Iranian Journal of

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Epidemiological studies of cancer is the corner stone of cancer control plans and necessary for setting goals, monitoring the progress, and evaluating the results of control efforts. Cancer is a generic name for a number of diseases that have different etiology, natural history, and outcome. Thus, control activities for each cancer is different and requires varied approaches. Primary prevention, i.e., controlling the initiation of cancers is now possible for a number of cancers including lung, stomach, liver, and cervix by controlling the use of tobacco, and infections with Helicobacter pylori, Hepatitis C, and Human papilloma viruses. Secondary prevention, i.e., early detection is mostly effective for the cancers of the breast (mammography), cervix (Pap test), prostate (digital rectal exam and PSA testing), colon and rectum (Colon- and Sigmoidscopy), and melanoma of the skin (clinical examination of the skin). Effective treatment is now possible for a large number of cancers with arrays of new medications such as Tamoxifen and Herceptin for breast cancer, Avastin for Colorectal and other cancers, and so on. Tertiary prevention, i.e., rehabilitation and hospice care is a necessary part of cancer control that is generally neglected. Cancer is a familial disease and when it struck, it affects the whole family. Health education and social support for the patients and their families is an integral part of cancer control activities and must be present in any effective cancer control program. Tertiary prevention not only includes proper palliative care, but also education and support for proper nutrition and improvement of the quality of life for the patient and the family.

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Background & Objectives: Breast cancer is a common malignancy in women in many parts of the world. The incidence of breast cancer in Iranian women is growing. Iranian patients are relatively younger than their western counterparts. We conducted a case-control study to determine roles of reproductive factors for breast cancer among women in Iran.
Methods: A hospital based case-control study was conducted in 2004 at a teaching hospital in Tehran, Iran. A total of 303 cases of breast cancer and 303 healthy controls were interviewed. Cases were identified through the oncology department of a university hospital and controls were recruited from other wards or out-patients clinics at the same hospital. Controls were matched to cases on age. Demographic and reproductive data were ascertained by personal interview using a structured questionnaire. Informed consent was obtained from cases and controls. Odds ratios and 95% confidence intervals for breast cancer were derived using logistic regression analysis.
Results: Mean ±SD age of cases and controls was 48.8 ±9.8 and 50.2 ± 11.1 years, respectively (range 24-84). The final model constructed after multivariate analysis indicated that factors such as never being married, menopause, older age at first live birth, parity, use of oral contraceptives, and history of chest X-ray between adolescence and the age of 30 yrs were significantly associated with breast cancer. Variables such as higher education, early age at menarche, abortion, breast feeding and its duration did not constitute significant risk factors.
Conclusions: Marital status, history of chest X-ray between adolescence and the age of 30, number of live births, and age at first live birth, menopause, and oral contraceptive use seem to increase the risk of developing breast cancer among women in Iran.

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Background and Objectives: Logistic regression is one of the most widely used generalized linear models for analysis of the relationships between one or more explanatory variables and a categorical response. Strong correlations among explanatory variables (multicollinearity) reduce the efficiency of model to a considerable degree. In this study we used latent variables to reduce the effects of multicollinearity in the analysis of a case-control study.
Methods: Our data came from a case-control study in which 300 women with breast cancer were compared to 300 controls. Five highly correlated quantitative variables were selected to assess the effect of multicollinearity. First, an ordinary logistic regression model was fitted to the data. Then, to remove the effect of multicollinearity, two latent variables were generated using factor analysis and principal components analysis methods. Parameters of logistic regression were estimated using these latent as explanatory variables. We used the estimated standard errors of the parameters to compare the efficiency of models.
Results: The logistic regression based on five primary variables produced unusual odds ratio estimates for age at first pregnancy (OR=67960, 95%CI: 10184-453503) and for total length of breast feeding (OR=0). On the other hand, the parameters estimated for logistic regression on latent variables generated by both factor analysis and principal components analysis were statistically significant (P<0.003). The standard errors were smaller than with ordinary logistic regression on original variables. The factors and components generated by the two methods explained at least 85% of the total variance.
Conclusions: This research showed that the standard errors of the estimated parameters in logistic regression based on latent variables were considerably smaller than that of model for original variables. Therefore models including latent variables could be more efficient when there is multicollinearity among the risk factors for breast cancer.

