Iranian Journal of

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Background & Objectives: Cancer has been traditionally regarded as a fatal disease it is a major public health problem in many countries throughout the world. In recent years, cancer morbidity and mortality has increased in our country and notably stomach cancer now ranks second or third among all cancers types with regard to morbidity.
Methods: Our study included all gastric cancer patients registered in the cancer registry of Fars province. The patients' survival status was followed using phone calls and death records from hospitals, other medical centers, and the city's cemetery. Data analysis involved the use of the nonparametric Kaplan-Meier and Cox proportional hazards models and was performed with the software package SPSS V.13.
Results: Of the 442 patients with gastric cancer, 303 cases (68.6 percents) were male, and the mean age of patients was 58.41 years (SD=14.46). In univariate analysis with the KM method, a statistically significant association was found between survival rates and the following factors: age at diagnosis (P<0.001), tumor grade (P=0.009), presence of metastases (P<0.001), and type of the initial treatment (P=<0.001). Factors without a significant relationship with the survival rate included sex, ethnicity, weight, BMI, tobacco use, history of cancer in close or distant relatives, place of residence, number of children, marital status, occupation, and income. In Cox regression, only age at diagnosis, tumor grade, and the presence of metastases showed a significant association with survival rates.
Conclusions: Our results imply that early detection of cancer at a lower age and in lower tumor grades could be important for increasing the patients' life expectancy.

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Background & Objective: Clinically Chronic Allograft Dysfunction (CAD) is characterized by a progressive decline in Glomerular Filtration Rate (GFR) over time, the pattern of disease progression determined by the five-stage model. In this paper, we used Erlang and Hypo-exponential distributions as Phase- Type distributions to describe hazard of kidney failure at over time in RTR with CAD.
Methods: In a single-center retrospective study, 214 patients with RTR with CAD were investigated at the Emam Hospital of Urmia University of Medical Sciences from 1997 to 2005. Kidney function at each visit assessed with GFR and categorized based on NKF and KCOQI staging system.
Results: The estimated hazard rates of disease progression from stage 1 to 2 , 0.0378 from stage 2 to 3 ,0.04 from stage 3 to 4 , 0.0458 and from stage 4 to 5 0.0541 were respectively based on each expected month . This estimates yield a mean waiting time of disease progression from stage 1 to Kidney failure or dialysis 91.63 month. The 18th, 58th, 118th and 155th months of death-censored graft survival were 0.99, 0.75, 0.25 and 0.10 respectively.
Conclusions: The findings of this study are compatible with hyperfiltration theory in chronic kidney disease and give us more detailed information about the daynamic process of disease which would help to manage it effictevliy.

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Background & Objective: Using parametric models is common approach in survival analysis. In the recent years, artificial neural network (ANN) models have increasingly used in survival prediction. The aim of this study was to predict of survival rate of patients with gastric cancer by using a parametric regression and ANN models and compare these methods.
Methods: We used the data of 436 gastric cancer patients from a cancer registry in Tehran between 2002-2007. All patients had a confirmed diagnosis. Data were randomly divided into two groups: training and testing (or validation) set. For analysis of data we used a parametric model (exponential, Weibull, normal, lognormal, logistic and log-logistic models) and a three layer ANN model. In order to compare of the prediction of two models, we used the area under receiver operating characteristic (AUROC) curve, classification table and concordance index.
Results: The prediction accuracy of the ANN and the parametric (Weibull) models were 79.45% and 73.97% respectively. The AUROC for the ANN and the Weibull models were 0.815 and 0.748 respectively.
Conclusions: The ANN had a better predictions than the Weibull model. Thus it is suggested to use of the ANN model survival prediction in field of cancer.

