Publications by authors named "Abbas Bahrampour"

42 Publications

Bayesian mixture cure rate frailty models with an application to gastric cancer data.

Stat Methods Med Res 2021 Mar 26;30(3):731-746. Epub 2020 Nov 26.

Department of Biostatistics and Epidemiology, 48463Kerman University of Medical Sciences, Kerman, Islamic Republic of Iran.

Mixture cure rate models are commonly used to analyze lifetime data with long-term survivors. On the other hand, frailty models also lead to accurate estimation of coefficients by controlling the heterogeneity in survival data. Gamma frailty models are the most common models of frailty. Usually, the gamma distribution is used in the frailty random variable models. However, for survival data which are suitable for populations with a cure rate, it may be better to use a discrete distribution for the frailty random variable than a continuous distribution. Therefore, we proposed two models in this study. In the first model, continuous gamma as the distribution is used, and in the second model, discrete hyper-Poisson distribution is applied for the frailty random variable. Also, Bayesian inference with Weibull distribution and generalized modified Weibull distribution as the baseline distribution were used in the two proposed models, respectively. In this study, we used data of patients with gastric cancer to show the application of these models in real data analysis. The parameters and regression coefficients were estimated using the Metropolis with Gibbs sampling algorithm, so that this algorithm is one of the crucial techniques in Markov chain Monte Carlo simulation. A simulation study was also used to evaluate the performance of the Bayesian estimates to confirm the proposed models. Based on the results of the Bayesian inference, it was found that the model with generalized modified Weibull and hyper-Poisson distributions is a suitable model in practical study and also this model fits better than the model with Weibull and Gamma distributions.
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http://dx.doi.org/10.1177/0962280220974699DOI Listing
March 2021

Characterization of miR-200 family members as blood biomarkers for human and laying hen ovarian cancer.

Sci Rep 2020 11 18;10(1):20071. Epub 2020 Nov 18.

Department of Obstetrics/Gynecology and Reproductive Biology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.

MicroRNA-200 (miR-200) family is highly expressed in ovarian cancer. We evaluated the levels of family members relative to the internal control miR-103a in ovarian cancer and control blood specimens collected from American and Hong Kong Chinese institutions, as well as from a laying hen spontaneous ovarian cancer model. The levels of miR-200a, miR-200b and miR-200c were significantly elevated in all human cancer versus all control blood samples. Further analyses showed significantly higher miR-200 levels in Chinese control (except miR-429) and cancer (except miR-200a and miR141) samples than their respective American counterparts. Subtype-specific analysis showed that miR-200b had an overall elevated level in serous cancer compared with controls, whereas miR-429 was significantly elevated in clear cell and endometrioid cancer versus controls. MiR-429 was also significantly elevated in cancer versus control in laying hen plasma samples, consistent with the fact that endometrioid tumor is the prevalent type in this species. A neural network model consisting of miR-200a/200b/429/141 showed an area under the curve (AUC) value of 0.904 for American ovarian cancer prediction, whereas a model consisting of miR-200b/200c/429/141 showed an AUC value of 0.901 for Chinese women. Hence, miR-200 is informative as blood biomarkers for both human and laying hen ovarian cancer.
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http://dx.doi.org/10.1038/s41598-020-77068-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674435PMC
November 2020

Estimating the Loss in Expectation of Life and Relative Survival Rate among Hemodialysis Patients in Iran.

J Res Health Sci 2020 Aug 3;20(3):e00487. Epub 2020 Aug 3.

Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

Background: Information regarding the prognosis and burden of diseases can be used by policymakers to determine competing health priorities. We aimed to assess the Relative Survival Rate (RSR) and loss of expectation of life (LEL) to evaluate the prognosis and burden of diseases in Hemodialysis (HD) patients.

Study Design: A retrospective cohort study.

Methods: We recruited 648 HD patients referred to three referral centers in Kerman City, Iran, from 2008 to 2019. RSR, was defined as the ratio of the observed and the expected survival rates of general population for persons of the same age and sex as patients in the current study. LEL was determined as the difference between corresponding life expectancies (LE). The extended Cox proportional hazard model was used to identify variables associated with the outcome.

Results: Variables associated with outcome were diabetic status and age. In the 5th year of the follow-up study, the overall RSR was 0.57. In general, for HD patients, the estimation of LE and LEL was 22.6 and 12.36 year, respectively.

Conclusion: HD patients, especially older patients, showed a very poor prognosis, with a large amount of lost life expectancy. Therefore, they need more care and attention from health authorities. It is suggested to estimate the cost of eliminating the risk factors causing kidney diseases.
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http://dx.doi.org/10.34172/jrhs.2020.21DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585771PMC
August 2020

Correlates of Alcohol Consumption and Drug Injection among Homeless Youth: A Case Study in the Southeast of Iran.

Addict Health 2019 Oct;11(4):207-215

HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Kerman University of Medical Sciences, Kerman, Iran.

Background: Alcohol use and drug injection are prevalent among homeless youths. The aim of this study was to identify the associated factors of alcohol consumption and drug injection among homeless youths aged 18-29 years.

Methods: Data on 202 homeless youths (111 males and 91 females) were collected using a standardized questionnaire and face-to-face interview. Lasso logistic regression was applied to determine the impact of associated factors on alcohol consumption and drug injection.

