ebrahim hajizadeh

Esophageal squamous cell carcinoma (ESCC) is one of the most lethal types of cancer. Late diagnosis significantly decreases patient survival rates.

The study aimed to identify survival groups for patients with ESCC and find predictive biomarkers of time-to-death from ESCC using state-of-the-art deep learning (DL) and machine learning algorithms.

Expression profiles of 60 ESCC patients, along with their demographic and clinical variables, were downloaded from the GEO dataset. A DL autoencoder model was employed to extract lncRNA features. The univariate Cox proportional hazard (Cox-PH) model was used to select significant extracted features related to patient survival. Hierarchical clustering (HC) identified risk groups, followed by a decision trees algorithm which was used to identify lncRNA profiles. We used Python.3.7 and R.4.0.1 software.

Inputs of the autoencoder were 8,900 long noncoding RNAs (lncRNAs), of which 1000 features were extracted. Out of the features, 42 lncRNAs were significantly related to time-to-death using the Cox-PH model and used as input for clustering of patients into high and low-risk groups (P-value of log-rank test = 0.022). These groups were then labeled for supervised HC. The C5.0 algorithm achieved an overall accuracy of 0.929 on the test set and identified four hub lncRNAs associated with time-to-death.

Novel discovered lncRNAs lnc - FAM84A-1 , LINC01866 , lnc - KCNE4-2 and lnc - NUDT12-4 implicated in the pathogenesis of death from ESCC. Our findings represent a significant advancement in understanding the role of lncRNAs on ESCC prognosis. Further research is necessary to confirm the potential and clinical application of these lncRNAs.

We used the multistate model to investigate how prognostic factors of breast cancer are seen to affect the disease process.

This cohort study was conducted at Motamed Cancer Institute of Tehran, Iran on 2363 breast cancer patients admitted from 1978 to 2017, and they were followed up until 2018. We applied the multistate models, including four states: diagnosis, recurrence, metastasis, and final absorbing mortality state.

Age over 50 years, positive lymph nodes and tumor size intensified the hazard of transition from diagnosis to metastasis (P=0.002, P<0.001 and P=0.001 respectively) and they also intensified the hazard of transition from diagnosis to mortality (P=0.010, P<0.001 and P<0.001 respectively). At the same time, the educational level decreased the hazard of mentioned transitions (P<0.001). Positive estrogen receptors reduced the hazard of transition from diagnosis to metastasis (P=0.007) and positive lymph nodes also intensified the hazard of transition from metastasis to mortality (P=0.040). Tumor size had an increasing role in the transitions from diagnosis to recurrence, recurrence to metastasis, and metastasis to mortality (P=0.014, P=0.018 and P=0.002 respectively).

Multistate model presented the detailed effects of prognostic factors on progression of breast cancer. Implementing early diagnosis strategies and providing informational programs, especially in younger ages and lower educational level patients may be helpful in reducing the hazard of transition to higher states of breast cancer and increasing the survival of Iranian women with breast cancer by controlling tumor size growth, lymph nodes involvements and estrogen receptor status.

Breast cancer is the most common cancer among women. Today, with advancements in medical sciences, increasing the cure probability of patients as well as increasing survival time is an important goal of cancer treatment. Therefore, in this study, in addition to examining patients’ survival, we investigated the cure probability of breast cancer patients and its prognostic factors using the semiparametric mixture cure model.

 This is a retrospective cohort study of 1310 breast cancer patients admitted to Motamed Cancer Institute from 1995 to 2013 and followed up until 2018. The Kaplan-Meier curve and a semiparametric mixture cure model were fitted to data. In this model, patients were divided into two categories of cured and uncured, then the cure rate and the survival rate of uncured patients were calculated, and related factors were identified.

 Of the 1310 women with breast cancer in the study, 235 (18.1%) cases died and others were censored. Based on the Kaplan-Meier curve, the cure rate was 68%, and the last death case was observed about 12 years after diagnosis. Obesity, lymph node involvement, and mastectomy were identified as risk factors for patients' long-term survival, while larger tumor size, more advanced stage of the disease, and lack of chemotherapy were risk factors for short-term survival.

 These findings indicate that many prognostic factors for breast cancer are not only important when choosing a treatment strategy in the short term, but they also play an important role in the long-term to identifying high-risk patients and those who still need further follow-up.

Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences, manifesting the “zero‑inflated” nature of the data. Moreover, there often exists a terminal event which may be correlated with the recurrent events. The goal of this study is to extend the application of joint frailty model to identify the prognostic factors associated with curing in patients with breast cancer.

As a prospective study, medical records of women who had been attended to Cancer Research Center, Shahid Beheshti University of Medical Sciences from January 1998 to February 2016 were reviewed. Finally, after an initial review of medical records, 711 patients were included in the study and analyzed. A checklist that included items drawn from the demographic background of patients was provided in the study. Two joint frailty models for zero‑inflated recurrent events, combining a logistic model for “structural zero” status (Yes/No) and a joint frailty proportional hazards model for recurrent and terminal event times were performed to identify factors associated with BCS.

The mean age of patients was 38.2 years. The numbers of subjects with 1, 2, 3, and 4 recurrent events were 392, 207, 97, and 15, respectively. The median follow‑up time was 6.87 years. There were 137 (19.2%) deaths from cancer during the follow‑up. Among the 574 patients who were censored, 418 had no tumor recurrence. Thus, there may exist a large portion of “cured” subjects. We can see that the radiation (OR = 6.02, CI = (3.87, 8.61)) and tumor size interaction with radiation (OR = 1.065, CI = (1.002–1.26)) were significant in the cure model (P < 0.05) which means that patients with smaller tumor sizes were more likely to be cured by radiation therapy.

Our proposed models can help investigators to evaluate which treatment will result in a higher fraction of cured subjects. This is usually an important research question in biomedical studies.

The present study analyzed the factors affecting the survival time of patients with leukemia from diagnosis to death, taking into account the cure rate. The aim of the present study was to apply two models of mixed and unmixed healing in the data of patients with leukemia who received bone marrow transplantation.

In this descriptive-analytical (Cohort) research, the data of 351 patients who were referred to Taleghani Hospital in Tehran affiliated to Shahid Beheshti University of Medical Sciences and received bone marrow transplantation due to leukemia were examined. Patients received bone marrow transplantation between 2007 and 2014 and were followed up until 2016. In this study, the cured models of Bernoulli-Weibull blended (taking into account the Bernoulli distribution for latent variables and the Weibull distribution for survival time) and the Poisson -Weibull blended cured model (considering the Poisson distribution for latent time variables for hiding and distribution and distribution for survival time) were fitted to the data.

In this study, 351 patients, 197 males (56.1%) and 154 females (43.9%), were studied in which 67 patients (19.1%) died. Among the significant variables of recurrence after transplantation, recurrence before transplantation, hemoglobin, type of transplant, age, body mass, blood type and type of diagnosis, variables age (p=0.01), recurrence after transplantation (0.03) and type of transplant (p=0.03) are among the variables affecting the survival time of leukemia patients. In the mixture cured model of Bernoulli-Weibull and the variables of age (p=0.004), recurrence after transplantation (p=0.013) and type of diagnosis (p<0.008) were variables affecting the survival time of leukemia patients in the non-mixture cured model Poisson -Weibull.

Patients with autologous bone marrow transplantation under the age of 30 have a better chance of survival, and also the non-mixture cured model has a better outcome than the mixture cured model.

The aim of this study was to investigate the burden of breast cancer (DALY Index) trend in Iran and compare it with the Eastern Mediterranean region (EMR) and finally to predict the burden of this disease.

Equalization of breast cancer burden trend in Iran and the EMR during the years 1990 to 2017 was tested using Cochrane Armitage method. The trend of changes in breast cancer burden in Iran and the EMR during this period was examined by three regression models and the best model was determined based on the model utility indicators. DALY index prediction between 2018 and 2027 was performed using exponential smoothing procedure.

Statistically, DALY index trend in Iran and the EMR did not differ significantly. In Iran, the DALY index in 2013 increased from equivalent index in the EMR. The trend of DALY index in Iran has increased rapidly from 2000 to 2015 and then, until 2017, the growth rate of this index decreased and according to the forecast from 2018 to 2027, a slight increase in this index will expect. In the EMR, the growth rate of the DALY index increased from 1990 to 2006 with a steady slope, then, by 2017, the slope of growth had slowed slightly and according to the forecast model, the trend of the DALY index until 2027 will be similar to the 2006 to 2017 period.

