<?xml version="1.0"?>
<Articles JournalTitle="Journal of Biostatistics and Epidemiology">
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Prediction of time to reflux using accelerated failure time model of Weibull distribution in children with antenatal hydronephrosis</title>
    <FirstPage>47</FirstPage>
    <LastPage>51</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Maryam</FirstName>
        <LastName>Nazemipour</LastName>
        <affiliation locale="en_US">Department of Epidemiology and Biostatistics, School of Public Health, International Campus, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Abdol-Mohammad</FirstName>
        <LastName>Kajbafzadeh</LastName>
        <affiliation locale="en_US">Pediatric Urology Research Center, Department of Pediatric Urology, Children&#x2019;s Hospital Medical Center, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Kazem</FirstName>
        <LastName>Mohammad</LastName>
        <affiliation locale="en_US">Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Mahmood</FirstName>
        <LastName>Mahmoudi</LastName>
        <affiliation locale="en_US">Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>07</Month>
        <Day>31</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: Prediction of time to reflux can aid healthcare providers and preparation programs. We constructed a risk prediction instrument for occurrence reflux in children with antenatal hydronephrosis.
Methods &amp; Materials: Demographic and clinical information was collected retrospectively in children with the antenatal hydronephrosis and mostly with reflux, followed at least 5 years. 
Results: Accelerated failure time model of data from 333 children was developed to assess the risk of time to reflux. Likelihood ratio tests of statistical significant were used to identify best fitting predictive function. Variables &#x201C;gender&#x201D;, &#x201C;Sr&#x201D;, and &#x201C;severity of ANH (in severe level)&#x201D; were highly significant (p&lt;0.05) in multivariate model, adjusting for some traditional risk factors.
Conclusion: This proposed risk probability model allows prediction of time to reflux for children with antenatal hydronephrosis to better inform parents from possible time of occurrence reflux and treatment strategies.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/207</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/207/158</pdf_url>
  </Article>
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Relationships between parents and adolescents after divorce in Tehran city</title>
    <FirstPage>52</FirstPage>
    <LastPage>60</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Jafar</FirstName>
        <LastName>Hezarjaribi</LastName>
        <affiliation locale="en_US">Department of Social Science, Allameh Tabataba'i University, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Maryam</FirstName>
        <LastName>Niyyati</LastName>
        <affiliation locale="en_US">Department of Social Science, Allameh Tabataba'i University, Tehran, Iran</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>06</Month>
        <Day>02</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: This research examines the change in the attitude and trust of adolescents to their parents after divorce. It seeks to find whether the attitude and trust between adolescents and their parents change after divorce?
Methods &amp; Materials: Participants in this study were 30 adolescents with divorced parents in Tehran; of these, 50% were boys and 50% girls. Interviews and questionnaires were used to collect the data. In general, 58 indicators were used to examine adolescents&#x2019; relationships with parents. The indicators are arranged in three dimensions of moderation, intimacy, and conflict.
Results: Testing the measures showed that the rate of talking with a teenager after divorce decreases and father's cry on his child increases. Moreover, the degree of father's disregard his teenager before and after divorce has not shown a significant difference. This issue is completely different about the relationship between mother and her teen.
Conclusion: The result of the study showed that in a divorce, the relationship between adolescent with the parent&#x2019;s changes, and the relationship between the adolescent and the father undergoes more changes in comparison to the relationship with mother. The survey also showed that attitudes and trust between adolescents and parents have changes as a result of divorce.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/195</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/195/156</pdf_url>
  </Article>
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Comparison of the accuracy of beta-binomial, multinomial, dirichlet-multinomial, and ordinal regression in modelling quality of life data</title>
    <FirstPage>61</FirstPage>
    <LastPage>71</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Ali</FirstName>
        <LastName>Ghanbari</LastName>
        <affiliation locale="en_US">Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Mir Saeed</FirstName>
        <LastName>Yekaninejad</LastName>
        <affiliation locale="en_US">Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Amir</FirstName>
        <LastName>Pakpour</LastName>
        <affiliation locale="en_US">Social Determinants of Health Research Center, Qazvin University of Medical Sciences, Shahid Bahonar Blvd, Qazvin, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Sobhan</FirstName>
        <LastName>Sanjari</LastName>
        <affiliation locale="en_US">Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Keramat</FirstName>
        <LastName>Nourijelyani</LastName>
        <affiliation locale="en_US">Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>08</Month>
        <Day>12</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: Questionnaires are used mostly as a tool in medical research. Due to the different varieties of questionnaires, we may face different score distributions. In many cases multiple linear regression assumptions are violated. Beta-binomial regression model has the high flexibility and compatibility with this situation. In previous studies there were no comparison between beta-binomial accuracy and other models to fitting quality of life data. So in this study, our aim is to compare the accuracy of models to prediction.
