• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1759-1764
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• 2015

Purpose: To establish the concept of lung cancer hazard assessment theoretical models, evaluating the degree of lung cancer risk of Beijing for regional population lung cancer hazard assessment to provide a basis for technical support. Materials and Methods: ISO standards were used to classify stratified analysis for the entire population, life cycle, processes and socioeconomic management. Associated risk factors were evaluated as lung cancer hazard risk assessment first class indicators. Study design: Using the above materials, indicators were given the weight coefficients, building lung cancer risk assessment theoretical models. Regional data for Beijing were entered into the theoretical model to calculate the parameters of each indicator and evaluate the degree of local lung cancer risk. Results: Adopting the concept of lung cancer hazard assessment and theoretical models for regional populations, we established a lung cancer hazard risk assessment system, including 2 first indicators, 8 secondary indicators and 18 third indicators. All indicators were given weight coefficients and used as information sources. Score of hazard for lung cancer was 84.4 in Beijing. Conclusions: Comprehensively and systematically building a lung cancer risk assessment theoretical model for regional populations in conceivable, evaluating the degree of lung cancer risk of Beijing, providing technical support and scientific basis for interventions for prevention.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1737-1742
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• 2013

Early diagnosis has a major role in improving prognosis of breast cancer. The purpose of this study was to assess the risk status of women 35-69 years of age using risk assessment models and the prevalence of mammography in a community setting. The sample of this cross sectional study consisted of 227 women, 35-69 years of age residing in Izmir, a city located in western region of Turkey. A questionnaire was used to collect data and the Gail and Cuzick-Tyrer models were applied to assess the risk of breast cancer. In this study, 52.7% of women had mammography at least once, and 41.3% of the women over the age of 40 had mammography screening in the last two years. The five years risk for breast cancer was high in 15.8% of women according to the Gail model and ten years risk was high in 21.7% with the Cuzick-Tyrer model. In the present study, the breast cancer risk levels were assessed in a population setting for the first time in Turkey using breast cancer risk level assessment models. Being in 60-69 age group, having low education and not being in menopause were significant risk factors for not having mammography according to logistic regression analysis. Mammography utilization rate was low. Women must be educated about breast cancer screening methods and early diagnosis. The women in the high risk group should be informed on their risk status which may increase their attendance at breast cancer screening.

• Environmental Mutagens and Carcinogens
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• v.19 no.2
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• pp.95-101
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• 1999

Risk Assessment is an important area in toxicology and the methodology for risk assessment has been developed. Mathematical models used for risk assessment include one-hit multi-hit, two-stage, probit logistic, multistage, and linearized multistage models. For the assessment of exposure dose, environmental monitoring has been applied, but it has limitation to accurately assess exposure level because the levels in the air, water, foods, and soil may vary depending on time of sampling. In addition, humans can be exposed to various sources of exposure and thus it will be impossible to estimate the total level of exposure in humans by environmental monitoring. To eliminate the limitation of environmental monitoring, a direct measurement of toxic materials or modified biomolecules (called biomarkers) associated with the exposure of toxic materials is needed. Here, scientific basis of biomarkers and future direction have been considered for the assessment of carcinogen exposure and cancer risk in humans.

• Toxicological Research
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• v.8 no.2
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• pp.317-329
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• 1992

Fifty chemicals are currently classified as human carcinogens based on epidemiologic and animal data. Humans are daily exposed to them from various sources of exposure via inhalation, dermal contact and oral ingestion. To reduce cancer risk to man, these human carcinogens should be appropriately regulated and monitored environmentally or biologically for routine human cancer risk assessment. A number of mathematical risk assessment models have been introduced, but any realistic and relevant model system is not available for humans. A mechanistic process for human cancer risk assessment was comprehensively reviewed and problems were also discussed. Here, a new conceptual approach using epidemiology and biological human monitoring was suggested for the most relevant method to study human cancer risk assessment.

• Journal of Radiation Protection and Research
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• v.42 no.2
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• pp.130-140
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• 2017

Background: With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. Materials and Methods: A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. Results and Discussion: The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies.