Due to the increasing trend of breast cancer over the past years, as well as increasing prediction of this trend, preventive measures such as designing a regular screening program and training and lifestyle modification are recommended.

Missing values are frequently seen in data sets of research studiesespecially in medical studies.Therefore, it is essential that the data, especially in medical research should evaluate in terms of the structure of missingness.This study aims to provide new statistical methods for analyzing such data.

Multiple imputation (MI) and inverse-probability weighting (IPW)aretwo common methods whichused to deal with missing data. MI method is more effectiveand complexthan IPW.MI requires a model for the joint distribution of the missing data given the observed data.While IPW need only a model for the probability that a subject has fulldata .Inefficacy in each of these models may causeto serious bias if missingness in dataset is large .Anothermethod that combines these approaches to give a doubly robust estimator.In addition, using of these methodswill demonstrate in the clinical trial data related to postpartum bleeding.

In this article, we examine the performance of IPW/MI relative to MI and IPW alone in terms of bias and efficiency.According to the results of simulation can be said that that IPW/MI have advantages over alternatives.Also results of real data showed that,results of MI/MI doesnot differ with the results of IPW/MIsignificantly.

Problem of missing data are in many studies that causes bias and decreasing efficacy inmodel.In this study, after comparing the results of these techniques,it was concludedthat IPW/MI method has better performance than other methods.

Restenosis after coronary angioplasty can have serious complications such as coronary artery bypass graft, myocardial infarction, and death.

The present study aimed at investigating the factors affecting the recurrence of coronary artery stenosis in patients undergoing angioplasty using the recurrent event data analysis.

A cohort study was performed on patients undergoing coronary angioplasty from March 23, 2009, to January 21, 2011. All patients were followed up from angioplasty to January 21, 2015. First, each of the independent variables was entered into the univariate Cox model with a frailty component. Then, variables with p-values of less than 0.2 were entered into the multivariate analysis. The statistical analysis was done using R software, version 3.6, at the significance level of 0.05.

The present study was conducted on 1,000 patients who underwent coronary angioplasty. We found that 441 patients experienced restenosis at least once in the study period. The mean survival time to the first event of restenosis was 44.08 ± 1.06 months. Patients with a history of diabetes, unstable angina, and myocardial infarction had a significantly higher hazard of restenosis compared to other patients (P < 0.05).

The results of the recurrent event survival analysis confirmed the significant role of risk factors such as a history of diabetes, unstable angina, and myocardial infarction. Therefore, training to enhance the patients’ awareness and attitude seems necessary to prevent them from exposing whit known risk factors. The periodic follow-up of patients with risk factors and more ongoing care are also necessary.

Nowadays, cancer is one of the most important medical problems. Breast cancer is also considered as the most common cancer of women: its prevalence has risen throughout the world in recent centuries and people can experience recurrent events that sometimes accompany with a terminal event. In the present study, using a frailty model we tried to model recurrent event in the precence of terminal event (death) in breast cancer patients.

In the current retrospective survival study, 342 patients with breast cancer registered in the cancer research center of Shohada-e-Tajrish Hospital were examined. The Liu model was used to joint modeling of recurrent events and terminal events, in which a shared frailty with Gamma distribution was used. Estimation of the parameters was done by the penelized maximum likelihood method and the frailtypack package in the R software version 3.4.1 was used to implement the model and analyzed the data. Significance level was set at 0.05.

In our cohort study, 342 women with breast cancer were studied. A univariate and multivariate analyses was performed for these patients. Of these, 78 cases (25.4%) had recurrence events, and 225 patients (74.6%) were censored. The obtained results of joint frailty model indicated that the relative risk of relapse in patients with first-degree familial history was 36% higher than that of other people (P <0.05). Relative risk of relapse in patients with stage 3 disease was 19% more than other stages and also the relative risk of relapse in patients with chemotherapy were 2.5 times higher than those without chemotherapy.

It seems that by investigating the effects of factors affecting the occurrence of recurring events with death with regard to unknown factors, such as modeling, we can simultaneously simulate the probabilistic nature of the disease and provide more accurate information to the researchers.

Breast cancer is one of the most common recurrence cancers among women. There are several factors that can affect multiple recurrence of this disease. On the other hand, simultaneous examination of the types of relapses will make the results more accurate. The purpose of this study was to use a joint frailty model to model multiple recurrences of breast cancer patients.