Methods &amp; Materials: In this cross-sectional study we collected the quality of life data from 511 healthy women in Qazvin, Iran. The data were used to compare accuracy of betabinomial model and with some other models. Since beta-binomial considers the discrete response variable, so it should be compared with other similar models which are mostly used such as multinomial, dirichlet-multinomial and ordinal regression models. The main method that we used in our study was cross-validation to determine the accuracy of different models. To compare the different aspects, vast variety of situations were made and considered.
Results: Regarding to the accuracy of models that were obtained by cross-validation in different situations, beta-binomial model had better accuracy among all models.
Conclusion: According to the results, we have concluded that beta-binomial model is more accurate in prediction and fitting to the quality of data than the other models. The main advantages of this model are its simplicity, more efficacy and accuracy than the similar models.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/210</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/210/159</pdf_url>
  </Article>
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Na&#xEF;ve Bayes evidence accumulation K-modes clustering: A new method for classifying binary data and its application on real data of injecting drug users</title>
    <FirstPage>72</FirstPage>
    <LastPage>78</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Zahra</FirstName>
        <LastName>Zamaninasab</LastName>
        <affiliation locale="en_US">HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Department of Biostatistics and Epidemiology, School of Public Health, Kerman university of Medical Sciences, Kerman, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Hamid</FirstName>
        <LastName>Sharifi</LastName>
        <affiliation locale="en_US">HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran AND Department of Biostatistics and Epidemiology, Faculty of Public Health, Kerman University of Medical Sciences, Kerman, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Abbas</FirstName>
        <LastName>Bahrampour</LastName>
        <affiliation locale="en_US">Modelling in Health Research Center, Institute for Futures Studies in Health, Department of Biostatistics and Epidemiology, Health Faculty, Kerman University of Medical Sciences, Kerman, Iran</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>04</Month>
        <Day>12</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: Clustering is the method of classifying discrete data such as Kmodes, and Na&#xEF;ve Bayes classifier is the classification to predict the unknown real classes. In this research, we improve the K-modes results by applying the Evidence Accumulation (EA) method to keep the initial mode vector to use in the Na&#xEF;ve Bayes EA K-Mode.
Methods &amp; Materials: The methods are applied to four real datasets, which the true classes are specified, for checking the external validity and purity of our methods. The free programming software R with package klaR for K-modes, EA, and package e1071 for Na&#xEF;ve Bayes is used. In addition, the methods are applied to the data of Injecting Drug Users (IDU) national dataset with sample size 2546.
Results: The EA K-modes algorithm applied to five real datasets then with the kept initial mode vector, rerun the K-modes. The results indicate the purity in the EA K-modes (0.544, 0.862, 0.914, 0.944, 0.625) has significant different with classic K-modes (0.497, 0.610, 0.404, 0.650, 0.625). Finally, we applied the Na&#xEF;ve Bayes classifier with prior probability finds in EA K-modes. For K=2 Na&#xEF;ve Bayes EA K-modes made better clustering (0.71, 0.873 against 0.625, 0.862 EA k-mode and 0.497, 0.61 K-mode).
Conclusion: In this paper, we proposed Na&#xEF;ve Bayes EA K-modes as a new method for clustering of binary data. Our new method leads to stable clustering compare with the previous studies. The Na&#xEF;ve Bayes EA K-modes method improves the purity and establishes a better separation.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/179</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/179/160</pdf_url>
  </Article>
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Small size at birth as a predictor of increased risk of childhood morbidity, mortality and malnutrition: Evidence from Bangladesh demographic and health survey</title>
    <FirstPage>79</FirstPage>
    <LastPage>90</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>M. Mazharul</FirstName>
        <LastName>Islam</LastName>
        <affiliation locale="en_US">Department of Statistics, College of Science, Sultan Qaboos University, Muscat, Sultanate of Oman</affiliation>
      </Author>
      <Author>
        <FirstName>Uzma</FirstName>
        <LastName>Marium</LastName>
        <affiliation locale="en_US">Oman Medical College, Shohar, Sultanate of Oman</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>06</Month>
        <Day>08</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: Physical size or weight at birth of an infant is an important biomarker of current and future health and development of the infant. The aim of this study is to examine the effect of small size at birth &#x2013; a proxy indicator of low birth weight - on childhood mortality, morbidity and malnutrition in Bangladesh.