• Journal of Radiation Protection and Research
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• v.46 no.3
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• pp.83-97
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• 2021

Background: The lifetime risk of lung cancer incidence due to radiation for nonsmokers is overestimated because of the use of the average cancer baseline risk among a mixed population, including smokers. In recent years, the generalized multiplicative (GM)-excess relative risk (ERR) model has been developed in the life span study of atomic bomb survivors to consider the joint effect of radiation and smoking. Based on this background, this paper discusses the issues of radiation risk assessment considering smoking in two parts. Materials and Methods: In Part 1, we proposed a simple method of estimating the baseline risk for nonsmokers using current smoking data. We performed sensitivity analysis on baseline risk estimation to discuss the birth cohort effects. In Part 2, we applied the GM-ERR model for Japanese smokers to calculate lifetime attributable risk (LAR). We also performed a sensitivity analysis using other ERR models (e.g., simple additive (SA)-ERR model). Results and Discussion: In Part 1, the lifetime baseline risk from mixed population including smokers to nonsmokers decreased by 54% (44%-60%) for males and 24% (18%-29%) for females. In Part 2, comparison of LAR between SA- and GM-ERR models showed that if the radiation dose was ≤200 mGy or less, the difference between these ERR models was within the standard deviation of LAR due to the uncertainty of smoking information. Conclusion: The use of mixed population for baseline risk assessment overestimates the risk for lung cancer due to low-dose radiation exposure in Japanese males.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1937-1943
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• 2013

Altered expression or function of manganese superoxide dismutase (MnSOD) has been shown to be associated with cancer risk but assessment of gene polymorphisms has resulted in inconclusive data. Here a search of published data was made and 22 studies were recruited, covering 20,025 case and control subjects, for meta-analyses of the association of MnSOD polymorphisms with the risk of prostate, esophageal, and lung cancers. The data on 12 studies of prostate cancer (including 4,182 cases and 6,885 controls) showed a statistically significant association with the risk of development in co-dominant models and dominant models, but not in the recessive model. Subgroup analysis showed there was no statistically significant association of MnSOD polymorphisms with aggressive or nonaggressive prostate cancer in different genetic models. In addition, the data on four studies of esophageal cancer containing 620 cases and 909 controls showed a statistically significant association between MnSOD polymorphisms and risk in all comparison models. In contrast, the data on six studies of lung cancer with 3,375 cases and 4,050 controls showed that MnSOD polymorphisms were significantly associated with the decreased risk of lung cancer in the homozygote and dominant models, but not the heterozygote model. A subgroup analysis of the combination of MnSOD polymorphisms with tobacco smokers did not show any significant association with lung cancer risk, histological type, or clinical stage of lung cancer. The data from the current study indicated that the Ala allele MnSOD polymorphism is associated with increased risk of prostate and esophageal cancers, but with decreased risk of lung cancer. The underlying molecular mechanisms warrant further investigation.

• Proceedings of the Korean Society of Toxicology Conference
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• 2002.05a
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• pp.137-137
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• 2002

Biologically Based Dose-Response (BBDR) models were developed using biomarkers for cancer risk assessment. To establish the relationship among biomarkers, exposure dose and tumor response, biomarkers in the lung, liver, stomach or blood were measured after a single or continuous administration of selected carcinogen (; BaP) in mice or rats.(omitted)

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.895-904
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• 2016

Breast cancer is the most commonly diagnosed invasive cancer among women. Many factors, both genetic and non-genetic, determine a woman's risk of developing breast cancer and several breast cancer risk prediction models have been proposed. It is vitally important to risk stratify patients as there are now effective preventive strategies available. All women need to be counseled regarding healthy lifestyle recommendations to decrease breast cancer risk. As such, management of these women requires healthcare professionals to be familiar with additional risk factors so that timely recommendations can be made on surveillance/risk-reducing strategies. Breast cancer risk reduction strategies can be better understood by encouraging the women at risk to participate in clinical trials to test new strategies for decreasing the risk. This article reviews the advances in the identification of women at high risk of developing breast cancer and also reviews the strategies available for breast cancer prevention.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.11
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• pp.4913-4916
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• 2016

Objective: As a source of information, medical data can feature hidden relationships. However, the high volume of datasets and complexity of decision-making in medicine introduce difficulties for analysis and interpretation and processing steps may be needed before the data can be used by clinicians in their work. This study focused on the use of Bayesian models with different numbers of nodes to aid clinicians in breast cancer risk estimation. Methods: Bayesian networks (BNs) with a retrospectively collected dataset including mammographic details, risk factor exposure, and clinical findings was assessed for prediction of the probability of breast cancer in individual patients. Area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity, and positive and negative predictive values were used to evaluate discriminative performance. Result: A network incorporating selected features performed better (AUC = 0.94) than that incorporating all the features (AUC = 0.93). The results revealed no significant difference among 3 models regarding performance indices at the 5% significance level. Conclusion: BNs could effectively discriminate malignant from benign abnormalities and accurately predict the risk of breast cancer in individuals. Moreover, the overall performance of the 9-node BN was better, and due to the lower number of nodes it might be more readily be applied in clinical settings.