• Asian Pacific Journal of Cancer Prevention
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• 제17권7호
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• pp.3505-3510
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• 2016

Cervical cancer is a major public health problem in Thailand, being ranked second only to breast cancer. Thai women have been reported to have a low rate of cervical cancer screening (27.7% of the 80% goal of WHO). We therefore aimed to apply the social marketing theory and health belief model in promoting cervical cancer screening in Kanthararom District, Sisaket Province. A total of 92 from 974 targeted women aged 30-60 years were randomly divided into two groups. The experimental group underwent application of social marketing theory and a health belief model program promoting cervical cancer screening while the control group received normal services. Two research tools were used: (1) application of social marketing theory and health belief model program and (2) questionnaire used to evaluate perceptions of cervical cancer. Descriptive and inferential statistics including paired sample t-test and independent t-test were used to analyze the data. After the program had been used, the mean score of perception of cervical cancer of experimental group was at a higher level (${\bar{x}}=4.09$; S.D.=0.30), than in the control group (${\bar{x}}=3.82$; S.D.=0.20) with statistical significance (p<0.001). This research demonstrated an appropriate communication process in behavioral modification to prevent cervical cancer. It can be recommended that this program featuring social marketing and the health belief model be used to promote cervical cancer screening in targeted women and it can be promoted as a guideline for other health services, especially in health promotion and disease prevention.

• Journal of Preventive Medicine and Public Health
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• 제46권2호
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• pp.74-81
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• 2013

Objectives: The objective of this study was to evaluate the performance of risk-adjusted mortality models for colorectal cancer surgery. Methods: We investigated patients (n=652) who had undergone colorectal cancer surgery (colectomy, colectomy of the rectum and sigmoid colon, total colectomy, total proctectomy) at five teaching hospitals during 2008. Mortality was defined as 30-day or in-hospital surgical mortality. Risk-adjusted mortality models were constructed using claims data (basic model) with the addition of TNM staging (TNM model), physiological data (physiological model), surgical data (surgical model), or all clinical data (composite model). Multiple logistic regression analysis was performed to develop the risk-adjustment models. To compare the performance of the models, both c-statistics using Hanley-McNeil pair-wise testing and the ratio of the observed to the expected mortality within quartiles of mortality risk were evaluated to assess the abilities of discrimination and calibration. Results: The physiological model (c=0.92), surgical model (c=0.92), and composite model (c=0.93) displayed a similar improvement in discrimination, whereas the TNM model (c=0.87) displayed little improvement over the basic model (c=0.86). The discriminatory power of the models did not differ by the Hanley-McNeil test (p>0.05). Within each quartile of mortality, the composite and surgical models displayed an expected mortality ratio close to 1. Conclusions: The addition of clinical data to claims data efficiently enhances the performance of the risk-adjusted postoperative mortality models in colorectal cancer surgery. We recommended that the performance of models should be evaluated through both discrimination and calibration.

• Asian Pacific Journal of Cancer Prevention
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• 제14권8호
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• pp.4897-4902
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• 2013

Here we assessed the effectiveness of cervical cancer screening using data from the Hiroshima Prefecture Cancer Registry regarding patient age at the start of screening and differences in screening intervals. A screening model was created to calculate the health status in relation to prognosis following cervical cancer screening and its influence on life expectancy. Epidemiological data on the mortality rate of cervical cancer by age groups and mortality rates from the Hiroshima Prefecture Cancer Registry were used for the model projections. Our results showed that life expectancy when screening rate was 100% compared with 0% was extended by approximately 1 month. Furthermore, when the incidence of cervical cancer was 0% compared with the screening rate was 100%, life expectancy was extended by a maximum of 3 months. Moreover, among individuals affected by cervical c ancer, a difference of 13 years in life expectancy was calculated between screened and unscreened groups.

