Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 52 59 EN Mahboubeh Rasouli Department of Biostatistics, Public Health school, Iran University of Medical Sciences, Tehran, Iran Mahmoodreza Ghadimi Department of Statistics, Iranian Social Security Organization, Tehran, Iran Masoomeh Shohani Department of Nursing, Faculty of Allied Medical Sciences, Ilam University of Medical Sciences, Ilam, Iran Asieh Ashouri Guilan Interventional Cardiovascular Research Center, Heshmat Hospital, Guilan University of Medical Sciences, Rasht, Iran Samaneh Hosseinzadeh Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran Kazem Mohammad Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Mahmood Mahmoodi Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran 2016 12 25 Background & Aim: Esophageal cancer is one of the main common causes of death. The high prevalence of esophageal cancer in northern Iran is an important public health problem. The main aim of this paper was to assess the factors affecting survival of  atients with esophageal cancer in neighbor provinces around the Caspian Sea using Weibull mixture cure model and mixture cure model based on a non-proportional hazard. Methods & Materials: This prospective study was designed to gather data of esophageal cancer from the Babol cancer registry, Iran, registered during 1990 to 1991. The study cases were also followed for a period of 15 years up to 2006. Mixture cure model via non-proportional hazard modeling was used to calculate cure fraction and investigate the factors responsible for the cure probability of patients. Estimates were obtained by maximization of the likelihood via SAS proc NLMIXED. Results: The median survival time was about 9 months and survival probability in 1, 3, and 5 years following diagnosis were 23%, 15% and 13%, respectively. The family history affected the cured fraction independently of its effect on the early outcome  In addition, it had significant effect on the probability of uncured state in the both models. Conclusion: The results demonstrated the great potential in cure modeling survival data via nonproportional hazard model compared to Weibull mixture cure model. https://jbe.tums.ac.ir/index.php/jbe/article/view/78 https://jbe.tums.ac.ir/index.php/jbe/article/download/78/55

Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 60 67 EN Hossein Ali Nikbakht Deputy of Health, Babol University of Medical Sciences, Babol, Iran Seyed Reza Hosseini Associate Professor, Social Determinants of Health Research Center, Babol University of Medical Sciences, Babol, Iran Heidar Sharifi-Fathabad Miandoab Health Center, Urmia University of Medical Sciences, Urmia, Iran Amin Daemi Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran Rahmat Habibzade Deputy of Health, Babol University of Medical Sciences, Babol, Iran Saber Ghaffari-Fam School of Nursing, Urmia University of Medical Sciences, Urmia, Iran 2016 12 25 Background & Aim: Nowadays tuberculosis (TB) is one of the public health concerns in Iran. The present study aimed to examine the clinical epidemiology and treatment findings of tuberculosis in Babol, Northern Iran. Methods & Materials: This cross-sectional study was carried out on medical records of tuberculosis registry pertained to Health Center of Babol, Mazandaran province, Iran. The investigated variables included demographic characteristics and some clinical patterns. To present the findings the descriptive statistics such as mean (standard deviation, SD) and frequency (and relative frequency) were used. Analytical statistics was applied by using chi-square test and independent samples Student’s t-test. Results: The average age of 200 patients infected with tuberculosis was 47.5 years (SD = 21.4), and 58.5% of the cases were male. In both genders, age groups 18-38 years comprised the greatest percentage. During the 5 years study period, 95% of the patients received treatment protocol 1 (including new cases with positive smear, negative smear, and extra-pulmonary). At the end of treatment, 90.5% were improved or treatment period was completed. The most important clinical symptoms in referring the patients to the therapeutic centers were cough (75.1%) and fever (60.9%). Conclusion: Education and giving information to general population about the most important clinical symptoms of tuberculosis such as fever and cough might be effective in early detection and prevention of Mycobacterium tuberculosis. Then effective treatment might decrease the burden of the disease. https://jbe.tums.ac.ir/index.php/jbe/article/view/79 https://jbe.tums.ac.ir/index.php/jbe/article/download/79/56

Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 68 75 EN Mitra Rahimzadeh Research Center for Social Determinations of Health, Alborz University of Medical Sciences, Karaj, Iran Behrooz Kavehie National Organization for Educational Testing (NOET) and University of Social Welfare and Rehabilitation Science (USWR), Tehran, Iran 2016 12 25 Background & Aim: In the survival data with Long-term survivors the event has not occurred for all the patients despite long-term follow-up, so the survival time for a certain percent is censored at the  end  of the  study.  Mixture  cure  model  was  introduced  by Boag,  1949  for  reaching  a  more efficient analysis of this set of data. Because of some disadvantages of this model non-mixture cure model was introduced by Chen, 1999, which became well-known promotion time cure model. This model was based on the latent variable distribution  of N. Non mixture cure models has obtained much  attention  after the introduction  of the latent activating  Scheme  of Cooner,  2007, in recent decades, and diverse distributions have been introduced for latent variable. Methods  & Materials:  In this article,  generalized  Poisson- inverse  Gaussian  distribution  (GPIG) will be presented for the latent variable of N, and the novel model which is obtained will be utilized in analyzing long-term survival data caused by skin cancer. To estimate the model parameters with Bayesian  approach,  numerical  methods  of  Monte  Carlo  Markov  chain  will  be  applied.  The comparison drawn between the models is on the basis of deviance information criteria (DIC). The model with the least DIC will be selected as the best model. Results: The introduced  model  with GPIG, with deviation  criterion  of 411.775, had best fitness than  Poisson  and  Poisson-inverse  Gaussian  distribution  with  deviation  criterion  of 426.243  and 414.673, respectively. Conclusion: In the analyzing long-term survivors, to overcome high skewness and over dispersion using distributions that consist of parameters to estimate these statistics may improve the fitness of model. Using distributions which are converted to simpler distributions in special occasions, can be applied as a criterion for comparing other models. https://jbe.tums.ac.ir/index.php/jbe/article/view/80 https://jbe.tums.ac.ir/index.php/jbe/article/download/80/57

Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 76 80 EN Shivalingappa Javali Department of Community Medicine, USM-KLE-International Medical Program, Nehrunagar, Belgaum, India Mohan Anantarao Sunkad Department of Community Medicine, USM-KLE-International Medical Program, Nehrunagar, Belgaum, India 2016 12 25 Background  & Aim: The objective  of our study was to find out the awareness, inclination  and desire to apply the biostatistics as a tool in their areas of work by healthcare professionals. Methods   &  Materials:   A  cross-sectional   study  was  done  using  self-administered,   validated questionnaire,  among the faculty,  resident  doctors and internees  of medical  college,  physiotherapy college, dental college and nursing college. Study was done in North Karnataka, India, during 2012-13. Results: Out of a total of 500 questionnaires  that were distributed  among participants,  only 460 questionnaires  were received with a dropout rate of 8%. The response rate was 92%. Most of the respondents believed that the biostatistics is more difficult than other subjects of medical sciences. The total mean perception of knowledge scores was 21.2 ± 4.26 and total mean attitude scores was 33.4 ± 6.78 and were statistically significant (P < 0.05). Conclusion:  The study has brought out the fact that “biostatistics”  is a difficult subject, more of mathematics  and  is  best  left  to  experts.  However  the  respondents  have  felt  “biostatistics”  an important part of evidence based medicine and a necessary skill for healthcare professional. https://jbe.tums.ac.ir/index.php/jbe/article/view/81 https://jbe.tums.ac.ir/index.php/jbe/article/download/81/58

Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 81 87 EN Awol Seid Department of Statistics, College of Computing and Informatics, Haramaya University, Dire Dawa, Ethiopia 2016 12 26 2016 12 26 Background & Aim: Multistate models are systems of multivariate survival data where individuals move through a series of  istinct states following certain paths of possible transitions. Such models provide a relevant tool for studying observations of a continuous time process at arbitrary times. The aim of this study was to model the transitions from a healthy (hypertension free) state to an illness (hypertension) state of a hypertensive patient under treatment. Methods & Materials: In this article, the application of multistate modeling using hypertension data is demonstrated. Hospital data were obtained for a cohort of 353 patients from Jimma University Hospital, Ethiopia. Results: Three states of the Markov process are defined based on the WHO guideline of high blood pressure, state 1 (BP < 140/90 mmHg), state 2 (BP ≥ 140/90 mmHg) and state 3 (dropout). The first state is termed as a healthy state, the second an illness state and the third one is an absorbing state. Initially, the state transition intensities and state occupation probabilities are estimated with no covariate. Then, the effect of gender and family history of hypertension on the state transition intensities are evaluated separately and jointly using proportional intensities model. Conclusion: The study indicates that gender has a significant effect on the transition intensities but not family history ofhypertension. https://jbe.tums.ac.ir/index.php/jbe/article/view/82 https://jbe.tums.ac.ir/index.php/jbe/article/download/82/48

Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 88 97 EN Maryam Nazemipour Department of Epidemiology and Biostatistics, School of Public Health, International Campus, Tehran University of Medical Sciences, Tehran, Iran Abdol-Mohammad Kajbafzadeh Pediatric Urology Research Center, Department of Pediatric Urology, Children’s Hospital Medical Center, Tehran University of Medical Sciences, Tehran, Iran Kazem Mohammad Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Abbas Rahimi Foroushani Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Maryam SeyedTabib Department of Epidemiology and Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran Ali Nazemipour Department of Computer Engineering, Sharif University of Technology, Tehran, Iran Mahmood Mahmoudi Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran 2016 12 26 2016 12 26 Background & Aim: We aimed to describe a standard survival analysis, so that we can analyze some factors related to the time of occurrence of different types of reflux (unilateral-left, unilateralright, and bilateral) in children with antenatal hydronephrosis (ANH) and to provide an approach taking competing risks into account. Methods & Materials: We used data of 193 children that was collected from Pediatric Urology Research Center of Children’s Hospital Medical Center, affiliated to Tehran University of Medical Sciences, Iran. The cause-specific and subdistribution hazard were computed. P < 0.05 was considered as statistically significant. R packages were used for analyzing the data. Results: Among these infants (36 girls, 157 boys), 117 (68%) cases had bilateral reflux as the event of interest. The variables “Sex” and “Direction of ANH (in bilateral level)” were significantly different (P<0.05), while “Severity of ANH (in moderate level)” and “Number of other kidney diseases beside ANH and vesicoureteral reflux (VUR)” were borderline. The cumulative incidence derived from the competing risks approach was at a lower level of estimate in comparison with the Kaplan-Meier method. The cumulative incidence curve depicted for the bilateral reflux in subgroups of the sex variable, confirmed the effect of sex. Conclusion: In the competing risks framework, it is inappropriate to use the Cox and Kaplan-Meier methods, which do not take competing risks into account. Multivariate regression model like the subdistribution hazard model besides the cumulative incidence curve are recommended. https://jbe.tums.ac.ir/index.php/jbe/article/view/83 https://jbe.tums.ac.ir/index.php/jbe/article/download/83/49

Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 98 103 EN Elham Ahmadnezhad National Institute of Health Research, Tehran University of Medical Sciences, Tehran, Iran Zhaleh Abdi Department of Health Expenditure, National Institute of Health Research, Tehran University of Medical Sciences, Tehran, Iran Abolhassan Safdari Department of Infectious Disease, Zahedan University of Medical Sciences, Zahedan, Iran Farshid Fayyaz-Jahani Academic Center for Education, Culture and Research Center, Urmia, Iran Sheida Malek-Afzali Department of Environment and occupational Health center, Ministry of Health, Tehran, Iran Soraya Fathollahi Department of Health in Disasters and Emergencies, International Campus, Tehran University of Medical Sciences, Tehran, Iran 2016 12 26 2016 12 26 Background & Aim: The aim of the study was to define the epidemiological characteristics of most important infectious diseases in Iran in recent decades. Methods & Materials: This was a situation trend analysis of infectious diseases (vector and water borne disease, and food borne diseases) in recent decades based on data availability. Three significance levels were used for Mann-Kendall test (90%, 95% and 99%). Results: The morbidities of most studied diseases had decreased in whole of the country. Unlike other diseases, coetaneous leishmaniasis had not followed the deacreasing trend. In terms of location, Khorasan-e-Shomali was followed the increasing pattern for in four out of six disaeses [malaria, leishmaniasis (coetaneous and visceral), and typhoid]. Conclusion: In conclusion, there is a significant decreasing trend of most important infectious diseases in Iran. Nevertheless, climate change is already happening and would influence the diseases trends. Hence, developing and implementing adaptation strate ies should be considered. https://jbe.tums.ac.ir/index.php/jbe/article/view/84 https://jbe.tums.ac.ir/index.php/jbe/article/download/84/50

Tehran University of Medical Sciences Journal of Biostatistics and Epidemiology 2383-4196 2 2 2016 12 26 104 110 EN Morteza Rostami Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran Behshid Garrusi Department of Community Medicine, Neuroscience Research Center, Afzallipour Medical School, Kerman University of Medical Sciences, Kerman, Iran Mohamad Reza Baneshi Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran 2016 12 26 2016 12 26 Background & Aim: In many medical studies, one data set is used to construct the model, and to test its performance. This approach is prone to over optimization, and leads to statistics with low chance of external validity. Data splitting can be used to create training and test sets but the cost is reduction in power. The aim of this study was to demonstrate the ability of bootstrap aggregating (bagging) in improving performance of classification and regression tree (CART) models. Methods & Materials: CART was applied on a sample of 404 subjects, to identify the factors that encourage people to change their body shape by cosmetic surgeries. Comparing known status of subjects with predicted group, sensitivity and specificity of models were compared. Firstly, all data was used to construct the tree and to test its performance. Secondly, model was fitted on half of data and tested on the second half. Thirdly, bagging was applied in which we drew 100 bootstrap samples. Using each bootstrap data, a tree was constr cted and its performance was tested on the unselected subjects. Final group prediction for each subject was determined following majority voting. Results: When the whole data was used the overall accuracy was 59%. In the test data set and bagging, accuracy reduced to 53% and 56%. Corresponding figures in terms of sensitivity were 60%, 52%, and 55%, respectively. Conclusion: Bagging corrected performance estimates for over optimization. Bagging method produces statistics which has higher chance for external validity. https://jbe.tums.ac.ir/index.php/jbe/article/view/85 https://jbe.tums.ac.ir/index.php/jbe/article/download/85/51