In this retrospective survival study,342 breast cancer patients whose records were registered at the Shohada Tajrish Hospital Cancer Research Center (Tehran, Iran) were investigated in 2005-2015. Patients were monitored for at least 6 months after diagnosis and their last condition was recorded in this study, the joint frailty survival model was used and data analysis was done in R software version 3.4.1.

The 3-year and 5-year survival rates were 0.79 and 0.68 respectively. According to the results of the fitted joint frailty model, it can be said that the risk of multiple recurrence is increased for patients with tumor grade greater than I. Also, tumor size (>20 mm) has a significant effect on the risk of recurrence and the risk of local and metastatic recurrence is more for HER2+ patients.

According to the results of this study, the relationship between metastasis and local relapses was high in breast cancer patients, which has great importance in the process of recognizing and treating of this disease. Although in this study, in a large sample of patients, there was a positive correlation between multiple recurrences, but these results should be considered with caution with small number of recurrences.

Child growth impairment (GI) causes much psychological, physical and economic harm to the community while a healthy growth and development at early childhood ensures access to a healthy society. This study aimed to evaluate the factors affecting GI of children under 6 years of age by using marginal models inWest Azerbaijan Province, Iran. In this longitudinal cohort study, 1070 children below 6 years were in a two-stage cluster sampling randomly selected and studied. The growth characteristics of the studied children (height, weight) and their development features (walking, speaking and teething age) were recorded, during a 6-year follow-up. Data were collected by R statistical software and analyzed by using independent marginal model. The results of this study showed that maternal age at the time of birth (P = 0.001) also her educational level (P < 0.05) and occupational status (P = 0.000), birthing method (P = 0.001), child’s gender (P = 0.000), breastfeeding (P = 0.000) and child’s walking age (P = 0.000) had a significant effect on GI. Present study revealed that the demographic factors and child’s walking age have a significant effect on children’s GI. At early childhood, GI influences many domains of individual’s life and subsequently the society status. So, it is recommended that the determinants of this crucial threat to be identified and effective plans to be provided for any problems that may arise at this time.

Generalized anxiety disorder (GAD) is a common disorder in infertile people. The aim of this study was the identification of associated risk factors for the severity of GAD in infertile people using an ordinal model with a flexible link function. This cross‑sectional study was conducted on 1146 individuals with a couple’s infertility problem selected from an infertility center in Tehran, Iran. Data collected using self‑administered questionnaires include demographic/clinical information and GAD‑7. We used a Bayesian‑ordered symmetric power logit (splogit) model to identify the risk factors for the severity of GAD. Furthermore, we implemented standard ordinal models to compare with the ordered splogit model. Female gender (B coefficient 0.48, 95% credible interval [CrI]: 0.34–0.62), longer duration of infertility (B coefficient 0.03, 95% CrI: 0.01–0.04), previous treatment failure (B coefficient 0.17, 95% CrI: 0.03–0.30), and self‑cause of infertility (B coefficient 0.12, 95% CrI: 0.01–0.23) were associated factors with the severity of GAD. The splogit model had a better fit and performance to determine the associated risk factor for the severity of GAD as compared to standard models. It provided more precise estimates of risk factors and one more significant risk factor. Infertile people with female gender, longer duration of infertility, failure in previous treatments, and self‑cause infertility are more likely to experience higher severity levels of GAD and require additional psychological, and support interventions. Furthermore, it can be argued that the ordinal splogit model is more powerful to identify the associated risk factors for the severity of GAD.