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Background and objectives: There is growing interest in assessing gene-environment interaction in the course of case-control studies. Difficulties related to the sampling of controls have led to the development of a range of non-traditional methods that do not require controls for estimating gene-environment interaction. One of these new modalities is the case-only approach, in which the assessment of gene-environment interaction is based on information from the cases only. The present article describes the application of this approach to data from breast cancer patients and compares its efficacy with that of a traditional case-control analysis.
Methods: We used age at first pregnancy, number of live birth, menopause and the total number of post-menopausal years as the "environment" factors and family history of breast cancer as the "gene" factor. We computed standard errors, 95% confidence intervals and (-2 log likelihood) to compare efficiency between case-control and case-only analyses.
Results: We observed significant interaction between menopause and family history of breast cancer by both methods (OR=4.32 CI: 1.10-16.90 for case-control analysis & OR=3.40 CI: 1.17-9.87 for case-only analysis). There was also a significant interaction effect between total years after menopause and family history of breast cancer (OR=1.07 CI: 0.98-1.16 in case-control analysis & OR=1.07 CI: 1.01-1.12 in case-only analysis). The case-only approach yielded narrower confidence intervals for the odds ratio, and the (-2 log likelihood) values computed by this method were correspondingly smaller.
Conclusions: Comparison of confidence intervals and (-2 log likelihood) values shows that the estimation of gene-environment interaction in breast cancer would be more efficient with the case-only approach than with the traditional case-control analysis.

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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 & Objectives: Today, the quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Malignancies have a clinical and health importance in the world and Iran. Breast cancer has first order among women’s malignancies. Now, survival rate for this cancer is long. However Breast cancer has several complications that affected patient’s life. It is necessary that we studying the quality of life and related factors among this patients.
Methods: We conducted a cross-sectional study on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz.We used QLQ-C30 & QLQ-BR23 to assessment quality of life in these patients. We used univariate nonparametric tests and multiple linear regression model to identify associations between dependent variables and the quality of life and it’s different scales.All calculation performed by using SPSS.V.13.
Results: Mean age of patients was 48.27±11.42 with quality of life total score 64.92±24.28. Univariate analysis showed that occupation,duration of disease,grade of tumor,physical,emotional and cognitive functioning, also, symptoms such as fatigue,pain, nausea and vomiting , insomnia , constipation and financial difficulties, perspective were associated to quality of life. (P< 0.05). But in multivariate analysis, only occupation, menopause status, dyspnea , grade of tumor and financial difficulties perspective were related to quality of life (p<0.05).
Conclusions: With this finding, It is recommended that financial supports, also early detection are necessary for improvement of quality of life in these patients

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Background & Objectives: The repression of retinoic acid receptor-β2 (RARβ2) expression is a concerning aspect of breast cancer, which is often induced by hypermethylation at promoter of the gene. We aimed to explore the correlation of plasma folate, vitamin B12 and total homocysteine (tHcy) levels with hypermethylation status of RARβ2 gene among Iranian breast cancer patients.
Methods: The hypermethylation status was investigated in 137 specimens tissues from primary breast cancer patients aged 28-85 years thorough methylation-specific PCR.
Results: Hypermethylation at RARβ2 gene was observed in 36.5 %. The hypermthylated RARβ2 associated with younger age at diagnosis and negative family history of breast cancer. The plasma level of folate was found lower in cases aged ≥48 years with hypermethylated RARβ2 gene (P<0.05). In contrast the level of tHcy was shown higher in cases aged <48 y (P<0.05). The risk of hypermethylation at RARβ2 gene increased with low plasma levels of folate (OR=0.21, 95%CI: 0.05-0.88) and vitamin B12 (OR=0.04, 95%CI: 0.01-0.92) and high plasma level of tHcy (OR=7.55, 95%CI: 1.07-25.7) in cases older than 48y.
Conclusions: Low plasma levels of folate, Vitamin B12 and high plasma level of total homocysteine could have important roles as prognostic factors in hypermethylation status of RARβ2 gene in breast cancer.

