific knowledge. are identified.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6811-6817
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• 2014

Background: Breast cancer risk prediction models are widely used in clinical practice. They should be useful in identifying high risk women for screening in limited-resource countries. However, previous models showed poor performance in derived and validated settings. Therefore, we aimed to develop and validate a breast cancer risk prediction model for Thai women. Materials and Methods: This cross-sectional study consisted of derived and validation phases. Data collected at Ramathibodi and other two hospitals were used for deriving and externally validating models, respectively. Multiple logistic regression was applied to construct the model. Calibration and discrimination performances were assessed using the observed/expected ratio and concordance statistic (C-statistic), respectively. A bootstrap with 200 repetitions was applied for internal validation. Results: Age, menopausal status, body mass index, and use of oral contraceptives were significantly associated with breast cancer and were included in the model. Observed/expected ratio and C-statistic were 1.00 (95% CI: 0.82, 1.21) and 0.651 (95% CI: 0.595, 0.707), respectively. Internal validation showed good performance with a bias of 0.010 (95% CI: 0.002, 0.018) and C-statistic of 0.646(95% CI: 0.642, 0.650). The observed/expected ratio and C-statistic from external validation were 0.97 (95% CI: 0.68, 1.35) and 0.609 (95% CI: 0.511, 0.706), respectively. Risk scores were created and was stratified as low (0-0.86), low-intermediate (0.87-1.14), intermediate-high (1.15-1.52), and high-risk (1.53-3.40) groups. Conclusions: A Thai breast cancer risk prediction model was created with good calibration and fair discrimination performance. Risk stratification should aid to prioritize high risk women to receive an organized breast cancer screening program in Thailand and other limited-resource countries.

• Journal of Food Hygiene and Safety
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• v.15 no.3
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• pp.267-270
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• 2000

This study was designed to predict the risk of a hazard chemical, vinyl chloride, by applying dose-response assessment that are one of the major process in practicing risk assessment. After extrapolating from the high dose exposure of vinyl chloride based upon animal carcinogenic data to the low dose exposed to human using several mathematical models, we calculated the cancer potency factors as well as virtually safe dose and the resulted values were compared. This process will provide the new insight to assess the risk of a chemical accurately imposed to human in the future.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.581-598
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• 2006

In many epidemiological and medical studies, a number of cancer mortalities in categorical classification may be considered as having Poisson distribution with person-years at risk depending upon time. The cancer mortalities have been evaluated by additive or multiplicative models with regard to background and excess risks based on several covariances such as sex, age at the time of bombings, time at exposure, or ionizing radiation, cigarette smoking habits, duration of smoking habits, etc. An interest herein is to examine an additive, synergistic, or antagonistic relationship between radiation exposures and cigarette smoking habits for cancer mortalities. The results revealed a highly significant antagonistic in uence for cancer mortalities from all non-hematologic findings, lung and respiratory system with negative interaction between radiation exposures and cigarette smoking amounts.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3937-3942
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• 2012

Background: Many studies have investigated possible association between the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism and ovarian cancer risk, but the impact is still unclear owing to the obvious inconsistencies. This study was performed to quantify the strength of the association with a metaanalysis. Methods: We searched the PubMed, Embase, and CNKI databases for studies relating the association between MTHFR C677T polymorphism and ovarian cancer risk and estimated summary odds ratios (ORs) with confidence intervals (CIs) for assessment. Results: Finally, eight studies with a total of 3,379 ovarian cancer cases and 4,078 controls were included into this meta-analysis. Overall the showed that MTHFR C677T polymorphism was not associated with ovarian cancer risk under all genetic models ($OR_{T\;versus\;C}$ = 1.03, 95%CI 0.90-1.18; $OR_{TT\;versus\;CC}$ = 1.08, 95%CI 0.79-1.47; $OR_{TT\;versus\;TC+CC}$ = 1.05, 95%CI 0.80-1.37; $OR_{TT+TC\;versus\;CC}$ = 1.05, 95%CI 0.86-1.21). Meta-analyses of studies with confirmation of HWE also showed no significant association. Subgroup analyses by ethnicity showed there was no significant association in the Caucasians but MTHFR C677T polymorphic variant T contributed to increased risk of ovarian cancer in East Asians. No evidence of publication bias was observed. Conclusion: Meta-analyses of available data show that MTHFR C677T polymorphism is not associated with ovarian cancer risk in Caucasians, but the MTHFR polymorphic variant T may contribute to increased risk in East Asians.

• Safety and Health at Work
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• v.7 no.3
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• pp.251-255
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• 2016

Background: Building demolition can lead to emission of dust into the environment. Exposure to silica dust may be considered as an important hazard in these sites. The objectives of this research were to determine the amount of workers' exposure to crystalline silica dust and assess the relative risk of silicosis and the excess lifetime risk of mortality from lung cancer in demolition workers. Methods: Four sites in the Tehran megacity region were selected. Silica dust was collected using the National Institute for Occupational Safety and Health method 7601 and determined spectrophotometrically. The Mannetje et al and Rice et al models were chosen to examine the rate of silicosis-related mortality and the excess lifetime risk of mortality from lung cancer, respectively. Results: The amount of demolition workers' exposure was in the range of $0.085-0.185mg/m^3$. The range of relative risk of silicosis related mortality was increased from 1 in the workers with the lowest exposure level to 22.64/1,000 in the employees with high exposure level. The range of the excess lifetime risk of mortality from lung cancer was in the range of 32-60/1,000 exposed workers. Conclusion: Geometric and arithmetic mean of exposure was higher than threshold limit value for silica dust in all demolition sites. The risk of silicosis mortality for many demolition workers was higher than 1/1,000 (unacceptable level of risk). Estimating the lifetime lung cancer mortality showed a higher risk of mortality from lung cancer in building demolition workers.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2853-2856
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• 2012

Background: Previous studies assessing associations between matrix metalloproteinase 2 (MMP-2) polymorphisms and lung cancer risk reported conflicting results. A meta-analysis was therefore performed to derive a more precise estimation. Method: Case-control studies assessing associations between MMP-2 C735T and C1306T polymorphisms and lung cancer risk were included. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. Results: 7 studies with a total of 3,189 lung cancer cases and 3,013 controls were finally included into this meta-analysis. Overall, the MMP-2 C735T polymorphism was associated with lung cancer risk under the homozygote model (CC versus TT: OR =1.44, 95% CI = 1.03-2.02, $I^2$ = 0%), while the MMP-2 C1306T polymorphism also associated demonstrated links with all four models (all P values less than 0.05). Subgroup analyses by race suggested obvious associations between MMP-2 C735T and C1306T polymorphisms and lung cancer risk in Asians but not in Caucasians. There was no evidence for publication bias. Conclusion: Currently available evidence supports teh conclusion that MMP-2 C735T and C1306T polymorphisms influence susceptibility to lung cancer in Asians.