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Background & Objectives: Cholera is always being considered as a public health threat in poor and developing countries. However outbreaks of cholera are not very common in central area of Iran in 2008 district health authority reported a cluster of diarrhea cases. We investigated this cluster to identify the etiological agent, source of transmission and propose control measures.
Methods: We analyzed the data of total of 1219 patients with colorectal cancer who registered between 1 January 2002 to 1 October 2007. Data were analyzed using univariate and multivariate Accelerated Failure Time (AFT) parametric survival model with frailty, utilizing STATA statistical software.
Results: In the univariate analysis for age at diagnosis, gender, marital status, race and education level, the survival of patients with colon cancer were approximately between half to one fourth and for BMI, alcohol history, Inflammatory Bowel Disease (IBD), familial history of cancer and the pathologic stage of tumor, the survival of patients with colon cancer were significantly (between 0.12 to 0.56 times) shorter than those patients with rectal cancer. In the multivariate analysis, for age at diagnosis (45-65 years), there was significant difference between colon and rectum cancer. But for BMI, alcohol history, IBD and pathologic stage there were not significant differences. The adjusted survival and 1, 2, 3, 4 and 5 year survival of patients with rectal cancer were better than those with colon cancer.
Conclusions: Site-specific evaluation of colon and rectum could give a better perspective of factors affecting these cancers. It may help to design of clinical trials, better diagnosis of diseases and optimal administration of specific treatments.

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Background and Objectives: Each year almost 400,000 people are diagnosed with oesophageal cancer worldwide. Wide variation in incidence has been reported both between countries and in different ethnic groups and populations within a country. The area with the highest reported incidence for oesophageal cancer is the so-called Asian ‘oesophageal cancer belt’, which stretches from eastern Turkey through north-eastern Iran, northern Afghanistan and southern Russia to northern China. In the high risk area of Gonbad in Iran, world age-standardised rates are more than 200 per 100,000 and the male/female ratio is reported as 0.8:1.0.This study aimed to assess the risk factors and demographic factors influencing survival of patients with esophageal cancer in north of Iran using weibull and log-logistic regression models.
 Methods: Demographic and clinical data of 359 patients with confirmed diagnosis of esophageal cancer from Babol Cancer registry utilized for our model. parametric and weibull models were employed to analyze the data. The Akaike information criterion (AIC) was also considered as a criterion to select the best model(s). All p values as 0.05 were considered as statistically significant.
Results: The sample study consisted of 62.7% men and 37.3% women. Estimated survival rates in 1, 3, and 5 years following diagnosis were 23%, 15%, and 13% respectively. According to AIC criterion, the hazard rate of non-monotonic and rejection proportional hazards assumption (p<0.05), log-logistic model was more efficient than weibull model. Family history of having cancer in patients showed a significant difference in both models.
Conclusion: It is concluded that early detection of people with a family history of cancer can be effective as an important factor in reducing the risk of death in patients with esophageal cancer.

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Background & Objectives: Despite decreasing the trend of coronary artery diseases in developed countries and outstanding improvements in clinical management of these patients, case fatality rate after an acute myocardial infarction (AMI) remains high in both genders. Identifying predicting factors of short-term survival in patients with AMI may play an important role in reducing mortality in these patients.
Methods: In this cohort study, all patients with acute myocardial infarction (AMI) admitted to all hospitals in Isfahan, Iran, during 2000-2008 which registered in Isfahan cardiovascular research Institute were analyzed. We used Cox regression models, uni- and multi-variable analysis. 
Results: Within the study period, 8800 AMI patients (73.6% male) were admitted with mean age of 61.85±12.5, and overall 28-day survival of 90.5%. Relative risk (RR) of death for 50-70 years old patients was 2.5 (CI:2-3.1), for over 70 years old RR=5 (CI:4-6.3), for women RR=1.7 (CI:1.5-1.9), for patients who had not received streptokinase RR=0.9 (CI:0.8-1.1), for inferior MI RR=4.2 (CI:2.2-7.8) and for anterior MI, RR was equal to 7.2 (CI:4-13.3).
Conclusion: Recognizing the predicting factors of short-term survival of AMI patients may help health professionals to provide better healthcare services for more at risk patients, i.e. elderly, women and patients with an anterior MI.