Methods &amp; Materials: The data for the study come from the 2014 Bangladesh Demographic and Health Survey. A total of 4,897 live births with information on size at birth as reported by their mothers were included in the analysis. Both descriptive and multivariate statistical techniques were used for data analysis
Results: One in every five live births (20%) was reported to be small in size in Bangladesh. Children born with small size at birth have some distinct characteristics than average size babies. Significantly higher incidence of malnutrition, mortality and morbidity were found among small size babies compared to average size babies. The multivariate analysis identified small size at birth as a significant predictor of childhood malnutrition, mortality and morbidity from diarrhea. Small size infants had 1.6 to 2.2 times higher risk of stunting, wasting or underweight, 1.6 times higher risk of diarrhea and 2.4 times higher risk of death during neonatal period than average size infants.
Conclusion: Health education to parents and special care for small size babies through trained health workers need to be undertaken for improving the health of small size babies. At the same time, appropriate policy should be taken to reduce the incidence of small size babies.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/200</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/200/161</pdf_url>
  </Article>
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Interpretation of exposure effect in competing risks setting under accelerated failure time models</title>
    <FirstPage>91</FirstPage>
    <LastPage>98</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Alireza</FirstName>
        <LastName>Abadi</LastName>
        <affiliation locale="en_US">Department of Community Medicine, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Bagher</FirstName>
        <LastName>Pahlavanzade</LastName>
        <affiliation locale="en_US">Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Farid</FirstName>
        <LastName>Zayeri</LastName>
        <affiliation locale="en_US">Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Taban</FirstName>
        <LastName>Baghfalaki</LastName>
        <affiliation locale="en_US">Department of Statistics, Faculty of Mathematical Sciences, Tarbiat Modares University, Tehran, Iran.</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>05</Month>
        <Day>09</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: In survival studies, incidence of competing risks causes that the time of event of interest to be unknown. Analysis of competing risk data, often implemented using hazard-based method under proportional hazard assumption. In this study, we interpreted covariate effect under accelerated failure time model and cause-specific survival function.
Methods &amp; Materials: We considered weibull hazard and survival function as cause-specific hazard and survival function and explored the relation between these function. Estimation of parameters performed using Bayesian methods with non-informative priors that implemented in R2WinBUGS package of R software.
Results: Simulation study showed that, the relation between hazard and survival parameters for weibull distribution is also established between parameters of cause-specific hazard and cause-specific survival function. This relation also verified in PBC data set for logarithm of serum bilirubin and D-penicillamine effect.
Conclusion: Although in competing risk studies, most of the analysis performed under PH assumption, analysis based on AFT models will also be applicable for these data. In these setting, coefficients can be interpreted as effects of covariate on time to each event.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/184</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/184/162</pdf_url>
  </Article>
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">A new transformed Weibull lifetime distribution and its inferences based on the Bayes and maximum likelihood procedures</title>
    <FirstPage>99</FirstPage>
    <LastPage>112</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Omid</FirstName>
        <LastName>Kharazmi</LastName>
        <affiliation locale="en_US">Department of Statistics, Faculty of Mathematical Sciences, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Hadis</FirstName>
        <LastName>Mehregan</LastName>
        <affiliation locale="en_US">Department of Statistics, Shahid Chamran Ahvaz University, Ahavaz, Iran</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>05</Month>
        <Day>27</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: In last three decades or so, an extensive research works has appeared&#xA0;in the literature on the theory of statistical distributions. The Weibull distribution is a very&#xA0;popular model, and has been extensively used over the past decades for modelling data in&#xA0;reliability, engineering and biological studies.&#xA0;
Methods &amp; Materials: First, we obtain some of important statistical and reliability&#xA0;characteristics of the new model, and then the estimation of the parameters of proposed&#xA0;model is studied through two views of Bayesian and classic statistics.&#xA0;
Results: We show that the new distribution has the ability to fit into complete and censored&#xA0;real data. In the application section, we show the superiority of the proposed model to some&#xA0;common statistical distributions.