• Asian Pacific Journal of Cancer Prevention
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• 제16권17호
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• pp.7923-7927
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• 2015

Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

• 대한간호학회지
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• 제41권4호
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• pp.460-470
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• 2011

Purpose: The aim of this study was to develop and test an explanatory model for sleep disorders in people with cancer. A hypothetical model was constructed on the basis of a review of previous studies, literature, and sleep models, and 10 latent variables were used to construct a hypothetical model. Methods: Data were collected from April 19 to June 25, 2010, using self-report questionnaires. The sample was 291 outpatients with cancer who visited the oncology cancer center at a university hospital. Collected data were analyzed using SPSS Win 15.0 program for descriptive statistics and correlation analysis and AMOS 7.0 program for covariance structural analysis. Results: It appeared that overall fit index was good as ${\chi}^2/df=1.162$, GFI=.969, AGFI=.944, SRMR=.052, NFI=.881, NNFI=.969, CFI=.980, RMSEA=.024, CN=337 in the modified model. The explanatory power of this model for sleep disorders in people with cancer was 62%. Further, sleep disorders were influenced directly by cancer symptom experience, dysfunctional beliefs and attitudes about sleep, and past sleep pattern. Conclusion: Findings suggest that nurses should assess past sleep pattern and consider the development of a comprehensive nursing intervention program to minimize the cancer symptom experience, dysfunctional beliefs and attitudes about sleep, and thus, reduce sleep disorders in people with cancer.

• Asian Pacific Journal of Cancer Prevention
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• 제17권8호
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• pp.3741-3745
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• 2016

Background: This study was carried out to examine breast cancer risk and its fertility predictors in women aged ${\geq}35$. Materials and Methods: This cross-sectional study was conducted on 560 healthy women referred to health centers of Tabriz-Iran, 2013-2014. Five-year and lifetime risk of developing breast cancer were determined using the Gail model. General linear modeling was applied to determine breast cancer predictors. Results: The mean age of the subjects was 42.7 (SD: 7.7) years. Mean 5-year and lifetime risks of developing breast cancer were determined to be 0.6% (SD: 0.2%) and 8.9% (SD: 2.5%), respectively. Variables of family history of breast cancer, age, age at menarche, parity, age at first childbirth, breastfeeding history, frequency of breastfeeding, method of contraception, marital status and education were all found to be predictors of breast cancer risk. Conclusions: According to the results of this study, screening programs based on the Gail model should be implemented for Iranian people who have a high risk for breast cancer in order to facilitate early detection and better plan for possible malignancies.

• 대한의용생체공학회:의공학회지
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• 제41권2호
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• pp.101-106
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• 2020

Although benign gastric ulcers do not develop into gastric cancer, they are similar to early gastric cancer and difficult to distinguish. This may lead to misconsider early gastric cancer as gastric ulcer while diagnosing. Since gastric cancer does not have any special symptoms until discovered, it is important to detect gastric ulcers by early gastroscopy to prevent the gastric cancer. Therefore, we developed a Convolution Neural Network (CNN) model that can be helpful for endoscopy. 3,015 images of gastroscopy of patients undergoing endoscopy at Gachon University Gil Hospital were used in this study. Using ResNet-50, three models were developed to classify normal and gastric ulcers, normal and gastric cancer, and gastric ulcer and gastric cancer. We applied the data augmentation technique to increase the number of training data and examined the effect on accuracy by varying the multiples. The accuracy of each model with the highest performance are as follows. The accuracy of normal and gastric ulcer classification model was 95.11% when the data were increased 15 times, the accuracy of normal and gastric cancer classification model was 98.28% when 15 times increased likewise, and 5 times increased data in gastric ulcer and gastric cancer classification model yielded 87.89%. We will collect additional specific shape of gastric ulcer and cancer data and will apply various image processing techniques for visual enhancement. Models that classify normal and lesion, which showed relatively high accuracy, will be re-learned through optimal parameter search.

