• Title/Summary/Keyword: Cancer model

Search Result 2,172, Processing Time 0.026 seconds

A Structural Model for Psychosocial Adjustment in Patients with Early Breast Cancer (초기 유방암 환자의 심리사회적 적응 구조모형)

  • Kim, Hye-Young;So, Hyang-Sook
    • Journal of Korean Academy of Nursing
    • /
    • v.42 no.1
    • /
    • pp.105-115
    • /
    • 2012
  • Purpose: This study was done to propose a structural model to explain and predict psychosocial adjustment in patients with early breast cancer and to test the model. The model was based on the Stress-Coping Model of Lazarus and Folkman (1984). Methods: Data were collected from February 18 to March 18, 2009. For data analysis, 198 data sets were analyzed using SPSS/WIN12 and AMOS 7.0 version. Results: Social support, uncertainty, symptom experience, and coping had statistically significant direct, indirect and total effects on psychosocial adjustment, and optimism had significant indirect and total effects on psychosocial adjustment. These variables explained 57% of total variance of the psychosocial adjustment in patients with early breast cancer. Conclusion: The results of the study indicate a need to enhance psychosocial adjustment of patients with early breast cancer by providing detailed structured information and various symptom alleviation programs to reduce perceived stresses such as uncertainty and symptom experience. They also suggest the need to establish support systems through participation of medical personnel and families in such programs, and to apply interventions strengthening coping methods to give the patients positive and optimistic beliefs.

Predictors of Participation in Prostate Cancer Screening among Older Men in Jordan

  • Abuadas, Mohammad H;Petro-Nustas, Wasileh;Albikawi, Zainab F.
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.16 no.13
    • /
    • pp.5377-5383
    • /
    • 2015
  • Background: Participation is one of the major factors affecting the long-term success of population-based prostate cancer screening programs. The aim of this study was to explore strong factors linked to participation in prostate cancer screening among older Jordanian adults using the Health Belief Model (HBM). Materials and Methods: Data were obtained from Jordanian older adults, aged 40 years and over, who visited a comprehensive health care center within the Ministry of Health. A pilot test was conducted to investigate the internal consistency of the the Champion Health Belief Model Scale for prostate cancer screening and the clarity of survey questions. Sample characteristics and rates of participation in prostate cancer screening were examined using means and frequencies. Important factors associated with participation in prostate cancer screening were examined using bivariate correlation and multivariate logistic regression analysis. Results: About 13% of the respondents had adhered to prostate cancer screening guidelines over the previous decade. Four out of the seven HBM-driven factors (perceived susceptibility, benefits and barriers to PSA test, and health motivation) were statistically significant. Those with greater levels of susceptibility, benefits of PSA test and health motivation and lower levels of barriers to PSA testing were more likely to participate in prostate cancer screening. Family history, presence of urinary symptoms, age, and knowledge about prostate cancer significantly predicted the participation in prostate cancer screening. Conclusions: Health professionals should focus more on the four modifiable HBMrelated factors to encourage older adults to participate in prostate cancer screening. Intervention programs, which lower perceived barriers to PSA testing and increase susceptibility, benefits of PSA testing and health motivation, should be developed and implemented.

Lack of Association between the hOGG1 Ser326Cys Polymorphism and Gastric Cancer Risk: a Meta-analysis

  • Li, Bai-Rong;Zhou, Guo-Wu;Bian, Qi;Song, Bin
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.13 no.4
    • /
    • pp.1145-1149
    • /
    • 2012
  • Aim: To clarify any association between the hOGG1 Ser326Cys polymorphism and susceptibility to gastric cancer. Methods: A meta-analysis based on 11 eligible case-control studies involving 5,107 subjects was carried out to summarize the data on the association between hOGG1 Ser326Cys polymorphism and gastric cancer risk. Results: No association was found between hOGG1 Ser326Cys polymorphism and gastric cancer risk (dominant model: OR = 0.95, 95% CI: 0.83-1.09, p = 0.486, ph (p values for heterogeneity) = 0.419; additive model: OR = 1.02, 95% CI: 0.81-1.30, p = 0.850, ph = 0.181; recessive model: OR = 1.09, 95% CI: 0.80-1.48, p = 0.586, ph = 0.053). Subgroup analysis based on ethnicity (Asian and Caucasian) and smoking status (ever smoker and never smoker) did did notpresent any significant association. Sensitivity analysis did not perturb the results. Conclusions: This study strongly suggested there might be no association between the hOGG1 Ser326Cys polymorphism and gastric cancer risk. However, larger scale studies are needed for confirmation.