Conclusion: In this paper, we have proposed a new transformed Weibull distribution,&#xA0;denoted by TWD. It is investigated that the new model has increasing, decreasing and&#xA0;bathtub shape hazard functions. We provide the comprehensive Bayesian and maximum&#xA0;likelihood estimation procedures for complete and right censored real observations.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/193</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/193/163</pdf_url>
  </Article>
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Journal of Biostatistics and Epidemiology</JournalTitle>
      <Issn>2383-4196</Issn>
      <Volume>4</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2018</Year>
        <Month>10</Month>
        <Day>31</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Evaluation of sensitivity and specificity of tuberculosis diagnostic tools among HIV positive patients: A cross-sectional study</title>
    <FirstPage>113</FirstPage>
    <LastPage>118</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Yousef</FirstName>
        <LastName>Alimohamadi</LastName>
        <affiliation locale="en_US">Pars Advanced and Minimally Invasive Medical Manners Research Center, Pars Hospital, Iran University of Medical Sciences Tehran, Iran AND Department of of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Parvin</FirstName>
        <LastName>Afsar-kazerooni</LastName>
        <affiliation locale="en_US">HIV Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Mojtaba</FirstName>
        <LastName>Sepandi</LastName>
        <affiliation locale="en_US">Health Research Center, Lifestyle Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Shahla</FirstName>
        <LastName>Chaichian</LastName>
        <affiliation locale="en_US">Minimally Invasive Techniques Research Center of Tehran Medical Sciences Branch, Islamic Azad University, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Hamidreza</FirstName>
        <LastName>Tabatabaee</LastName>
        <affiliation locale="en_US">Department of Epidemiology, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Zahra</FirstName>
        <LastName>Kashi</LastName>
        <affiliation locale="en_US">Pars Advanced and Minimally Invasive Medical Manners Research Center, Pars Hospital, Iran University of Medical Sciences Tehran, Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Manije</FirstName>
        <LastName>Alimohammadi</LastName>
        <affiliation locale="en_US">Noor Research Center for Ophthalmic Epidemiology, Noor Eye Hospital, Tehran, IR Iran</affiliation>
      </Author>
      <Author>
        <FirstName>Firooz</FirstName>
        <LastName>Esmaeilzadeh</LastName>
        <affiliation locale="en_US">Department of Health Economics &amp; Management, School of Public Health, Tehran University of Medical, Tehran, Iran</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2018</Year>
        <Month>08</Month>
        <Day>10</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Background &amp; Aim: Tuberculosis is the major cause of morbidity and mortality among&#xA0;HIV patients. Thus, early diagnosis of Tuberculosis among these patients is important. The&#xA0;purpose of the present study was to determine the Sensitivity, Specificity, PPV and NPV for&#xA0;tools of diagnosing TB among HIV patients referred to behavioral disorder counseling&#xA0;center of Shiraz city.
Methods &amp; Materials: In this cross sectional study, 250 HIV+ patients in Shiraz were&#xA0;evaluated. For each patient, three sputum smears and a Chest X-ray and PPD was taken.&#xA0;Sensitivity, specificity, and positive and negative predictive values were determined based&#xA0;on the results of sputum cultures as a gold standard.
Results: Among 250 HIV+ individuals who entered the study, 8 (3.2 %) were diagnosed&#xA0;with tuberculosis. The sensitivity, specificity, PPV and NPV for chest x-ray were 62.5%,&#xA0;96%, 38% and 98.7%, respectively. Also they were 62.5%, 98.7%, 62.5% and 98.7% for&#xA0;AFB 1, and 25%, 99.5%, 66% and 97.5% for AFB 2. Finally, these factors were 99.5%,&#xA0;99.5%, 66% and 97.5% for AFB 3.
Conclusion: The prevalence of TB among HIV+ patients referring to the behavioral disease&#xA0;counseling center in Shiraz was lower than in other endemic areas of developing countries.&#xA0;The screening tools for diagnosis of tuberculosis included the chest x-ray and Acid Fast&#xA0;Bacilli and PPD test in order to find out the important role of detecting TB disease among&#xA0;HIV-infected people.</abstract>
    <web_url>https://jbe.tums.ac.ir/index.php/jbe/article/view/209</web_url>
    <pdf_url>https://jbe.tums.ac.ir/index.php/jbe/article/download/209/164</pdf_url>
  </Article>
</Articles>