Tumor stage is one of the most reliable prognostic factors in the clinical characterization of colorectal cancer. The identification of genes associated with tumor staging may facilitate the personalized molecular diagnosis and treatment along with better risk stratification in colorectal cancer. The study aimed to identify genetic signatures associated with tumor staging and patients’ survival in colorectal cancer and recognize the patients' risk category for clinical outcomes based on transcriptomic data. In this retrospective cohort study, two available transcriptomic datasets, including 232 patients with colorectal cancer under accession number GSE17537 and GSE17536 were used as discovery and validation sets, respectively. A Bayesian sparse group selection method in the discovery set was applied to identify the associated genes with the tumor staging. Then further screening was performed using survival analysis, and significant genes were used to develop a gene signature model. Finally, the robust performance of the signature model was assessed in the validation set. A total of 56 genes were significantly associated with the tumor staging in colorectal cancer. Survival analysis resulted in a shortlist of 19 genes, including ADH1B (P = 0.012), AHI (P = 0.006), AKAP12 (P = 0.018), BNIP3 (P = 0.015), CLDN11 (P = 0.015), CST9L (P = 0.028), DPP10 (P = 0.029), FBXO33 (P = 0.036), HEBP (P = 0.025), INTS4 (P = 0.003), LIPJ (P = 0.001), MMP21 (P = 0.006), NGRN (P = 0.014), PAFAH1B2 (P = 0.035), PCOLCE2 (P = 0.009), PIM1 (P = 0.007), TBKBP1 (P = 0.003), TCEB3B (P = 0.001), and TIPARP (P = 0.018), developing the signature model and validation. In both discovery and validation sets, the discrimination ability of the signature model to categorize patients with colorectal cancer into low- and high-risk subgroups for mortality and recurrence at 3- and 5-years showed good discrimination performances, with the area under the receiver operating characteristic curve (ROC) ranging from 0.64 to 0.88. It also had good sensitivity (discovery set 63.1%, validation set 61.7%) and specificity (discovery set 75.0%, validation set 59.3%) to discriminate between early- and late-stage groups. We identified a 19-gene signature associated with tumor staging and survival of colorectal cancer, which may represent potential diagnosis and prognosis markers, and help to classify patients with colorectal cancer into low- or high-risk subgroups.

This study aimed to design and assess a comprehensive questionnaire about the violence against women in an Iranian population. This study was a sequential exploratory mixed method.. According to the results of the qualitative Research and the revising of texts ,the primitive instruments were designed. Face validity ,content validity (by measuring content validity toward content validity index)and construct validity(by analysis of exploratory factor) were used to determine the validity of instruments and therefore internal consistency and test-retest method were used to determine reliability of instruments.In face validity 7items were excluded due to a score less than 1.5.In content validity by taking the 0.79 cut-off point to assess content validity index and 0.59 cut-off point to 34 items were elimented. And thus the number of items reduced to 58. validity by exploratory factor analysis was performed. Exploratory factor analysis suggested a six-factor model items including: Social factors undermining family stability, unhealthy life skills of couples, improper and insufficient teachings to couples , unhealthy treating of wives toward their husbands, Family support paradox, immediacy. These six factors explained 75% of variance violence against women. therefore internal consistency and test-retest method were used to determine reliability of instruments(α=0.987), (ICC=0.992).
Considering that all validity and reliability indexes of the questionnaire are reported in an appropriate level, violence against women’ questionnaire can be used as a valid and reliable questionnaire in measuring domestic violence in Iranian married men. However ,future research is recommended to evaluate usability of the study in other cultural settings.

Data types are recurrent events in studies in which each person may experience an event at different times. One of the most popular approaches to analyze recurrent event data is obtaining an estimate of the means/rate of events at different times. In this context, determining the variability over time can help better understand the effect of factor on the response. In this study, we applied smoothing methods to estimate coefficients in time-dependent rate model, and we also showed its application in data of psoriasis patients.

In the present study, psoriasis patients who experienced relapse that led to hospitalization during 2005 and 2014 in the Dermatology Department of Imam Khomeini hospital in Tehran were examined. To investigate the rate of relapse during a year, time-dependent rate model was used and variability of the effects was assessed using Wald test. Both b-spline and kernel methods were used to estimate time varying coefficients in rates model. Finally, results from methods were compared based on the obtained estimates.

Based on the results of the Wald test, the effect of season on the occurrence of psoriasis was significantly different (p<0.01). Also according to the estimated coefficients from both b-spline and kernel methods, there was little difference between them.

In situations in which the effect of a variable is different at different times, using time-dependent coefficients rate model can lead to a better estimate of the effect of variable on the response. On the other hand, smoothing methods can smooth the effects of the variables that vary over time.

