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Articles by Hojjat Zeraati
Total Records ( 4 ) for Hojjat Zeraati
  Hojjat Zeraati , Mahmood Mahmoudi , Anoshirvan Kazemnejad and Kazem Mohammad
  This study was designed and carried out to determine the five-year survival rate of gastric cancer patients who had undergone surgical treatment at one of the most important cancer treatment centers, the Iran Cancer Institute and to assess its associated factors. During a study period, patients may often experience events that are likely to affect the final outcome as well. Should these intermediate events and their time of occurrence be overlooked, they may bias the results of the study. It has been suggested that such variables be assigned in the model as time-dependent covariates, but using models with joint distribution of time before death and time before an intermediate event (in this study, relapse), although more difficult, will certainly provide more accurate results. In this study we analyzed the data using a non-homogenous semi-Markovian stochastic process, which basically, regarding life span and intensity rate as the stochastic processes, was a doubly stochastic process and recommend it for analyses of similar data. Two hundred and 81 gastric cancer patients with adenocarcinomatous pathology who had been admitted to and operated on at the Iran Cancer Institute between March 1995 and March 1999 were enrolled in this study. The patients` life expectancy after surgery was determined and its relationship with variables of age at the time of surgery, gender and factors related to the disease such as the cancer site, stage, presence of metastases and sites of metastasis were assessed. In the analyses, methods of Kaplan-Meier, Cox proportional hazards model, non-homogenous Markovian process and Breslow estimator were used. The software used for the analyses were S Plus 2000 and R and an alpha level of 0.05 was considered significant. The five-year survival rate and the median life expectancy in the studied patients were 22.6% and 19.00 months, respectively. The Cox proportional hazards model was used to assess the effect of different variables simultaneously and it showed that age, lymph node metastasis, recurrence and disease stage influenced the chances of survival. It was also shown that lymph node metastasis and disease stage correlated with time of recurrence, while age, distant metastasis and disease stage affected survival after recurrence and age correlated with survival of patients without recurrence. Gastric cancer patients in Iran have a low five-year survival rate. One of the most important reasons seems to be delayed consultation and diagnosis. Most patients are seen first with the disease in the late stages. At this point, most have lymph node, liver, or even distant metastases which makes treatment even more complex. Thus, it is necessary to employ mass media for extensive public education about the early warning signs of the disease and performing periodic examinations.
  Hojjat Zeraati , Farid Zayeri , Gholamreza Babaee , Navid Khanafshar and Fatemeh Ramezanzadeh
  In this study, we aimed to estimate number of required hospital beds using stochastic process and statistical simulation. Preliminary required data for simulation process is collected from a random sample of hospitalized women in an obstetrics ward. Then, a simulation study was performed in regard to distribution of inpatients. Hospitalization time before and after starting treatment and the number of inpatients in all kinds of services were the principal parameters in simulation process. The initial results from the sample showed that the number of hospitalized women in all services follows a poisson distribution. Additionally, the estimation of required number of hospital beds in this ward was obtained using simulation study. The introduced methods can easily utilize in other obstetrics wards as well as different hospital units. It seems that postulating poisson distribution for inpatients in other hospital units is a valid assumption. May be it`s preferable to study this method in other hospital units as well.
  Nargess Saiepour , Kazem Mohammad , Roya Abhari , Hojjat Zeraati and Ahmad Ali Noorbala
  The aim of this study was to investigate the association between mental disorder and back pain among postmenopausal Iranian women. Three thousand six hundred and fifty five postmenopausal women were interviewed in the second National Health Survey (2nd NHS) in the year 2000, in Iran. Of whom, 2953 women were included in this study. Back pain (BKP) was considered as dependent variable and mental disorder as independent variable. Factors like age, Body Mass Index (BMI), residential area, employment, literacy, smoking habit, marital status and spinal fractures were considered as confounders. Logistic regression models have been applied for data analysis. The BKP prevalence was 40.1% and the prevalence of mental disorder was 44.3%. After adjustment for confounders, mental disorder was positively associated with BKP, OR (CI): 1.615 (1.36, 1.91). This study confirmed that BKP and mental disorder are common problems and these two factors are associated amongst postmenopausal women. Further longitudinal studies are recommended to specify casual inferences.
  Zohreh Amiri , Kazem Mohammad , Mahmoud Mahmoudi , Hojjat Zeraati and Akbar Fotouhi
  This study is designed to assess the application of neural networks in comparison to the Kaplan-Meier and Cox proportional hazards model in the survival analysis. Three hundred thirty gastric cancer patients admitted to and surgically treated were assessed and their post-surgical survival was determined. The observed baseline survival was determined with the three methods of Kaplan-Meier product limit estimator, Cox and the neural network and results were compared. Then the binary independent variables were entered into the model. Data were randomly divided into two groups of 165 each to test the models and assess the reproducibility. The Chi-square test and the multiple logistic model were used to ensure the groups were similar and the data was divided randomly. To compare subgroups, we used the log-rank test. In the next step, the probability of survival in different periods was computed based on the training group data using the Cox proportional hazards and a neural network and estimating Cox coefficient values and neural network weights (with 3 nodes in hidden layer). Results were used for predictions in the test group data and these predictions were compared using the Kaplan-Meier product limit estimator as the gold standard. Friedman and Kruskal-Wallis tests were used for comparisons as well. All statistical analyses were performed using SPSS version 11.5, Matlab version 7.2, Statistica version 6.0 and S_PLUS 2000. The significance level was considered 5% (α = 0.05). The three methods used showed no significance difference in base survival probabilities. Overall, there was no significant difference among the survival probabilities or the trend of changes in survival probabilities calculated with the three methods, but the 4 year (48th month) and 4.5 year (54th month) survival rates were significantly different with Cox compared to standard and estimated probabilities in the neural network (p<0.05). Kaplan-Meier and Cox showed almost similar results for the baseline survival probabilities, but results with the neural network were different: higher probabilities up to the 4th year, then comparable with the other two methods. Estimates from Cox proportional hazards and the neural network with three nodes in hidden layer were compared with the estimate from the Kaplan-Meier estimator as the gold standard. Neither comparison showed statistically significant differences. The standard error ratio of the two estimate groups by Cox and the neural network to Kaplan-Meier were no significant differences, it indicated that the neural network was more accurate. Although we do not suggest neural network methods to estimate the baseline survival probability, it seems these models is more accurately estimated as compared with the Cox proportional hazards, especially with today`s advanced computer sciences that allow complex calculations. These methods are preferable because they lack the limitations of conventional models and obviate the need for unnecessary assumptions including those related to the proportionality of hazards and linearity.
 
 
 
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