Findings: The mean age of the participants was 26.30 ± 3.19 years. Also, the prevalence of alcohol consumption and drug injection was 33.0% [95% confidence interval (CI): 30-36] and 4.0% (95% CI: 0-8), respectively; 6 people (3.0%) consumed alcohol and injected drugs at the same time. Correlates of alcohol consumption and drug injection were male sex [odds ratio (OR) = 5.7], age (OR = 0.96 and OR = 0.98), bachelor or higher education level (OR = 1.34), non-Iranian nationality (OR = 0.05 and OR = 0.18), food score (OR = 0.92), smoking (OR = 2.05), substance use (OR = 1.12), opposite sex relationship (OR = 1.6), homosexual relationship (OR = 3.56 and OR = 2.69), and mental disorder (OR = 0.99).

Conclusion: Based on our findings, it seems that the homeless youth are more desired to use alcohol and drug injection, whereas the prevalence of alcohol consumption and drug injection in homeless youth was higher than general youth population in Iran. Therefore, some suitable solutions are needed to prevent the homelessness. Also, the effective variables that were identified in this study for alcohol use and drug injection can help design and implement beneficial interventions.
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http://dx.doi.org/10.22122/ahj.v11i4.245DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7073810PMC
October 2019

Mortality risk factors in patients with gastric cancer using Bayesian and ordinary Lasso logistic models: a study in the Southeast of Iran.

Gastroenterol Hepatol Bed Bench 2020 ;13(1):31-36

Modeling in Health Research Center, Faculty of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

Aim: The aim of this study was to apply two types of statistical models to determine the factors that influence the mortality rate in patients with gastric cancer.

Background: In Iran, gastric cancer ranks the first and second most prevalent among men and women, respectively. It is the first cause of death in Iran in both gendersival.

Methods: In this retrospective study, data were obtained from 339 (216 male) patients diagnosed with gastric cancer in the city of Kerman (South-East of Iran) during 2001-2015. In this study, ordinary and Bayesian Lasso (least absolute shrinkage and selection operator) logistic regression models, with goodness-of-fit indices, were compared and the models' risk factors were also determined.

Results: The mean age of the participants was 62.84 ±14.53 years, and 12.4% of them were younger than 45 years. Also, the mortality rate was 57.7%. Gender, morphology of the tumor, and time of diagnosis were found to be significant factors in the mortality of the patients in both models. This study found that the Bayesian Lasso model had better fitness.

Conclusion: The high mortality rate of gastric cancer and its high prevalence at age below 45 years are alarming. Thus, great attention should be paid to prevention, early diagnosis, especially in females, and adenocarcinoma to improve the survival of patients with gastric cancer.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7069537PMC
January 2020

Factors Affecting Long-Survival of Patients with Breast Cancer by Non-Mixture and Mixture Cure Models Using the Weibull, Log-logistic and Dagum Distributions: A Bayesian Approach.

Asian Pac J Cancer Prev 2020 Feb 1;21(2):485-490. Epub 2020 Feb 1.

Department of Biostatistics and Epidemiology, Kerman University of Medical Sciences, Kerman, Iran.

Background: Breast cancer is a top biomedical research priority, and it is a major health problem. Therefore, the present study aimed to determine the prognostic factors of breast cancer survival using cure models.

Methods: In this retrospective cohort analytic study, data of 140 breast cancer patients were collected from Ali Ibn Abi Taleb hospital, Rafsanjan, Southeastern Iran. Since in this study, a part of the population had long-term survival, cure models were used and evaluated using DIC index. The data were analyzed using Openbugs Software.

Results: In this study, of 140 breast cancer patients, 23 (16.4%) cases died of breast cancer. Based on the findings, the Bayesian nonmixture cure model, with type I Dagum distribution, was the best fitted model. The variables of BMI, number of children, number of natural deliveries, tumor size, metastasis, consumption of canned food, tobacco use, and breastfeeding affected patients' survival based on type I Dagum distribution.

Conclusion: The results of the present study demonstrated that the Bayesian nonmixture cure model, with type I Dagum distribution, can be a good model to determine factors affecting the survival of patients when there is the possibility of a fraction of cure. In this study, it was found that adapting a healthy lifestyle (eg, avoiding canned foods and smoking) can improve the survival of breast cancer patients.
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http://dx.doi.org/10.31557/APJCP.2020.21.2.485DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332130PMC
February 2020

The Relation between Hearing Loss and Smoking among Workers Exposed to Noise, Using Linear Mixed Models.

Iran J Otorhinolaryngol 2020 Jan;32(108):11-20

Department of Otorhinolaryngology, Faculty of Medical, Kerman University of Medical Sciences, Kerman, Iran.

Introduction: Noise is one of the most common and harmful physical factors in the working environment and has physical and psychological effects on individuals. In this study, the audiometry results of industrial workers were modeled and the effect of noise and other factors on hearing loss was examined.

Materials And Methods: This was a longitudinal study based on the records of workers who had worked over 10 years in the industry and had recorded audiometries since their employment. Data was analyzed through linear mixed models.

Results: During each year of noise exposure, hearing loss was 1.9 db at 4000 Hz; 0.059 in low frequencies and 0.62 db in high frequencies. At 8000 Hz the effect of the age at employment on hearing loss was significant (P=0.014). At low frequencies the interaction of smoking and age at employment was significantly related to hearing loss (P˂0.001).

Conclusion: This study showed that despite acquaintance with safety measures, workers still face hearing loss in industry and employers should put workers under more surveillance for using protective gear. Smoking might be another risk factor for hearing loss.
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http://dx.doi.org/10.22038/ijorl.2019.37555.2229DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007995PMC
January 2020

Comparison of Penalized Cox Regression Methods in Low-Dimensional Data with Few-Events: An Application to Dialysis Patients' Data.