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Background & Objectives: The Cox proportional-hazards regression and other parametric models model have achieved widespread use in the analysis of time-to-event data with censoring and covariates. However employing Bayesian method has not been widely used or discussed. The aim of this study was to evaluate the prognostic factors in using Bayesian interval censoring analysis.
Methods: This cohort study was based on 178 patients with gastric cancer from January 2003 to December 2007 admitted to Taleghani teaching hospital in Tehran. Known prognostic risk factors were entered into the analysis using Bayesian Weibull and Exponential models. The term DIC was employed to find best model.
Results: The results were showed survival rate depended on age of diagnosis and tumor size. Those patients who had early diagnosis and/or had smaller tumor size were in lower risk of death.
Conclusion: The age of diagnosis and tumor size of patients are important prognostic factors related to survival of patients with gastric cancer. Based on DIC, Bayesian analysis of the Weilbull model performed better than the Exponential model. As a result, if this cancer has been diagnosed early, the relative risk of death would reduce.

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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: Competing risk data is one of the multivarite survival data. Competing risk data can be modelled using copula function. In this study we propose a bayesian modelling approach of competing risk data using the copula function.
Methods: We used the data from colorectal cancer registyrarty in Tehran. After constructing likelihood function using Clayton copula by choosing appropriate prior distribution for parameters, we obtained the posterior distribution of parameters using the Metropolis-Hastings algorithms and Slice sampling.
Results: The results of univariate analysis showed that sex, histology of tumor, extent of wall penetration, lymph node metastasis, distant metastasis and pathological stage of tumor were significantly associated with colon cancer and sex, histology of tumor, lymph node metastasis, distant metastasis and pathological stage of tumor were were significantly related to rectal cancer. In the multivariate analysis, age at diagnosis, tumor grade and distant metastasis were significant prognostic factors for colon cancer and tumor grade and size of the tumor were significant prognostic factors of rectal cancer
Conclusions: As we showed some variables may have different impacts on colon and rectum cancers, consequently, further studies are needed to be conducted considering risk factors of these cancers separately.

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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: The experience of patients with breast cancer may vary in different cultures. The aim of this qualitative study was to explore the experiences of women with breast cancer in Iran.
Methods: Fifty one participants were recruited from a university-affiliated breast clinic in Tehran. In-depth interviews each lasting approximately one hour per participant were scheduled and conducted in a private room. The interviews intended to motivate the participants to reflect on their life experiences since the cancer diagnosis. The interviews were tape-recorded and were transcribed to elucidate the major themes encountered in the interviews.
Results: The mean age of patients was 48.8 years (SD = 10.5), 44 were married, one was single, and six were widowed or divorced. Forty-eight participants underwent radical mastectomy and 13 patients received breast-conserving surgery. Thirty-five (69%) patients received chemotherapy. Overall eight major themes emerged from the analysis. These were: importance of God and spiritual beliefs, importance of family support especially husbands and children during the diagnosis and treatment, difficult times during receiving mammography results, experiencing an ambiguous condition while losing their breasts, fear of recurrence, concerns about children, and chemotherapy as the worst experience during the course of treatment.

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Normal 0 false false false EN-US X-NONE AR-SA Background & Objectives: Human papillomavirus (HPV) infection seems to be the most common sexually transmitted infection. High-risk (HR) human papillomavirus (HPV) prevalence has been shown to correlate well with cervical cancer incidence rates. Since there is little known about the epidemiology of this infection in Tehran, we designed to estimate the prevalence of HPV in some areas in Tehran. 
Methods: Cervical specimens were obtained from 825 married women aged 21-59 years from the general population of Tehran, Iran according to the standardised protocol of the IARC International HPV surveys. HPV was detected using a GP5+/6+ PCR-based assay.
Results: HPV prevalence in the general population was 7.8% (5.1% of high-risk types), with no statistically significant variations by age. Cervical intraepithelial neoplasia was diagnosed in 4.1% of women, of whom 35.3% were HPV-positive. HPV16 was confirmed as the most common type among women with both normal (1.8%) and abnormal (8.8%) cytology. HPV positivity was significantly higher among divorced women, women in polygamous marriages and those reporting husbands' extramarital affairs.
Conclusion: However the prevalence of HPV seems not high in comparison with other international data, more molecular and seroepidemiological survey in national level needs to have a better perspective.