Breast cancer is one of the most common recurrence cancers among women. There are several factors that can affect the multiple recurrence of this disease, which have been studied and recognized in various studies, however, with the fact that these factors are known, cannot always accurately predict the incidence of metastasis. On the other hand, simultaneous examination of the types of relapses will make the results more accurate. One of the types of models used to analyze recurrent events with heterogeneity among patients is a frailty model. The purpose of this study was to use a joint frailty model to model multiple recurrences in breast cancer patients data. In this retrospective study, 342 breast cancer patients whose records were registered at the Shohada Tajrish Hospital Cancer Research Center were investigated. Patients were monitored for at least 6 months after diagnosis, and their last condition was recorded. For data analysis, the joint frailty survival model was used. Data modeling and data analysis were done in R software. The three-year and five-year survival rates for patients were respectively 0.79 and 0.68 respectively. According to the results of the fitted joint frailty model, it can be said that the risk of multiple recurrence (local and metastasis) is increased for patients with tumor grade greater than I. We also found that if we did not consider the relationship between multiple recurrence in patients with breast cancer, we would lose significant correlation. Considering the significant variance of the frailty component of the metastasis event, it can be concluded that patients with the same predictor variables also have a different metastasis risk and, on the other hand, given the low frequency of types of recurrences in this study, the results should be considered with caution.

Recurrent event data are often encountered in biomedical research, for example, recurrent infections or recurrent hospitalizations for patients after renal transplant. In many studies, there are more than one type of events of interest. We aimed to identify the association between two types of events using multivariate joint modeling and then apply this statistical method in the clinical data set. Study design: A retrospective cohort study Overall, 342 subjects with breast cancer whose records were registered for follow-up in a Cancer Research Center at Shohadaye Tajrish Hospital, Tehran, Iran from 2006 to 2015 were investigated. These patients were monitored for at least 6 months after diagnosis and their latest status were recorded. Joint frailty model was used for modeling the relationship between two types of recurrences with Frailty package in R software. When the terminal event was considered as death, three-year and five-year survival rates for the patients were 0.79 and 0.68, respectively. Given the results obtained from a fitted joint frailty model, the risk of multiple recurrences (local and metastases) increased for the patients with tumor grades greater than I. With regard to the significant variance of the frailty component of the metastases event, it can be inferred that patients with the same predictive variables are prone to different levels of metastases risk and, on the other hand, given the low frequency of types of recurrences, caution should be exercised when considering the obtained results.

Individuals with breast cancer may experience multiple types of recurrence and a terminal event during their life. Follow-up may be interrupted for several reasons, including patients lost to follow-up or end of a study. Death is considered as a dependent terminal event. The main objective was to model the dependency between (locoregional and metastaticrelapses and death in breast cancer patients. This retrospective cohort study was conducted in Cancer Research Center, Shahid Beheshti University of Medical Sciences on 342 patients with BC. Patients were followed up to 20 years from January 1996 until February 2015. This study considers the analysis of diseases recurrence and survival for joint modeling of three correlated evens: Local recurrence, metastasis, and death. The aims are to detect the effects of relapses on death and the correlation between local and distant recurrences. We propose a joint frailty model for multiple recurrent events with a terminal event. According to all obtained results of the fitted models, the risk of local and metastatic relapses or death increased for women with positive lymph node (N+) or for women with a grade higher than I. Also, it was found that if the association between these 3 times to events are not taken into account, we may lose a significant association. The variable HR+ was significantly correlated with the hazards of two types of recurrences, and death for both reduced and proposed models (P < 0.05). We concluded that the risk of locoregional recurrences is correlated with the risk of metastatic and the risk of metastatic relapse is also correlated with death. In this special setting, it can be difficult to get an independence between locoregional and distant recurrences. Also, these results should be considered with caution, with the few number of recurrences.

Individuals with breast cancer may experience multiple types of recurrence and a terminal event during their life. Follow-up may be interrupted for several reasons, including patients lost to follow-up or end of a study. Death is considered as a dependent terminal event. The main objective was to model the dependency between (locoregional and metastaticrelapses and death in breast cancer patients. This retrospective cohort study was conducted in Cancer Research Center, Shahid Beheshti University of Medical Sciences on 342 patients with BC. Patients were followed up to 20 years from January 1996 until February 2015. This study considers the analysis of diseases recurrence and survival for joint modeling of three correlated evens: Local recurrence, metastasis, and death. The aims are to detect the effects of relapses on death and the correlation between local and distant recurrences. We propose a joint frailty model for multiple recurrent events with a terminal event. According to all obtained results of the fitted models, the risk of local and metastatic relapses or death increased for women with positive lymph node (N+) or for women with a grade higher than I. Also, it was found that if the association between these 3 times to events are not taken into account, we may lose a significant association. The variable HR+ was significantly correlated with the hazards of two types of recurrences, and death for both reduced and proposed models (P < 0.05). We concluded that the risk of locoregional recurrences is correlated with the risk of metastatic and the risk of metastatic relapse is also correlated with death. In this special setting, it can be difficult to get an independence between locoregional and distant recurrences. Also, these results should be considered with caution, with the few number of recurrences.

