• Asian Pacific Journal of Cancer Prevention
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• 제14권10호
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• pp.5657-5661
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• 2013

In India, among males, leukemia rates vary across the country. The present unmatched hospital-based case-control study conducted at Tata Memorial Hospital included subjects registered between the years 1997-99. There were 246 leukemia cases and 1,383 normal controls. Data on demographics, lifestyle, diet and occupation history were recorded. Cigarette (OR=2.1) and bidi smoking (OR=3.4) showed excess risk for leukemia. Odds ratios were 3.9 for fish-eaters, 0.40 for chilli eaters, 1.5 for milk drinkers and 0.60 for coffee drinkers, compared to non-drinkers/eaters. However, neither exposure to use of pesticides nor cotton dust showed any excess risk for leukemia.

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 1996년도 제48차 추계 학술대회 연제집
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• pp.125-126
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• 1996

• Journal of Preventive Medicine and Public Health
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• 제54권4호
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• pp.259-264
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• 2021

Traditional epidemiological studies have identified a number of risk factors for various diseases using regression-based methods that examine the association between an exposure and an outcome (i.e., one-to-one correspondences). One of the major limitations of this approach is the "black-box" aspect of the analysis, in the sense that this approach cannot fully explain complex relationships such as biological pathways. With high-throughput data in current epidemiology, comprehensive analyses are needed. The network approach can help to integrate multi-omics data, visualize their interactions or relationships, and make inferences in the context of biological mechanisms. This review aims to introduce network analysis for systems epidemiology, its procedures, and how to interpret its findings.

• Infection and chemotherapy
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• 제50권4호
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• pp.287-300
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• 2018

Pneumonia is the leading cause of morbidity and mortality, particularly in old adults. The incidence and etiologic distribution of community-acquired pneumonia is variable both geographically and temporally, and epidemiology might evolve with the change of population characteristics and vaccine uptake rates. With the increasing prevalence of chronic medical conditions, a wide spectrum of healthcare-associated pneumonia could also affect the epidemiology of community-acquired pneumonia. Here, we provide an overview of the epidemiological changes associated with community-acquired pneumonia over the decades since pneumococcal conjugate vaccine introduction.

• 고려인삼학회:학술대회논문집
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• 고려인삼학회 1990년도 Proceedings of International Symposium on Korean Ginseng, 1990, Seoul, Korea
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• pp.95-95
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• 1990

• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2685-2686
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• 2013

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 2004년도 제56차 추계 학술대회 연제집
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• pp.35.1-35.1
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• 2004

• Asian Pacific Journal of Cancer Prevention
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• 제15권9호
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• pp.4109-4115
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• 2014

Background: Accurate assessment of disease progression requires proper understanding of natural disease process which is often hidden and unobservable. For this purpose, disease status should be clearly detected. But in most diseases it is not possible to detect such status. This study, therefore, aims to present a model which both investigates the unobservable disease process and considers the error probability in diagnosis of disease states. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at the Iran Cancer Institute from 1995 to 1999 were analyzed. Moreover, to estimate and assess the effect of demographic, diagnostic and clinical factors as well as medical and post-surgical variables on transition rates and the probability of misdiagnosis of relapse, a hidden Markov multi-state model was employed. Results: Classification errors of patients in alive state without a relapse ($e_{21}$) and with a relapse ($e_{12}$) were 0.22 (95% CI: 0.04-0.63) and 0.02 (95% CI: 0.00-0.09), respectively. Only variables of age and number of renewed treatments affected misdiagnosis of relapse. In addition, patient age and distant metastasis were among factors affecting the occurrence of relapse (state1${\rightarrow}$state2) while the number of renewed treatments and the type and extent of surgery had a significant effect on death hazard without relapse (state2${\rightarrow}$state3)and death hazard with relapse (state2${\rightarrow}$state3). Conclusions: A hidden Markov multi-state model provides the possibility of estimating classification error between different states of disease. Moreover, based on this model, factors affecting the probability of this error can be identified and researchers can be helped with understanding the mechanisms of classification error.

• Asian Pacific Journal of Cancer Prevention
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• 제15권1호
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• pp.441-447
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• 2014

Background: Multi-state models are appropriate for cancer studies such as gastrectomy which have high mortality statistics. These models can be used to better describe the natural disease process. But reaching that goal requires making assumptions like Markov and homogeneity with time. The present study aims to investigate these hypotheses. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. To assess Markov assumption and time homogeneity in modeling transition rates among states of multi-state model, Cox-Snell residuals, Akaikie information criteria and Schoenfeld residuals were used, respectively. Results: The assessment of Markov assumption based on Cox-Snell residuals and Akaikie information criterion showed that Markov assumption was not held just for transition rate of relapse (state 1 ${\rightarrow}$ state 2) and for other transition rates - death hazard without relapse (state 1 ${\rightarrow}$ state 3) and death hazard with relapse (state 2 ${\rightarrow}$ state 3) - this assumption could also be made. Moreover, the assessment of time homogeneity assumption based on Schoenfeld residuals revealed that this assumption - regarding the general test and each of the variables in the model- was held just for relapse (state 1 ${\rightarrow}$ state 2) and death hazard with a relapse (state 2 ${\rightarrow}$ state 3). Conclusions: Most researchers take account of assumptions such as Markov and time homogeneity in modeling transition rates. These assumptions can make the multi-state model simpler but if these assumptions are not made, they will lead to incorrect inferences and improper fitting.

• Asian Pacific Journal of Cancer Prevention
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• 제15권3호
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• pp.1197-1203
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• 2014

Background: Adenocarcinoma (ADC) is the most common histological type of lung cancer and its proportion is rising, especially in Asian non-smoking women. Recent studies suggest miR-25 may have diverse effects on the pathogenesis of different types of cancer. However, the role of miR-25 in lung cancer is still unknown. The aim of this study was to investigate the potential clinical value of miR-25 in non-smoking women with lung ADC. Patients and Methods: Quantitative RT-PCR was performed to evaluate the expression of miR-25 in 100 lung ADC tumor tissues and matched plasma samples and Pearson correlation tests were used to analyze the relationship between values. Associations of miR-25 expression with clinicopathological features were determined using the Student's t-test. To determine prognostic value, overall survival (OS) was evaluated using the Kaplan-Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazard model. Results: Expression of miR-25 in tissue was found to be associated with lymph node metastasis (P=0.021) and disease stage (P=0.012). Moreover, high miR-25 expression was also associated with poorer overall survival of women with lung ADC (P=0.008). Conclusion: Tissue miR-25 expression may be associated with tumor progression and have prognostic implications in female lung ADC patients.