Use of an Artificial Neural Network to Predict Risk Factors of Nosocomial Infection in Lung Cancer Patients

  • Chen, Jie;Pan, Qin-Shi;Hong, Wan-Dong;Pan, Jingye;Zhang, Wen-Hui;Xu, Gang;Wang, Yu-Min
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.15 no.13
    • /
    • pp.5349-5353
    • /
    • 2014
  • Statistical methods to analyze and predict the related risk factors of nosocomial infection in lung cancer patients are various, but the results are inconsistent. A total of 609 patients with lung cancer were enrolled to allow factor comparison using Student's t-test or the Mann-Whitney test or the Chi-square test. Variables that were significantly related to the presence of nosocomial infection were selected as candidates for input into the final ANN model. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the performance of the artificial neural network (ANN) model and logistic regression (LR) model. The prevalence of nosocomial infection from lung cancer in this entire study population was 20.1% (165/609), nosocomial infections occurring in sputum specimens (85.5%), followed by blood (6.73%), urine (6.0%) and pleural effusions (1.82%). It was shown that long term hospitalization (${\geq}22days$, P= 0.000), poor clinical stage (IIIb and IV stage, P=0.002), older age (${\geq}61days$ old, P=0.023), and use the hormones were linked to nosocomial infection and the ANN model consisted of these four factors. The artificial neural network model with variables consisting of age, clinical stage, time of hospitalization, and use of hormones should be useful for predicting nosocomial infection in lung cancer cases.

Pharmacophore Development for Anti-Lung Cancer Drugs

  • Haseeb, Muhammad;Hussain, Shahid
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.16 no.18
    • /
    • pp.8307-8311
    • /
    • 2016
  • Lung cancer is one particular type of cancer that is deadly and relatively common than any other. Treatment is with chemotherapy, radiation therapy and surgery depending on the type and stage of the disease. Focusing on drugs used for chemotherapy and their associated side effects, there is a need to design and develop new anti-lung cancer drugs with minimal side effects and improved efficacy. The pharmacophore model appears to be a very helpful tool serving in the designing and development of new lead compounds. In this paper, pharmacophore analysis of 10 novel anti-lung cancer compounds was validated for the first time. Using LigandScout the pharmacophore features were predicted and 3D pharmacophores were extracted via VMD software. A training set data was collected from literature and the proposed model was applied to the training set whereby validating and verifying similar activity as that of the most active compounds was achieved. Therefore pharmacophore develoipment could be recommended for further studies.

Assessing Misdiagnosis of Relapse in Patients with Gastric Cancer in Iran Cancer Institute Based on a Hidden Markov Multi-state Model

  • Zare, Ali;Mahmoodi, Mahmood;Mohammad, Kazem;Zeraati, Hojjat;Hosseini, Mostafa;Naieni, Kourosh Holakouie
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.15 no.9
    • /
    • pp.4109-4115
    • /
    • 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.

Zinc and Zinc Related Enzymes in Precancerous and Cancerous Tissue in the Colon of Dimethyl Hydrazine Treated Rats

  • Christudoss, Pamela;Selvakumar, R.;Pulimood, Anna B.;Fleming, Jude Joseph;Mathew, George
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.13 no.2
    • /
    • pp.487-492
    • /
    • 2012
  • Trace element zinc deficiency or excess is implicated in the development or progression of some cancers. The exact role of zinc in the etiology of colon cancer is unclear. To cast light on this question, an experimental model of colon carcinogenesis was applied here. Six week old rats were given sub cutaneous injections of DMH (30 mg/kg body weight) twice a week for three months and sacrificed after 4 months (precancer model) and 6 months (cancer model). Plasma zinc levels showed a significant decrease (p<0.05) at 4 months and a greater significant decrease at 6 months (p<0.01) as compared with controls. In the large intestine there was a significant decrease in tissue zinc levels (p<0.005) and in CuZnSOD, and alkaline phosphatase activity (p<0.05) in the pre-cancerous model and a greater significant decrease in tissue zinc (p<0.0001), and in CuZnSOD and alkaline phosphatase activity (p<0.001), in the carcinoma model. The tissue zinc levels showed a significant decrease in the small intestine and stomach (p<0.005) and in liver (p<0.05) in the cancer model. 87% of the rats in the precancer group and 92% rats in the cancer group showed histological evidence of precancerous lesions and carcinomas respectively in the colon mucosa. This study suggests that the decrease in plasma zinc, tissue zinc and activity of zinc related enzymes are associated with the development of preneoplastic lesions and these biochemical parameters further decrease with progression to carcinoma in the colon.