J Res Health Sci 2019 Jul 15;19(3):e00452. Epub 2019 Jul 15.

Department of Biostatistics and Epidemiology, Kerman University of Medical Sciences, Kerman,

Background: Dialysis is a dominant therapeutic method in patients with chronic renal failure. The ratio of those who experienced the event to the predictor variables is expressed as event per variable (EPV). When EPV is low, one of the common techniques which may help to manage the problem is penalized Cox regression model (PCRM). The aim of this study was to determine the survival of dialysis patients using the PCRM in low-dimensional data with few events.

Study Design: A cross-sectional study.

Methods: Information of 252 dialysis patients of Bandar Abbas hospitals, southern Iran, from 2010-16 were used. To deal with few mortality cases in the sample, the PCRM (lasso, ridge and elastic net, adaptive lasso) were applied. Models were compared in terms of calibration and discrimination.

Results: Thirty-five (13.9%) mortality cases were observed. Dialysis data simulations revealed that the lasso had higher prediction accuracy than other models. For one unit of increase in the level of education, the risk of mortality was reduced by 0.32 (HR=0.68). The risk of mortality was 0.26 (HR=1.26) higher for the unemployed than the employed cases. Other significant factors were the duration of each dialysis session, number of dialysis sessions per week and age of dialysis onset (HR=0.93, 0.95 and 1.33).

Conclusion: The performance of penalized models, especially the lasso, was satisfying in low-dimensional data with low EPV based on dialysis data simulation and real data, therefore these models are the good choice for managing of this type of data.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7183557PMC
July 2019

Comparison of methods to Estimate Basic Reproduction Number () of influenza, Using Canada 2009 and 2017-18 A (H1N1) Data.

J Res Med Sci 2019 24;24:67. Epub 2019 Jul 24.

Department of Biostatistics and Epidemiology, Faculty of Health, Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

Background: The basic reproduction number () has a key role in epidemics and can be utilized for preventing epidemics. In this study, different methods are used for estimating 's and their vaccination coverage to find the formula with the best performance.

Materials And Methods: We estimated for cumulative cases count data from April 18 to July 6, 2009 and 35-2017 to 34-2018 weeks in Canada: maximum likelihood (ML), exponential growth rate (EG), time-dependent reproduction numbers (TD), attack rate (AR), gamma-distributed generation time (GT), and the final size of the epidemic. Gamma distribution with mean and standard deviation 3.6 ± 1.4 is used as GT.

Results: The AR method obtained a 95% confidence interval [CI]) value of 1.116 (1.1163, 1.1165) and an EG (95%CI) value of 1.46 (1.41, 1.52). The (95%CI) estimate was 1.42 (1.27, 1.57) for the obtained ML, 1.71 (1.12, 2.03) for the obtained TD, 1.49 (1.0, 1.97) for the gamma-distributed GT, and 1.00 (0.91, 1.09) for the final size of the epidemic. The minimum and maximum vaccination coverage were related to AR and TD methods, respectively, where the TD method has minimum mean squared error (MSE). Finally, the (95%CI) for 2018 data was 1.52 (1.11, 1.94) by TD method, and vaccination coverage was estimated as 34.2%.

Conclusion: For the purposes of our study, the estimation of TD was the most useful tool for computing the , because it has the minimum MSE. The estimation > 1 indicating that the epidemic has occurred. Thus, it is required to vaccinate at least 41.5% to prevent and control the next epidemic.
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http://dx.doi.org/10.4103/jrms.JRMS_888_18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6670001PMC
July 2019

Estimation of the Basic Reproduction Number and Vaccination Coverage of Influenza in the United States (2017-18).

J Res Health Sci 2018 Sep 22;18(4):e00427. Epub 2018 Sep 22.

Department of Biostatistics and Epidemiology, Modeling in Health Research Center, Faculty of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

Background: Determining the epidemic threshold parameter helps health providers calculate the coverage while guiding them in planning the process of vaccination strategy. Since the trend and mechanism of influenza is very similar in different countries, we planned a study with the mentioned goal by using data of US from 2017 to 2018.

Study Design: A secondary study.

Methods: R0 and corresponding vaccination coverage are estimated using the national and state-level data of the US from the 40th in 2017 to the 5th week in 2018. Four methods maximum likelihood (ML), exponential growth (EG), time-dependent reproduction numbers (TD), and sequential Bayesian (SB) are used to calculate minimum vaccination coverage. The gamma distribution is considered as the distribution and the generation of time.

Results: The peak of epidemy in most states has occurred in the 15th week after the beginning of the epidemics. The generation time obey the Gamma distribution with mean and standard deviation of 3.6 and 1.6, respectively, was utilized for the generation time. The R0 (vaccination coverage) equaled 1.94 (48.4%), 1.80 (44.4%), 3.06 (67.3%), and 2.11 (52.6%) for EG, ML, SB, and TD methods at the national level, respectively.

Conclusion: The R0 estimations were in the range of 1.8-3.06, indicating that an epidemic has occurred in the US (R0>1). Thus, it is required to vaccinate at least 44.4% to 67.3% to prevent the next epidemics of influenza. The findings of this study assist futures studies to apply disease control by vaccination strategies in order to prevent a national disaster.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6941634PMC
September 2018

The relation between mortality from cardiovascular diseases and temperature in Shiraz, Iran, 2006-2012.

ARYA Atheroscler 2018 Jul;14(4):149-156

Professor, Department of Epidemiology and Biostatistics, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.

Background: Several studies have suggested that temperature may have an effect on the number of cardiovascular deaths in societies. Global warming is a concern, and cardiovascular diseases are the top cause of death worldwide. This study investigated the relation between temperature and cardiovascular mortality in Shiraz City, Iran.