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Background & Objectives: Peritoneal dialysis is one of the most common types of dialysis in patients with renal failure. However multivariate analysis such as log- rank test and Cox have usually used to evaluate association of risk factors in survival of this group of patients, the aim of this study was to perform of Weibull, Gamma, Lognormal and Logistic Mixture cure models in survival analysis of these patients.
Methods: Data of 433 patients undergoing CAPD who registered in two centers in Tehran, Iran between 1997 to 2009 were used in this analysis. We investigated center, gender, age, cholesterol, Low Density Lipoprotein (LDL), High density lipoprotein (HDL), triglyceride, albumin, hemoglobin, creatinine, Fasting Blood Sugar (FBS), calcium and phosphorous as variables effect with Kaplan-Meier and cure model. CUREREGR module was used for survival analysis.
Results: Comparison of AIC (Akaike Information Criterion) of Weibull, Gama, Lognormal and Logistic Mixture cure models showed that Weibull distribution AIC is lower for almost all variables than other distributions. Weibull distribution has better fitness for data than others. In the multivariate Weibull model, age and albumin variables had significant effect on long-term survival of patients (P<0.01). Triglycerides effect on long-term survival had borderline (P = 0.065). Also HDL, FBS and calcium were significant on short term survival (P<0.01) but significance of LDL was borderline (P=0.088).
Conclusion: Cure models have the ability to analyze dialysis patients' survival data and can differentiate long-term survival from short- term survival. The interpretation of survival data with these statistical models could be more accurate and would help to make better prediction for patients by health care professionals.

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Background & Objectives: Identifying the important influential factors is a great challenge in oncology studies. Decision tree is one of methods that could be used to evaluate the prognostic factors and classifying the patients' homogeneously. This method identifies the main prognostic factors and then determines the subgroups of patients based on those prognostic factors. The aim of this study was to assess the prognostic factors and homogeneous subgroups of colorectal patient through survival tree.
Methods: Data collected from an observational of 739 colorectal patients registered in the cancer registry affiliated to the center of Research Center of Gastroenterology and Liver Disease (RCGLD), Shahid Beheshti Medical University, Tehran, Iran. Death was the interested event and the survival time was calculated from date of diagnosis until occurrence of event (or censoring) in months. Finally we used decision tree based method for classifying and analyzing the data.
Results: Based on our result, decision tree identified four covariates as important prognostic factors in 0.05 significant levels: general stage of cancer, age of diagnosis, histology of tumor and morphology type of tumor. Also patients based on these prognostic factors divided into five homogeneous subgroups. The greater values of measure of separation (SEP) criterion support the appropriateness of this model for such the data.
Conclusion: Decision tree is powerful and intuitive method. It has a key feature that is in addition to evaluate the prognostic factors, provides the homogeneous subgroups for future analysis.

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Background & Objectives: Golestan province in Iran has been known as a high risk area for esophageal cancer (EC). This study was conducted to assess the population-based survival rate in EC patients in Golestan province of Iran.
Methods: In a longitudinal study, 223 EC patients registered in Golestan population-based cancer registry in 2007 and 2008 were recruited. Kaplan-Meier method was performed to calculate median survival and log rank test was also used to compare survival rates between subgroups of variables. Multivariate Cox regression model was employed to determine adjusted hazard ratios (AHR) for different variables.
Results: From 223 patient, 129 (57/8%) were male. The mean age of participants was 64/3 years. The median survival in our study was 11/08 months. Survival rates for 6, 12 and 36 months were 69%, 47% and 14%, respectively. The results of Cox regression analysis showed that the AHR for patients with metastasis stage (compared to those with localized stage) was 13.89 (95% CI: 7/93-24/32) and the AHR for workers (compared to clerks) was 2.4 (95% CI: 3/8-1/47).
Conclusion: Our results showed that survival rate of EC patients were higher than the rate reported in a previous study from this region. However the survival rate from this region seems still lower than those reported from developed countries. Implementation of appropriate screening programs in this region will result in early diagnosis of EC and consequently will increase survival rate in EC patients.

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Background & Objectives: Although several studies have been carried out for evaluation of the first birth interval, none of them has considered the presence of infertile women within the sample. Therefore, the aim of this study was to employ survival analysis to study the first birth interval and its determinant factors more accurately.
Methods: In Data from 1068 married women of reproductive age in west Azarbaijan province were considered in this investigation. Two-stage sampling design was used to collect data via a questionnaire, modified Gompertz model, a special kind of cure models, was employed in this study. For descriptive and analytical data analysis, SPSS 16 and R 2.12 were used respectively.
Results: In this study, the average interval between marriage and first birth was 3.9± 0.7 (± SD) years. Using modified Gompertz model, among all demographic factors only mother’s education had significant effect on the first birth interval so that with increasing mother’s educational level, the first birth interval had also increased. (P =0.007). In addition, the estimation of the proportion of women who did not have any children was 0.062 that showed a positive trend with increasing mother’s educational level.
Conclusion: This study revealed that due to the presence of infertility among married women the use of Modified Cured Gompertz model is an appropriate method for evaluation of the first birth intervals and it's determinant factors.