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Background & Objectives: The economic costs of cancer care are a burden to people diagnosed with cancer, their families, and society as a whole. Despite several studies about cancer in Iran, there is paucity of cost analysis in this area. The aim of this study was to estimate the cost of cancer subgroups in Kerman, Iran.
Methods: A retrospective analysis of administrative 223 diagnosed patients with different cancers was undertaken.
Results: Monthly average cost of cancer was 3.32 thousand US dollars (average exchange rate in 2010: 10308 Iranian rials= 1 US dollar). Breast cancer, with an average 4.30 thousand US dollars per month was the most expensive and cancer of male reproductive organs with average2.16 thousand US dollars were the cheapest cancer.
The hidden monthly cost of all types of cancer was 2 thousand US dollars, breast cancer, lung, blood and female reproductive organs were costly and brain and peripheral nerves cancer, gastrointestinal tract and prostate were medium and male reproductive organs cancer was less costly.
Conclusion: Economically impact and burden of cancer should be an important consideration in the health policy making in Iranian health service system.

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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: Cox regression model is one of the statistical methods in survival analysis. The use of smoothing techniques in Cox model makes the more accurate estimates for the parameters. Fractional polynomial is one of these techniques in Cox model. The aim of this study was to assess the effects of prognostic factors on survival of patients with gastric cancer using the fractional polynomial in Cox model and Cox proportional hazards.
Methods: Information of total of 216 patients with gastric cancer who underwent surgery in the gastroenterology ward of Taleghani Hospital in Tehran between 2003 and 2008 were included in this retrospective study. In this research, fractional polynomial in Cox model and Cox proportional hazards model were utilized for determining the effects of prognostic factors on patients’ survival time with gastric cancer. The SPSS version 18.0 and R version 2.14.1 were used for data analysis. These models were compared with Akaike information criterion.
 Results: The analysis of Cox proportional hazards and fractional polynomial models resulted in age at diagnosis and tumor size as prognostic factors on survival time of patients with gastric cancer independently (P<0.05). Also, Akaike information criterion was equal in both models.
Conclusion: In the present study, the Cox proportional hazards and fractional polynomial models led to similar results with equal Akaike information criterions. Using of smoothing methods helped us eliminate non-linear effects but it seemed more appropriate to use Cox proportional hazards model in medical data because of its’ ease of interpretation and capability of modeling in both continuous and discrete covariates.

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Background and Objectives: Colorectal cancer, as the third common cancer, is one of the main health problems in Iran. We assessed the burden of colorectal cancer, as one of the high-priority indices, in this cross-sectional study in Iran in 2008.

Methods: CANMOD software was used for calculation. The input data included the population of Iran, all-cause and colorectal cancer mortality rates, and incidence rate of colorectal cancer, which were all obtained from the Iran Statistic Center, Mortality Registry System, and Cancer Registry System.

 Results: The total burden of colorectal cancer according to DALY in Iran in 2008 was 52534 years in the total population. Years of lost life (YLL) amongst males and females were 26455 and 19887 years, respectively. Years lived with disability (YLD) were 3473 and 2719 years for males and females, respectively. The burden of colorectal cancer per 1000 population was 75.4 years for males and 65.7 years for females. The peak age of colorectal cancer burden rate was in the age group 45-79 years.

 Conclusion: The burden of the colorectal cancer in Iran has increased compared to the last study (2003) which is due to the increase in its incidence and the related mortality during this period. Due to the possibility of prevention and effective intervention, this cancer should be a priority in the health care system. However, the final judgment should be made after calculation of the burden of other cancers, diseases, and damages at the country level and their respective rankings.

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  Background & Objectives: Breast cancer is the most common cancer among women. Numerous factors are effective in the improvement of patients undergoing surgery in terms of preventing relapse or need for repeated treatment during 6 months after the surgery. This study aimed to determine the factors affecting improvement of patients undergoing surgery for breast cancer using a logistic regression model.

  Methods: In this study information of 150 patients were extracted from the surgical records of patients underwent surgery at the Cancer Institute of Tehran Imam Khomeini Hospital. Data were analyzed through SPSS software and using logistic regression models .

  Results: Of 150 studied patients, 18 patients (12%) were not fully recovered while 132 (88%) had complete remission. The mean age of the patients was 43 ± 7.5 years, 92.8% were married, and 87.3% had children. According to the results, the odds of non recovery increased by 1.26 times with each one-year increase in age, 5.3 times with each one lymph node involvement, and 8.67 times in the case of metastasis. Other variables, such as marital status, number of children, tumor size, and location of the metastasis showed no significant relationship.

  Conclusion : The Results showed that age at diagnosis, due to its relationship with metastases and number of involved lymph nodes can be directly or indirectly affect the outcome. Therefore, increasing the women's awareness about breast cancer seems to be necessary for early diagnosis which requires planning a sufficient screening program by health policy makers of the country.

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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.