Methods: In this ecological study, data about temperature and cardiovascular deaths (in age and gender groups) in Shiraz City were inquired from 2006 to 2012. The simultaneous and delayed relation between monthly temperature and cardiovascular deaths was examined using Spearman and Pearson correlation tests, and crude and adjusted negative binomial regression analysis with adjustment for confounding factors such as humidity, rainfall, wind direction, wind speed, and air pollutants. Analysis was done using MINITAB and STATA software.

Results: During this period 17,167 deaths were reported in Shiraz. The lowest number of cardiovascular deaths was reported in 20 °C. No significant relation was observed between mean monthly temperature and cardiovascular deaths in the same month after adjusting for confounding factors. Although, cardiovascular death in 18- to 60-year-old people showed an inverse significant relation with minimum [Incidence rate ratio (IRR) = 0.98989, P = 0.020], maximum (IRR = 0.99046, P = 0.011), and mean temperature (IRR = 0.98913, P = 0.006) of the same month in the crude model, it was not significant in the adjusted model (IRR = 0.99848, P = 0.848, IRR = 0.99587, P = 0.584, and IRR = 0.99512, P = 0.506, respectively).

Conclusion: It seems that there is no significant relation between temperature and cardiovascular deaths in Shiraz, which is probably due to its moderate climate, and the fact that no major heat or cold wave occurred during this time.
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http://dx.doi.org/10.22122/arya.v14i4.1341DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6312568PMC
July 2018

Hospital service quality - patient preferences - a discrete choice experiment.

Int J Health Care Qual Assur 2018 Aug;31(7):676-683

Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences , Kerman, Iran.

Purpose: High quality healthcare is important to all patients. If healthcare is felt to be high quality, then patients will be satisfied, and the relationship between patients and healthcare providers will improve. Patient satisfaction is among the most commonly used service quality indicators; however, it is not fully known which factors influence satisfaction. Therefore, it is necessary to pay attention to the elements that affect both healthcare quality and patient satisfaction. Nowadays, several methods are used in health economics to assess patient preferences, prioritize them and help health policy makers improve services. Discrete choice experiment (DCE) is one method that is useful to elicit patient preferences regarding healthcare services. The purpose of this paper is to apply DCE and elicit patient preferences in medical centers to rank certain healthcare quality factors.

Design/methodology/approach: The descriptive, analytical study used a cross-sectional questionnaire that the authors developed. In total, 12 scenarios were chosen after applying fractional factorials. The questionnaire was completed by patients who were admitted to Kerman General Teaching Hospitals, South-East Iran in 2015. Patient preferences were identified by calculating the characteristics' marginal effects and prioritizing them. The generalized estimation equation (GEE) model was used to determine attribute effects on patient preferences.

Findings: In total, 167 patients completed the questionnaire. Prioritizing the attributes showed that "physical examination" was the most important attribute. Other key features included "cleanliness," "training after discharging," "medical staff attention," "waiting for admission" and "staff attitude." All attributes were statistically significant ( p<0.05) except staff behavior. No demographic characteristic was significant.

Practical Implications: To increase hospital patient satisfaction, health policy makers should develop programs to enhance healthcare quality and hospital safety by increasing physical examination quality and other services.

Originality/value: To estimate DCE independent variables, logistic regression models are usually used. The authors used the GEE model to estimate discrete choice experiment owing the explanatory variables' dependency.
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http://dx.doi.org/10.1108/IJHCQA-01-2017-0006DOI Listing
August 2018

Short-term effects of air pollution on respiratory mortality in Ahvaz, Iran.

Med J Islam Repub Iran 2018 8;32:30. Epub 2018 Apr 8.

Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.

Urban air pollutants may affect respiratory mortality. This study was conducted to investigate this effect in Ahvaz, one of the most polluted cities in the world. The impact of 7 major air pollutants including O3, PM10, NO2, CO, and SO2 were evaluated on respiratory mortality in different gender and age groups using a quasi-Poisson, second degree polynomial constrained, distributed lag model, with single and cumulative lag structures adjusted by trend, seasonality, temperature, relative humidity, weekdays, and holiday. Data were analyzed using the dlnm package in R x64 3.2.5 software. Significance level was set at less than 0.05. In adjusted models, for each IQR increase of O3 in the total population, the risk ratio (RR) for respiratory deaths in 0 to 14- day lags was, respectively, 1.009 (95% CI:1.001-1.016) and 1.009 (95% CI:1.002-1.017), and it was 1.021 (95% CI: 1.002-1.040) in cumulative 0 to 14- day lags. For PM10, in the total population and in adjusted models after 0 to 14- day lags and in cumulative lags of 0 to 14 for an IQR increase in the mean concentration of PM10, the RR for respiratory deaths increased significantly and was, respectively, 1.027 (95% CI:1.002-1.051), 1.029 (95% CI:1.006-1.052), and 1.065 (95% CI:1.005-1.128). NO2 showed a significant association with respiratory deaths only in the 18 to 60 year- old age group and in 9- day lags (RR= 1.318, 95% CI:1.002-1.733). Finally, the results showed that for an IQR increase in the mean concentration of CO and SO2, the adjusted RR for respiratory deaths in 9- day lags in the total population was, respectively, RR= 1.058 (95% CI:1.008-1.111) and 1.126 (95% CI:1.034-1.220). Air pollution in Ahvaz is probably causing increased respiratory mortality.
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http://dx.doi.org/10.14196/mjiri.32.30DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6108243PMC
April 2018

The relation between air pollution and respiratory deaths in Tehran, Iran- using generalized additive models.