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Background & Objectives: Although the population of elderly is increasing in Iran, few studies carried out on this group. The aim of this study was to identify life expectancy and contributory risk factors for the Tehranian elderly of ages above 60 years.
Methods: Individuals above 60 years old whom were recruited in the primary phase of the Tehran Lipid and Glucose Study (TLGS) during 1998-2001 were followed up for 12 years and their vital status were registered (1998-2011). Age and sex mortality rates for age groups (60-69, 70-79, 80+) were calculated and by using Cox proportional hazard model the mean of survival time and hazard rates with respect to risk factors were estimated.
Results: Life expectancy for females and males after crossing 60 years of age reaches to 81 and 80 years, respectively without any statistically significant differences between these two groups. Cox model showed that diabetes, BMI>33Kg/m2 and non ischmecic heart disease reduced survival time in women significantly. While diabetes, smoking, hypertension, ischemic heart disease, history of MI, stroke or sudden death of father, brother or son, lack of physical activity and antihypertensive medications are among the hazardous risk factors for men.
 Conclusion: Among the variables studied, only three (ABC) of them were found as risk factors of women's life, while for men seven risk factors were identified. It seems that more studies are needed to determine the risk factors for women.

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  Background and Objectives : recent years, considerable attention has been paid to statistical models for classification of medical data according to various diseases and their outcomes. Artificial neural networks have been successfully used for pattern recognition and prediction since they are not based on prior assumptions in clinical studies. This study compared two statistical models, artificial neural network and logistic regression, to predict the survival of patients with breast cancer.

  Methods: Two models were applied on cancer registry data, Kerman, southeast of Iran, to predict survival. The data of 712 breast cancer patients in the age group 15 to 85 years was used in this study. The logistic regression and three-layer perceptron neural network models were compared in terms of predicting the survival. Sensitivity, specificity, prediction accuracy, and the area under ROC curve were used for comparing the two models.

  Results : In this study, the sensitivity and specificity of logistic regression and artificial neural network models were (0.594, 0.70) and (0.621, 0.723), respectively. Prediction accuracy and the area under ROC curve for two models were (0.688, 0.725) and (0.70, 0.725), respectively.

  Conclusion: Although there were insignificant differences in the performance of the two models for predicting the survival of the patients with breast cancer, the corresponding results of artificial neural network were more appropriate for predicting survival in such data.

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  Background and Objectives : Various studies have reported different survival rates of patients with gastric cancer in Iran, and there is no overall estimate of the survival rate. The aim of this study was to conduct a meta-analysis of one, three, and five-year survival rate of patients with gastric cancer in Iran.

  Methods: In this study, all of the national databases including Iran Medex, Magiran, SID, and Medlib and the English databases including Google Scholar and PubMed were searched by using the keywords “stomach cancer”, “survival rate” and other Persian and English synonymous keywords, in the period 1392-1339 . Then, all articles with inclusion criteria and acceptable quality were investigated. Der Simonian and Laird random effects models were used to combine the results of all studies. Other analyses including subgroup analysis, sensitivity analysis, and assessment of publication bias were performed by using the funnel plot, and Beg’s and Egger’s tests. Finally, the data was analyzed using STATA software.

  Results: Of the 235 articles found in the initial search, nine studies were eligible for this study. According to these studies, one, three and five-years survival rate of patients with gastric cancer was 0.57 (95% CI: 0.45-0.70), 0.29 (95% CI: 0.22-0.37), 0.17 (95% CI: 0.13-0.21), respectively.

  Conclusion : Researches conducted in different parts of Iran are limited and there are no exact statistics on the survival rate in other parts of Iran. Therefore, further studies in the whole country are required to obtain more precise estimates of the survival and factors affecting it.