The health system in Iran faces specific challenges as the managerial role of head nurses have changed. The importance of this role cannot be underestimated for the healthcare organizations’ success. The present study was conducted to explore the meaning of managerial competence of head nurses in intensive care units (ICU) in Iran.
This study used a qualitative approach. We extracted the lived experience of ten Iranian ICU head nurses. Data were collected through unstructured in‑depth interviews from 2014 to 2015. Interviews were recorded and transcribed verbatim and were interpreted using Van Manen’s six‑step approach.
The expansion and clustering of 442 initial themes led to the emergence of 35 secondary themes, nine subthemes, and three main themes. Managerial competence – theme included “self‑excellence,” “ward excellence,” and “intensive care excellence.”
The “managerial competence of ICU head nurses” is a dynamic concept that reflects the psychological and functional capability of head nurses in contributing towards excellence in their own critical care practice as well as that of the ward. A competent head nurse has outstanding personal and nursing attributes and holistic knowledge, and is also committed to the ongoing professional improvement of him/herself. Using their ability to facilitate interpersonal and interprofessional communication effectively, a head nurse seeks the psychological, physical, and human optimization of the ward in which he/she works. Therefore, the goal of providing insightful critical care through smart organization and planning of nurses and other personnel can be achieved.

Aims :

Breast cancer is one of the most prevalent recurrent cancers among women. Several factors affecting multiple recurrences of this disease have been studied and recognized in various studies. One of the various types of models used to analyze recurrent events considering the lack of homogeneity among patients is a frailty model. The aim of the present study was to investigate joint frailty modeling for multiple recurrent events and its application in patients with breast cancer.

Materials and Methods:

 In this survival and retrospective analysis, 342 patients with breast cancer whose records were registered for follow-up in a Cancer Research Center at Shohadaye Tajrish Hospital, Tehran, Iran, from 2006 to 2015, were selected. The sampling method was purposive. These patients were monitored for at least 6 months after diagnosis and their latest statuses. For data analysis, the joint frailty survival model was used. Running the model and conducting the data analysis were performed by codes in Frailtypack using R 3.4.1 statistical software. 

Findings:

Three-year and five-year survival rates for the patients were 0.79 and 0.68, respectively. The risk of multiple recurrences (Local and metastases) increased for the patients with tumor grades greater than I. It was found that when neglecting the relationship between multiple recurrences in the patients with breast cancer, a significant correlation was missed.

Conclusion :

With regard to the significant variance of the frailty component of the metastases event, the patients with the same predictive variables are prone to different levels of metastases risk.

In oncology studies, categorizing a quantitative prognostic variable or determining cut point is aimed at categorizing individuals into homogenous groups. Such categorizations are useful for treatment recommendations and clinical trial design.
This article aims at determining the cut point for breast cancer diagnosis age by factors affecting the patients’ survival, using cure model.
In this longitudinal study, a total 559 patients with breast cancer referring to breast cancer research center, Tehran, Iran, from 1986 to 2006 entered the study. Patients were followed until 2013. The last status of patients was recorded, using telephone conversation. Then, the cut point of breast cancer diagnosis age was determined, using change point cure model with survival-related covariates and R v.2.15.0 software.
In the present study, the mean age of diagnosis was reported 46.31 ± 11.17. Median time of follow-up was 68.36 months with the range of 0.89 to 324. The results showed that age cut point was 49.45 (± 0.64). In young group, one unit increase in tumor size led to 57% reduction in the chance of cure. In old group, the chance of recovery declined by 51%. In old group, the chance of cure among those with lymph node declined by %61 compared to those without lymph node. In the young group, this variable was not significant. Level of education, type of surgery, and estrogen receptor had no significant relationship with cure in none of the age groups at 5% error level.
The results showed that the effect of age in breast cancer prognosis is adjusted at 50-year cut point, leading to two relatively homogeneous groups. This cut point is effective in assessing predictive and prognostic factors in breast cancer. The difference between effect of tumor size and effect of lymph node involvement in different age groups can be helpful in determining more appropriate therapeutic strategies.