BMC Pulm Med 2018 Mar 20;18(1):49. Epub 2018 Mar 20.

Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Background: Some epidemiological evidence has shown a relation between ambient air pollution and adverse health outcomes. The aim of this study was to investigate the effect of air pollution on mortality from respiratory diseases in Tehran, Iran.

Methods: In this ecological study, air pollution data was inquired from the Tehran Province Environmental Protection Agency and the Tehran Air Quality Control Company. Meteorological data was collected from the Tehran Meteorology Organization and mortality data from the Tehran Cemetery Mortality Registration. Generalized Additive Models (GAM) was used for data analysis with different lags, up to 15 days. A 10-unit increase in all pollutants except CO (1-unit) was used to compute the Relative Risk of deaths.

Results: During 2005 until 2014, 37,967 respiratory deaths occurred in Tehran in which 21,913 (57.7%) were male. The strongest relationship between NO and PMand respiratory death was seen on the same day (lag 0), and was respectively (RR = 1.04, 95% CI: 1.02-1.07) and (RR = 1.03, 95% CI: 1.02-1.04). O and PM had the strongest relationship with respiratory deaths on lag 2 and 1 respectively, and the RR was equal to 1.03, 95% CI: 1.01-1.05 and 1.06, 95% CI: 1.02-1.10 respectively. NO, O, PM and PM also showed significant relations with respiratory deaths in the older age groups.

Conclusions: The findings of this study showed that O, NO, PM and PM air pollutants were related to respiratory deaths in Tehran. Reducing ambient air pollution can save lives in Tehran.
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http://dx.doi.org/10.1186/s12890-018-0613-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5859399PMC
March 2018

Lag time structure of cardiovascular deaths attributed to ambient air pollutants in Ahvaz, Iran, 2008-2015.

Int J Occup Med Environ Health 2018 Jul 15;31(4):459-473. Epub 2018 Mar 15.

Kerman University of Medical Sciences, Kerman, Iran (Physiology Research Center).

Objectives: There are few studies about the association between breathing polluted air and increased risk of cardiovascular diseases and cardiac death in the Middle East. This study aimed to investigate the relation between air pollutants and cardiovascular mortality (based on ICD-10) in Ahvaz.

Material And Methods: In this ecological study, the data about cardiovascular disease mortality and air pollutants from March 2008 until March 2015 was inquired from the Ahvaz City Authority and the Khuzestan Province Environmental Protection Agency. The quasi-Poisson, second degree polynomial constrained, distributed lag model; using single and cumulative lag structures, adjusted by trend, seasonality, temperature, relative humidity, weekdays and holidays was used for the data analysis purposes.

Results: Findings indicated a direct significant relation between an interquartile range (IQR) increase in ozone and cardiovascular deaths among men after 3 days' lag. There was also a significant relation between an IQR increase in particulate matter below 10 μm and cardiovascular deaths for all people, over 60 years old and under 18 years old after 3 and 13 days' lags. There was a significant relation between an IQR increase in nitrogen dioxide and carbon monoxide, and cardiovascular deaths in the case of under 18-year-olds (in the lag 11) and over 60-year-olds (in the lag 9), respectively. We finally found a significant association between an IQR increase in sulfur dioxide and cardiovascular deaths in the case of men, under 18-year-olds and from 18- to 60-year-olds in the lag 9, 0, and 11, respectively (p-values < 0.05).

Conclusions: It appears that air pollution is significantly associated with cardiovascular deaths in Ahvaz City. Int J Occup Med Environ Health 2018;31(4):459-473.
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http://dx.doi.org/10.13075/ijomeh.1896.01104DOI Listing
July 2018

Predicting the Survival of Gastric Cancer Patients Using Artificial and Bayesian Neural Networks

Asian Pac J Cancer Prev 2018 Feb 26;19(2):487-490. Epub 2018 Feb 26.

Modeling of Health Research Center, Department of Biostatistics and Epidemiology, School of Health, Kerman University of Medical Sciences, Kerman, Iran. Email:

Introduction and purpose: In recent years the use of neural networks without any premises for investigation of prognosis in analyzing survival data has increased. Artificial neural networks (ANN) use small processors with a continuous network to solve problems inspired by the human brain. Bayesian neural networks (BNN) constitute a neural-based approach to modeling and non-linearization of complex issues using special algorithms and statistical methods. Gastric cancer incidence is the first and third ranking for men and women in Iran, respectively. The aim of the present study was to assess the value of an artificial neural network and a Bayesian neural network for modeling and predicting of probability of gastric cancer patient death. Materials and Methods: In this study, we used information on 339 patients aged from 20 to 90 years old with positive gastric cancer, referred to Afzalipoor and Shahid Bahonar Hospitals in Kerman City from 2001 to 2015. The three layers perceptron neural network (ANN) and the Bayesian neural network (BNN) were used for predicting the probability of mortality using the available data. To investigate differences between the models, sensitivity, specificity, accuracy and the area under receiver operating characteristic curves (AUROCs) were generated. Results: In this study, the sensitivity and specificity of the artificial neural network and Bayesian neural network models were 0.882, 0.903 and 0.954, 0.909, respectively. Prediction accuracy and the area under curve ROC for the two models were 0.891, 0.944 and 0.935, 0.961. The age at diagnosis of gastric cancer was most important for predicting survival, followed by tumor grade, morphology, gender, smoking history, opium consumption, receiving chemotherapy, presence of metastasis, tumor stage, receiving radiotherapy, and being resident in a village. Conclusion: The findings of the present study indicated that the Bayesian neural network is preferable to an artificial neural network for predicting survival of gastric cancer patients in Iran.
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http://dx.doi.org/10.22034/APJCP.2018.19.2.487DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5980938PMC
February 2018

Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

J Res Med Sci 2017 26;22:135. Epub 2017 Dec 26.