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  Background & Objectives : Gastric cancer has a low survival and remains a serious threat to the health of human life, especially in developing countries such as Iran. The present study was performed to estimate the main effective factors in the survival rate of patients with gastric cancer in the Province of Kohgilouyeh & Boyerahmad.

  Methods: All cases of gastric cancer in Kohgiloyeh and Boyerahmad recorded in Provinces of Fars and Kohgiloyeh and Boyerahmad cancer registry were enrolled in this study. The impact of the independent variables on the survival was estimated by single and multivariate Cox regression controlled for the probable confounding variables. Survival analysis was performed using Kaplan Meier curves, the log-rank test, and Wilcoxon test to compare the results. Analysis of the data was performed by SPSS 19, and P-values less than 0.05 were considered significant.

 Results: Among the 348 studied patients, 75.6% were male and the rest (24.4%) were female. In general, in this study, 1, 2, 3, 4, and 5-year survival rate of the patients was 37, 27, 20, 19, and 18%, respectively. By combining these end variables in regression models, three risk groups were identified. In the high risk group, the cumulative survival rate was 0% at the end of the fifth year.

 Conclusion: Execution of the down-staging program through public education, considering the low survival rate in this province seems essential especially for high-risk groups such as farmers, ranchers and regional nomadic populations.

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  Background & Objectives : Management of time-dependent variables is the advantages of survival analysis. This study compares time-dependent and -independent variables in survival analysis in culling of dairy cows.

  Methods: In this historical cohort, 7067 dairy cows in the Province of Tehran were recruited. Cows were followed to the next calving or culling. Data on the occurrence of health disorders, calving season, parity, and milk production was obtained. Model 1 treated diseases as time-independent covariates. In models 2, up to 5 diseases were considered time-dependent covariates. For each observation, we split follow-up time in intervals each corresponding to a different lactation month using Lexis expansion of the original dataset. Model 2 assumed that an animal experienced a certain disease from the beginning of the occurrence of that disease by the end of the period. Model 3 assumed that cows were at risk from the begging of the study until the disease occurred (inverse of model 2). In models 4 and 5, an animal was assumed to experience a certain disease for 1 month if the disease occurred during this period. In Model 4 assumed diseases occurred only one time, and in model 5, multiple disease occurrences at different months were considered as different episodes.

  Results : AIC in model 1 and 5 was 10809 and 10366 moreover, BIC was 10926 and 10528. According to this numbers and the shape of the Cox-Snell Residuals, model 5 with Gompertz distribution was the best model.

  Conclusion : Models without time dependency tended to seriously underestimate the risk of a disease on culling.

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Background and Objectives: Breast cancer is one of the most common cancers among women and is the second main cause of death after lung cancer. The objective of this study was to use the Bayes model to analyze the prognostic effects on the survival of the women with breast cancer after surgery in the south of Iran.

Methods: The date was collected 1192 women who had breast cancer in Namazi Hospital Research Center between 2001 and 2006. The complete information of only 1148 of them was registered. Parametric Bayes and Bayes Cox methods were used. Considering 0.05 as the level of significance, the data analysis was done using the WinBUGS14 software.

Results: The mean age of the patients (at the time of diagnosis) was 47 years in this study. Cox one-variable analysis showed a significant relationship between survival and smoking (P=0.009), bone metastasis (P=0.01), the number of lymph nodes (P=0.001), the tumoral level of malignancy (P=0.001), the surgical method (P=0.015), financial status (P=0.025), and the tumor size (P=0.001). By fitting Bayes models the variables tumor size, level of malignancy and number of lymph nodes were significant.   

Conclusion: The results showed that clinicopathological features of cancer had a significant role in the survival of the patients.

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Background and Objectives: Colorectal cancer is the fourth leading cause of cancer death worldwide.  Annually 1430000 cases would be diagnosed and half of these people would die of the disease. In Iran, colorectal cancer is the fifth common cancer among men and is the thirdamong women. This study was designed to estimate survival rates for patients with colorectal cancer and related factors.  

Methods: During the 1384 to 1388 years 24,807 patients diagnosed with colorectal cancer were recorded in the Cancer Registry of the Ministry of Health and Medical Education. Age, gender, marital status, education, occupation, place of residence, tumor diagnosis, the clinical and demographic factors in colorectal cancer as effective on survival entered in Aalen’s additive hazard model and diagram Aalen's was used to study the effects of these factors over time. R 3.2.0 software was used for data analysis.