Bayesian Method for Modeling Male Breast Cancer Survival Data

  • Khan, Hafiz Mohammad Rafiqullah;Saxena, Anshul;Rana, Sagar;Ahmed, Nasar Uddin
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.15 no.2
    • /
    • pp.663-669
    • /
    • 2014
  • Background: With recent progress in health science administration, a huge amount of data has been collected from thousands of subjects. Statistical and computational techniques are very necessary to understand such data and to make valid scientific conclusions. The purpose of this paper was to develop a statistical probability model and to predict future survival times for male breast cancer patients who were diagnosed in the USA during 1973-2009. Materials and Methods: A random sample of 500 male patients was selected from the Surveillance Epidemiology and End Results (SEER) database. The survival times for the male patients were used to derive the statistical probability model. To measure the goodness of fit tests, the model building criterions: Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were employed. A novel Bayesian method was used to derive the posterior density function for the parameters and the predictive inference for future survival times from the exponentiated Weibull model, assuming that the observed breast cancer survival data follow such type of model. The Markov chain Monte Carlo method was used to determine the inference for the parameters. Results: The summary results of certain demographic and socio-economic variables are reported. It was found that the exponentiated Weibull model fits the male survival data. Statistical inferences of the posterior parameters are presented. Mean predictive survival times, 95% predictive intervals, predictive skewness and kurtosis were obtained. Conclusions: The findings will hopefully be useful in treatment planning, healthcare resource allocation, and may motivate future research on breast cancer related survival issues.

Clinical Pharmacokinetics of Vancomycin in Ovarian Cancer Patients (난소암 환자에서 반코마이신의 임상약물동태)

  • Kim, Yang Woo;Choi, Jun Shik;Lee, Jin Hwan;Park, Jae Young;Choi, Byong Chul;Burm, Jin Pil
    • Korean Journal of Clinical Pharmacy
    • /
    • v.8 no.1
    • /
    • pp.13-18
    • /
    • 1998
  • The purpose of this study was to determine pharmacokinetic parameters of vancomycin using the compartment model dependent and compartment model independent analysis in 6 Korean normal volunteers and 8 ovarian cancer patients. Vancomycin was administered 1.0 g bolus by IV infusion over 60 minutes. The elimination rate constant ($\beta$), volume of distribution (Vd), total body clearance (CLt), and area under the plasma level-time curve (AUC) of vancomycin in normal volunteers using the compartment model dependent analysis were $0.150\pm0.030\;hr^{-1},\;32.9\pm2.81\;L/kg,\;5.36\pm0.63\;L/hr,\;and\;186.5\pm20.5\;{\mu}g/ml{\cdot}hr$, respectively. The $\beta$, Vd, CLt, and AUC of vancomycin in ovarian cancer patients using the compartment model dependent analysis were $0.109\;0.008\;hr^{-1},\;41.5\pm3.01\;L/kg,\;4.58\pm0.57\;L/hr\;and\;218.3\pm22.9\;{\mu}g/ml{\cdot}hr$, respectively. There were significant differences (p<0.05,\;p<0.01) in $\beta$, Vd, CLt, and AUC between normal volunteers and ovarian cancer patients. The elimination rate constant (Kel), CLt, and AUC of vancomycin in normal volunteers using the compartment model independent analysis were $0.152\pm0.022\;hr^{-1},\;5.77\pm0.75\;L/hr,\;and\;173.2\pm22.5;{\mu}g/ml{\cdot}hr$, respectively. The Kel, CLt, and AUC of vancomycin in ovarian cancer patients using the compartment model independent analysis were $0.126\pm0.012\;hr^{-1},\;4.96\pm0.55\;L/hr,\;and\;201.7\pm25.6;{\mu}g/ml{\cdot}hr$, respectively. There were significant differences (p<0.05, p<0.01) in Kel, CLt, and AUC between normal volunteers and ovarian cancer patients. And also, there was significant difference (p<0.05) in Kel of vancomycin in ovarian cancer patients between the compartment model dependent and independen analysis. It is necessary for effective dosage regimen of vancomycin in ovarian cancer patient to use these population parameters.

  • PDF

Beliefs, Attitudes, and Behavior of Turkish Women about Breast Cancer and Breast Self-Examination According to a Turkish Version of the Champion Health Belief Model Scale

  • Erbil, Nulufer;Bolukbas, Nurgul
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.13 no.11
    • /
    • pp.5823-5828
    • /
    • 2012
  • Background: Breast cancer (BC) is one of the most common cancer affecting women worldwide. Although a great deal of progress has been made in the health sciences, early diagnosis, and increasing community awareness, breast cancer remains a life-threatening illness. In order to reduce this threat, breast cancer screening needs to be implemented in all communities where possible. Objective: The purpose of this study was to examine health beliefs, attitudes and behaviors about breast cancer and breast self-examination of Turkish women. Methods: Data were collected from a sample of 656 women, using an adapted Turkish version of Champion's Health Belief Model Scale (CHBMS), between January and May 2011, in Ordu province of Turkey. Results: The results showed that 67.7% of women had knowledge about and 55.8% performed BSE, however 60.6% of those who indicated they practiced BSE reported they did so at irregular intervals. CHBMS subscales scores of women according to women's age, education level, occupation, family income and education level of the women's mothers, family history of breast cancer, friend and an acquaintance with breast cancer, knowledge about breast cancer, BSE and mammography were significantly different. Conclusion: Knowledge of women about the risks and benefits of early detection of breast cancer positively affect their health beliefs, attitudes, and behaviors. Health care professionals can develop effective breast health programs and can help women to gain good health behavior and to maintain health.