Department of Biostatistics and Epidemiology, Modeling in Health Research Center, Faculty of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

Background: Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients.

Materials And Methods: We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM).

Results: The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86).

Conclusion: Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.
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http://dx.doi.org/10.4103/jrms.JRMS_405_17DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5767811PMC
December 2017

Molecular epidemiology of infectious diseases.

Electron Physician 2017 Aug 1;9(8):5149-5158. Epub 2017 Aug 1.

Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

Molecular epidemiology (ME) is a branch of epidemiology developed by merging molecular biology into epidemiological studies. In this paper, the authors try to discuss the ways that molecular epidemiology studies identify infectious diseases' causation and pathogenesis, and unravel infectious agents' sources, reservoirs, circulation pattern, transmission pattern, transmission probability, and transmission order. They bring real-world examples of research works in each area to make each study design more understandable. They also address some research areas and study design aspects that need further attention in future. They close with some thoughts about future directions in this field and emphasize on the need for training competent molecular epidemiology specialists that are capable of dealing with rapid advances in the field.
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http://dx.doi.org/10.19082/5149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5614305PMC
August 2017

Comparing indices of median nerve among diabetic patients with or without metabolic syndrome.

Diabetes Metab Syndr 2017 Dec 18;11 Suppl 2:S669-S673. Epub 2017 May 18.

Cardiovascular Research Center, Institute of Basic and Clinical Physiology Sciences, Kerman University of Medical Sciences, Kerman, Iran. Electronic address:

Background: Metabolic syndrome is highly prevalent among patients with type II diabetes and is reported as a strong risk factor for cardiovascular diseases as well as carpal tunnel syndrome (CTS). The aim of the current study was to compare median nerve indices among diabetic patients with and without metabolic syndrome.

Methods: This cross-sectional study was conducted on 105 patients with type II diabetes whom participated in the coronary artery disease risk factor study in Kerman, Iran (KERCARDS). Patients with type II diabetes were called and those with clinical symptoms of CTS were included in the study, and median nerve indices were measured according to standard electro diagnosis tests. GEE statistical model was used to compare median nerve indices among diabetic patients with and without metabolic syndrome. All statistical analysis was done using SPSS 20.0.

Results: The mean age of participants was 57.57±9.53. There was no significant difference between the left and right hand regarding median nerve indices except median nerve motor amplitude (MA). Furthermore, components of metabolic syndrome including BMI and LDL were determined as risk factors for CTS according to several indices.

Conclusion: Components of metabolic syndrome had more influence on sensory indices than motor indices and primary control of these components might prevent dysfunction of sensory neurons and also motor neurons in advanced stages among diabetic patients.
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http://dx.doi.org/10.1016/j.dsx.2017.04.023DOI Listing
December 2017

Modeling the Burden of Cardiovascular Diseases in Iran from 2005 to 2025: The Impact of Demographic Changes.

Iran J Public Health 2017 Apr;46(4):506-516

Center for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran.

Background: Estimating the burden of non-communicable diseases particularly cardiovascular disease (CVD) is essential for health management and policymaking. In this paper, we used a regression model to estimate the future impact of demographic changes on the burden of CVD in Iran during the next two decades.

Methods: Disability-adjusted life years (DALY) were used to estimate the future burden of CVD in Iran. A regression model was used to estimate DALY caused by CVD in the Iranian population aged 30-100 yr, stratified by age group and sex. The predicted population of Iranians aged ≥ 30 yr was entered into the model and DALY were calculated over 2005-2025. To assess the areas of uncertainty in the model, we did sensitivity analysis and Monte Carlo Simulation.

Results: In the year 2005, there were 847309 DALYs caused by CVD in Iranian adults aged ≥ 30 yr. This figure will nearly be 1728836 DALYs in 2025. In other words, just because of the aging, DALY related to CVD will increase more than two-fold in 2025 compared with 2005. The burden of CVD was higher in men (443235) than in women (404235) in 2005; but in 2025, the difference will be less (867639 vs. 861319).

Conclusion: The burden of CVD will increase steeply in Iran over 2005-2025, mainly because of the aging population. Therefore, more attention is needed to deal with the impact of CVD in the following decades in Iran.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5439040PMC
April 2017

Comparison of Weibull and Lognormal Cure Models with Cox in the Survival Analysis Of Breast Cancer Patients in Rafsanjan.

J Res Health Sci 2017 02 16;17(1):e00369. Epub 2017 Feb 16.

Modeling in Health Research, Institute for Future Studies in Health, Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman,Iran.

Background: Breast cancer is the most common cancer after lung cancer and the second cause of death. In this study we compared Weibull and Lognormal Cure Models with Cox regression on the survival of breast cancer.

Study Design: A cohort study.

Methods: The current study retrospective cohort study was conducted on 140 patients referred to Ali Ibn Abitaleb Hospital, Rafsanjan southeastern Iran from 2001 to 2015 suffering from breast cancer. We determined and analyzed the effective survival causes by different models using STATA14.