Results: Stage of tumor had a significant association with survival rates. In this study 1 to 5 year survival rate for patients with stage II tumors, was 100%, 98%, 96%, 93% and 93% respectively and for patients with stage III tumors 99%, 97%, 94%, 90% and 84%, respectively.

Conclusion: In spite of using Cox model in survival analysis by many researchers, Aalen’s model may yield new insights in prognostic studies of survival time of patients with colorectal cancer over time. Our results suggest that early detection of patients in primary stage is important to increase survival.

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Background and Objectives: Social determinants of health affect a wide range of health consequences. The aim of this study was to analyze the effects of social determinants of health factors on survival in patients with malignant brain tumors.

Methods: This cross-sectional retrospective study was done in Imam Khomeini and Shariati Hospitals in 2014. Based on inclusion criteria, the data of 148 patients were collected. The collected data included demographic information (including age, sex, education level, employment status, marital status, health insurance status, number of household members), information about the tumor and disease (stage / grade), The first and the last time of follow-up, type of selected treatment, and the duration of survival after treatment. We used SPSS 15 to analyze data.

Results: Our results showed a significant relationship between survival and variables such as the size of the household, education, employment status, and age. Patients with grade 3 tumors had a lower relative risk of dying while employed patients, patients in the age range 18-30 years, and male patients had a higher relative risk of dying (lower survival).

Conclusion: Lack of reliable databases and appropriate integration and communication between different organizations recording to patient data, and also probable sensitivity in obtaining personal information has led to the lack of systematic information about the impact of social determinants of health. it is recommended that a system of recording integrated information for different disease should be established in the country for designing informed policies based on the evidence.

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Background and Objectives: A small sample size can influence the results of statistical analysis. A reduction in the sample size may happen due to different reasons, such as loss of information, i.e. existing missing value in some variables. This study aimed to apply bootstrap and jackknife resampling methods in survival analysis of thalassemia major patients.

Methods: In this historical cohort study, the data of 296 patients with thalassemia major who were visited at Zafar Clinic, Tehran, from 1994 to 2013 were used. Parametric survival models were used to analyze the data. The log – normal survival model was selected as the best model and then the bootstrap and jackknife resampling algorithms were used for this model. Data analysis was carried out with the STATA 12.0 software.

Results: The results of the resampling methods showed that standard errors decreased and confidence intervals were shortened. In addition, the result of the bootstrap and jackknife resampling methods showed that age group and the relationship of the parents (P<0.001) were significant compared with the log-normal model (P>0.900).

Conclusion: Comparison of the confidence intervals suggests that the jackknife resampling method can be used when the sample size is small.

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Background and Objectives: The cancer of the pancreatic head and Ampulla of Vater is a malignant disease usually seen in advanced stages with symptoms caused by stomach and biliary obstruction. Curative treatment is possible in the early stage. Unfortunately, most symptomatic patients are in the advanced stage and have an unrespectable tumor; therefore, they should undergo palliative surgery. This study was performed to determine the complications and survival rate of patients who underwent palliative surgery for advanced stages of cancer in the Ampulla Vater and pancreatic head.

Methods: In this study, 49 patients with advanced stages of cancer in the Ampulla of Vater and pancreatic head who had undergone palliative surgery from 2003 to 2014 at Baqiyatallah Hospital were studied and the complications and survival rate were determined.

Results: Eleven patients (22.44%) underwent biliary bypass, 6 (12.24%) underwent gastric bypass, and 32 (65.32) underwent both procedures. Twelve (24.49%) patients developed complications. Anastomotic leak and peritonitis were the most common complications seen in 6 (12.2%). Seven patients (14.28%) died in the hospital. The mean survival was 5.47 ± 8.38 months. Upon follow up, survival was significantly longer in older patients (P=0.01).

Conclusion: In one-fourth of the patients with advanced stages of cancer, palliative surgery of the pancreatic head and Ampulla of Vater caused complications, and the mean survival rate was less than six months. The results of this study recommend the use of less invasive procedures such as biliary stenting in the advanced stages of the disease.