• Asian Pacific Journal of Cancer Prevention
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• 제16권2호
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• pp.437-442
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• 2015

Aim: To establish a pancreatic cancer stem cell model using human pancreatic cancer cells in nude mice to provide a platform for pancreatic cancer stem cell research. Materials and Methods: To establish pancreatic cancer xenografts using human pancreatic cancer cell line SW1990, nude mice were randomly divided into control and gemcitabine groups. When the tumor grew to a volume of $125mm^3$, they treated with gemcitabine at a dose of 50mg/kg by intraperitoneal injection of 0.2ml in the gemcitabine group, while the mice in control group were treated with the same volume of normal saline. Gemcitabine was given 2 times a week for 3 times. When the model was established, the proliferation of pancreatic cancer stem cells was observed by clone formation assay, and the protein and/or mRNA expression of pancreatic stem cell surface markers including CD24, CD44, CD133, ALDH, transcription factors containing Oct-4, Sox-2, Nanog and Gli, the key nuclear transcription factor in Sonic Hedgehog signaling pathway was detected by Western blot and/or RT-PCR to verify the reliability of this model. Results: This model is feasible and safe. During the establishment, no mice died and the weight of nude mice maintained above 16.5g. The clone forming ability in gemcitabine group was stronger than that of the control group (p<0.01). In gemcitabine group, the protein expression of pancreatic cancer stem cell surface markers including CD44, and ALDH was up-regulated, the protein and mRNA expression of nuclear transcription factor including Oct-4, Sox-2 and Nanog was also significantly increased (P<0.01). In addition, the protein expression of key nuclear transcription factor in Sonic Hedgehog signaling pathway, Gli-1, was significantly enhanced (p<0.01). Conclusions: The pancreatic cancer stem cell model was successfully established using human pancreatic cancer cell line SW1990 in nude mice. Gemcitabine could enrich pancreatic cancer stem cells, simultaneously accompanied by the activation of Sonic Hedgehog signaling pathway.

• 한국수정란이식학회지
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• 제31권1호
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• pp.97-107
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• 2016

Although many diseases could be treated by the development of modern medicine, there are some incurable diseases including brain cancer, Alzheimer disease, etc. To study human brain cancer, various animal models were reported. Among these animal models, mouse models are valuable tools for understanding brain cancer characteristics. In spite of many mouse brain cancer models, it has been difficult to find a new target molecule for the treatment of brain cancer. One of the reasons is absence of large animal model which makes conducting preclinical trials. In this article, we review a recent study of molecular characteristics of human brain cancer, their genetic mutation and comparative analysis of the mouse brain cancer model. Finally, we suggest the need for development of large animal models using somatic cell nuclear transfer in translational research.

• Asian Pacific Journal of Cancer Prevention
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• 제15권14호
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• pp.5681-5684
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• 2014

Objective: Prevalence is a statistic of primary interest in public health. In the absence of good follow-up facilities, it is often difficult to assess the complete prevalence of cancer for a given registry area. An attempt is made to arrive at the complete prevalence including limited duration prevalence with respect of selected sites of cancer for India by fitting appropriate models to 1, 3 and 5 year cancer survival data available for selected registries of India. Methodology: Cancer survival data, available for the registries of Bhopal, Chennai, Karunagappally, and Mumbai was pooled to generate survival for the selected cancer sites. With the available data on survival for 1, 3 and 5 years, a model was fitted and the survival curve was extended beyond 5 years (up to 30 years) for each of the selected sites. This helped in generation of survival proportions by single year and thereby survival of cancer cases. With the help of estimated survived cases available year wise and the incidence, the prevalence figures were arrived for selected cancer sites and for selected periods. In our previous paper, we have dealt with the cancer sites of breast, cervix, ovary, lung, stomach and mouth (Takiar and Jayant, 2013). Results: The prevalence to incidence ratio (PI ratio) was calculated for 30 years duration for all the selected cancer sites using the model approach showing that from the knowledge of incidence and P/I ratio, the prevalence can be calculated. The validity of the approach was shown in our previous paper (Takiar and Jayant, 2013). The P/I ratios for the cancer sites of lip, tongue, oral cavity, hypopharynx, oesophagus, larynx, nhl, colon, prostate, lymphoid leukemia, myeloid leukemia were observed to be 10.26, 4.15, 5.89, 2.81, 1.87, 5.43, 5.48, 5.24, 4.61, 3.42 and 2.65, respectively. Conclusion: Cancer prevalence can be readily estimated with use of survival and incidence data.