Results: According to AIC, log-normal model was more consistent than Weibull. In the multivariable Lognormal model, the effective factors like smoking, second -hand smoking, drinking herbal tea and the last breast-feeding period were included. In addition, using Cox regression factors of significant were the disease grade, size of tumor and its metastasis (p-value<0.05). As Rafsanjan is surrounded by pistachio orchards and pesticides applied by farmers, people of this city are exposed to agricultural pesticides and its harmful consequences. The effect of the pesticide on breast cancer was studied and the results showed that the effect of pesticides on breast cancer was not in agreement with the models used in this study.

Conclusions: Based on different methods for survival analysis, researchers can decide how they can reach a better conclusion. This comparison indicates the result of semi-parametric Cox method is closer to clinical experiences evidences.
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February 2017

Relationship Between Air Pollution, Weather, Traffic, and Traffic-Related Mortality.

Trauma Mon 2016 Sep 22;21(4):e37585. Epub 2016 Aug 22.

Modeling in Health Research Center, Institute for Futures Studies in Health, Department of Biostatistics and Epidemiology, Faculty of Health Kerman Univesity of Medical Sciences Kerman, IR Iran.

Background: Air pollution and weather are just two of many environmental factors contributing to traffic accidents (RTA).

Objectives: This study assessed the effects of these factors on traffic accidents and related mortalities in Ahvaz, Iran.

Methods: In this ecological study, data about RTA, traffic-related mortalities, air pollution (including NO, CO, NO, NO PM, SO, and O rates) and climate data from March 2008 until March 2015 was acquired from the Khuzestan State Police Force, the Environmental Protection Agency and the State Meteorological Department. Statistical analysis was performed with STATA 12 through both crude and adjusted negative binomial regression methods.

Results: There was a significant positive correlation between increase in the monthly average temperature, the number of rainy days, and the number of frost days with the number of RTA (P < 0.05). Increased monthly average relative humidity, evaporation, and number of sunny days were negatively correlated with the frequency of RTA (P < 0.05). We also observed an inverse significant correlation between monthly average relative humidity, evaporation, and wind speed with traffic accident mortality (P < 0.05). Some air pollutants were negatively associated with the incidence rate of RTA.

Conclusions: It appears that some weather variables were significantly associated with increased RTA. However, increased levels of air pollutants were not associated with increased rates of RTA and/or related mortalities. Additional studies are recommended to explore this topic in more detail.
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http://dx.doi.org/10.5812/traumamon.37585DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5282930PMC
September 2016

Death from respiratory diseases and temperature in Shiraz, Iran (2006-2011).

Int J Biometeorol 2017 Feb 14;61(2):239-246. Epub 2016 Jul 14.

Deputy of Health, Shiraz University of Medical Sciences, Shiraz, Iran.

Some studies have suggested that the number of deaths increases as temperatures drops or rises above human thermal comfort zone. The present study was conducted to evaluate the relation between respiratory-related mortality and temperature in Shiraz, Iran. In this ecological study, data about the number of respiratory-related deaths sorted according to age and gender as well as average, minimum, and maximum ambient air temperatures during 2007-2011 were examined. The relationship between air temperature and respiratory-related deaths was calculated by crude and adjusted negative binomial regression analysis. It was adjusted for humidity, rainfall, wind speed and direction, and air pollutants including CO, NO, PM, SO, O, and THC. Spearman and Pearson correlations were also calculated between air temperature and respiratory-related deaths. The analysis was done using MINITAB16 and STATA 11. During this period, 2598 respiratory-related deaths occurred in Shiraz. The minimum number of respiratory-related deaths among all subjects happened in an average temperature of 25 °C. There was a significant inverse relationship between average temperature- and respiratory-related deaths among all subjects and women. There was also a significant inverse relationship between average temperature and respiratory-related deaths among all subjects, men and women in the next month. The results suggest that cold temperatures can increase the number of respiratory-related deaths and therefore policies to reduce mortality in cold weather, especially in patients with respiratory diseases should be implemented.
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http://dx.doi.org/10.1007/s00484-016-1206-zDOI Listing
February 2017

Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran.

PLoS One 2016 9;11(6):e0156499. Epub 2016 Jun 9.

Regional Knowledge Hub, and WHO Collaborating Centre for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug networks and mass migration of Afghan refugees and labours to Iran, which calls for extensive preventive efforts.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0156499PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4900578PMC
July 2017

Assessment of the impact of the malaria elimination programme on the burden of disease morbidity in endemic areas of Iran.

Malar J 2016 Apr 14;15:209. Epub 2016 Apr 14.

Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Background: Controlling and preventive measures considerably reduced malaria incidence in Iran over the past few years, which confined the endemic areas to some regions in the southeastern Iran. The National Malaria Elimination Programme commenced in 2010. With regard to the presumption that the elimination programme interventions have accelerated the declining trend of malaria incidence across the endemic areas of Iran, the present study attempted to assess the effectiveness of the elimination programme by reviewing malaria incidence status, over a 14-year period, and comparing the trend of malaria incidence across malaria-endemic areas between the control and pre-elimination phase, and the elimination phase.

Methods: A retrospective analysis of malaria surveillance data was conducted in a 14-year period (2001-2014), using multilevel Poisson regression. The epidemiological malaria maps and indicators also were developed and compared between the control and pre-elimination phase, and the elimination phase.

Results: The mean of malaria incidence was 2.2 (1.7-2.7) for the entire study period. This rate was 3.4 (2.6-4.1) in the control and pre-elimination phase, and 0.41 (0.25-0.57) for the elimination phase. During the malaria elimination phase, the decline of annual malaria incidence had significantly accelerated and autochthonous cases had the greatest difference in malaria incidence decline (compared to the control and pre-elimination phase), whereas, falciparum cases had the lowest difference in malaria incidence decline, followed by non-Iranian and imported cases. Furthermore, there was a decline in Iranians to non-Iranians ratio and an increase in the ratios of over 15 to under 15, as well as male to female, in the elimination phase in comparison to the control and pre-elimination phase.