Background and Appropriate health services including sexual health are regarded as human rights especially for women. The aim of this study was to determine the extent and causes of lack of sexual health services in women attending health centers, and providing a suitable strategy for their elimination.
This study was conducted using a sequential explanatory mixed method in 2014. The first phase of the study was done in 514 women who referred to Sari health centers applying a cross-sectional design. Women who did not receive even one of the sexual health services entered the qualitative phase of the study, which was done by conventional qualitative content analysis. Then, the two phases were combined. Nominal group technique was used to prioritize the strategies about sexual health services.
The quantitative phase showed that 20% of females and 50% of male partners did not seek treatments for genital ulcers or abnormal secretions. None of the males with multiple spouses have used condoms at their last sexual intercourses. According to the qualitative phase, two reasons were found for not receiving sexual health services: the lack of women's attendance to health centers and non-accountability of health centers to women's sexual health needs.
The current health system in Iran does not respond to women’s sexual health needs. Therefore, in Iran, sexual health services are suggested to be integrated with the health system alongside empowering women about their health needs and increasing men's awareness in providing women's sexual needs.

Growth failure, constituting one the health problems in children below 2 yr of age, can lead to major complications such as death or mental, emotional and physical disabilities. The present study aimed to investigate effective factors on growth failure in the height and weight of less than 2 yr old children of Khorramabad, Iran in 2013.
This present longitudinal retrospective study used stratified and clustered sampling. Based on growth curves in family records, the incidence times of growth failure in height and weight of each child were recorded. In the next stage, using recurrent events model (proportional rate model), along with SAS software (version 9.2), the data were modeled.
According to proportional rate model, the effect of mothers’ educational level on the rate of growth failure in the height and weight of children was significant (P=0.046, P=0.049) and the effect of fathers’ job was significant only on growth failure in children’s weight (P Enhancing mother’s awareness in low-income families, in tandem with changing educated mothers’ attitude towards the required skills and guiding principles for feeding children below 2 yr of age, can be conceived of as the most important approach in dealing with growth failure of children.

Non-compliance is a concern to all healthcare disciplines especially in patients with chronic illness that is caused by social factors. For determining the factors affect on patient's health, it is essentialto understand the meaning of compliance and its measurement which lead to improve compliance. However, there is not any instrument to assess compliance of all dimensions of treatment in patients with chronic disease in Iranian context. The purpose of this study was to develop and psychometric properties of compliance questionnaire.
This study was conducted by triangulation approach in two concept analysis and methodological research sequential phases. In first part, Hybrid Model concept analysis was used to explore the meaning of compliance and to generate questionnaire items, and in second part psychometric properties was used to evaluate the validity and reliability of a compliance instrument.First, in theoretical phase of Hybrid Model concept analysis, data was collected by using literature reviews to develop a working definition. Second in field work phase qualitative data obtained through semi-structure interviews withparticipatingof 6 patients diagnosed with chronic disease. Third, in analytical phase, integration and reanalysis of the data gained during two former phases of concept analysis was conductedusing directed qualitative content analysis. In second part, a primary questionnaire was created by using the results of research. In the third part, the psychometric properties including face validity, content validity, construct validity, internal consistency, and test-retest reliability was measured.
The process of concept analysis in theoretical phase resulted in extracting 11 categories,in field work phase seven categories and in third phaseeight themes emerged. 127 items was extracted.The psychometric property was carried out as a result the 127-item questionnaire was modified and the items decreased to 48. The result of exploratory factor analysis showed that this questionnaire contains 7 factors including making effort for treatment, intention to take the treatment, adaptability, integrating illness into life, stick to the treatment, commitment to treatment and indecisiveness for applying treatment and the items decreased to 40. The 7 factors explained nearly 48.514% of the variance of the questionnaire. The reliability was carried out by using test-retest reliability andCronbachsalpha 0.92.
These findings offer helpful insights into the meaning of compliance and provide an instrument to assess the adherence of patients with chronic disease. The Adherence Questionnaire appears to be an appropriate tool for providing reliable and valid data to determine compliance in adult patients with chronic disease in Iranian context.