Conclusions: It seems that the decline of malaria transmission, which has been initiated over the past few years, has accelerated as a result of the elimination programme, and Iran is approaching the goals set regarding the elimination of this disease.
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http://dx.doi.org/10.1186/s12936-016-1267-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4831192PMC
April 2016

Quantile Regression and its Key Role in Promoting Medical Research.

Iran J Public Health 2016 Jan;45(1):116-7

Research Center for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran; Dept. of Epidemiology and Biostatistics, School of Health, Kerman University of Medical Sciences, Kerman, Iran.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4822385PMC
January 2016

Association of Handgrip Strength With Malnutrition-Inflammation Score as an Assessment of Nutritional Status in Hemodialysis Patients.

Iran J Kidney Dis 2016 Jan;10(1):30-5

Department of Occupational Health, Student Research Committee, Kerman University of Medical Sciences, Kerman, Iran.

Introduction:   Protein-energy wasting (PEW) is very common in patients with chronic kidney disease and those undergoing maintenance dialysis. Reduced handgrip strength is associated with PEW and considered as a reliable nutritional parameter that reflects loss of muscle mass. This study aimed to evaluate the handgrip strength and its relationship with the Malnutrition-Inflammation Score (MIS) among Iranian dialysis patients.

Materials And Methods: The study population consisted of 83 randomly selected hemodialysis patients from the dialysis centers in Kerman, Iran. Handgrip strength was measured using a dynamometer according to the recommendations of the American Society of Hand Therapists. All the patients were interviewed and the MIS of the patients were recorded.  Results. The PEW was prevalent in Kerman hemodialysis patients, with 83% and 17% having mild and moderate PEW based on MIS, respectively. Handgrip strength was significantly associated with age, sex, height, weight, and diabetes mellitus. After adjustment for age, handgrip strength was significantly associated with nutritional assessment markers on the basis of the MIS.

Conclusions: Handgrip strength can be incorporated as a reliable tool for assessing nutrition status in clinical practice. However, further research is needed to determine the reference values and cutoff points both in healthy people and in hemodialysis patients to classify muscle wasting.
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January 2016

Using Advanced Statistical Models to Predict the Non-Communicable Diseases.

Iran J Public Health 2015 Dec;44(12):1714-5

Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4724750PMC
December 2015

Predicting the Incidence of Smear Positive Tuberculosis Cases in Iran Using Time Series Analysis.

Iran J Public Health 2015 Nov;44(11):1526-34

Health Sciences Research Center, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran.

Background: Determining the temporal variation and forecasting the incidence of smear positive tuberculosis (TB) can play an important role in promoting the TB control program. Its results may be used as a decision-supportive tool for planning and allocating resources. The present study forecasts the incidence of smear positive TB in Iran.

Methods: This a longitudinal study using monthly tuberculosis incidence data recorded in the Iranian National Tuberculosis Control Program. The sum of registered cases in each month created 84 time points. Time series methods were used for analysis. Based on the residual chart of ACF, PACF, Ljung-Box tests and the lowest levels of AIC and BIC, the most suitable model was selected.

Results: From April 2005 until March 2012, 34012 smear positive TB cases were recorded. The mean of TB monthly incidence was 404.9 (SD=54.7). The highest number of cases was registered in May and the difference in monthly incidence of smear positive TB was significant (P<0.001). SARIMA (0,1,1)(0,1,1)12 was selected as the most adequate model for prediction. It was predicted that the incidence of smear positive TB for 2015 will be about 9.8 per 100,000 people.

Conclusion: Based on the seasonal pattern of smear positive TB recorded cases, seasonal ARIMA model was suitable for predicting its incidence. Meanwhile, prediction results show an increasing trend of smear positive TB cases in Iran.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4703233PMC
November 2015

The incidence of recurrence of tuberculosis and its related factors in smear-positive pulmonary tuberculosis patients in Iran: A retrospective cohort study.

Lung India 2015 Nov-Dec;32(6):557-60

Department of Biostatistics and Epidemiology, Environmental Health Engineering Research Center, Kerman University of Medical Sciences, Kerman, Iran.

Background And Aim: Studying the recurrence of smear-positive pulmonary tuberculosis (TB) is a convenient way to evaluate the effectiveness of TB control programs and identify vulnerable patients. In the present study, the rate of recurrence of TB and its predictors were determined in Iran.

Materials And Methods: This study was a retrospective cohort. Eligible people were patients with smear-positive TB who were diagnosed from 2002 to 2011. The end of the follow-up time was December 2013. The number of people who entered the cohort was 1,271 subjects. In order to determine the predictors of recurrence, multivariate logistic regression was used. Analysis was done using SPSS 20.

Results: The recurrence incidence was 8.3% and in 85.9% of these patients, it occurred in the time interval of 1-5 years after successful treatment. The recurrence rate was not significantly related to gender, age group, and diabetes. But it was significantly higher in patients whose sputum smear grading before treatment was 2 + or more, patients with positive sputum smear at the end of the second month of the treatment, patients who had completed treatment, and patients who were smokers (P < 0.05).

Conclusions: Our study showed that a considerable percentage of smear-positive pulmonary TB patients experience recurrence and that some patients are at a higher risk of recurrence.
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http://dx.doi.org/10.4103/0970-2113.168113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663856PMC
December 2015