Background & Objectives: The analysis of age and survival probabilities, today, is several decades old. The calculation of age average in different groups of human society and analysis of factors which are effective on it to access methods for increase of individual’s health and age is one the daily concerns of scientists in different branches of biology and medicine. The objectives of this study were to assess the effects of prognostic factors on survival of patients with breast cancer using the Aalen Additive Hazards Model, and to illustrate the advantage of Aalen’s plot.Materials & Methods: during 2005-2007, 133 women with breast cancer were treated in Fayazbakhsh hospital, Tehran. All patients followed until 2011 April. To analysis data, Aalen’s Additive Hazard Model used. The graph of estimated cumulative regression function (Aalen s graph) was draw to analyze the effect of independent variable during time.Results: Significant factors in univariate analysis was entered into multivariable analysis of Allen`s Additive Hazard Model.HER2, third tumor malignancy grade and the number of positive lymph nodes more than10 were recognized as significant factors in patient`s survival in multivariable Model.Conclusion: Additive Hazard Model is used as a suitable substitution for Cox Model. In which standard deviation of estimations will be smaller than Cox Model.

Adding parameters to a known distribution is a valuable way of constructing flexible families of distributions. In this paper, we introduce a new Model, the modified Additive Hazard rate Model, by replacing the Additive Hazard rate distribution in the general proportional add ratio Model. Next, when two sets of random variables follow the modified Additive Hazard Model, we establish stochastic comparisons between the series and parallel systems comprising these components.

Background & Objective: In most countries, heart diseases are known as first cause of death among non-contagious diseases and in Iran it is one of the most important causes of death. Therefore assessing risk factors associated with survival of these patients is necessary. In this study, effect of some risk factors on Hazard of death of subjects with acute myocardial infarction (AMI) is investigated.Materials & Methods: In this historical cohort study, 197 patients that experience AMI for the first time was studied which were admitted in Bushehr hospitals during 1997-2001. Aalen’s Additive Hazard Model used in this study to assess the relation of death Hazard rate after first AMI and risk factors like age at time of infarction, patient’s sex, systolic and diastolic blood pressure, serum total cholesterol, LDL and HDL.Results: Average survival time of patients in the present study was more than 4 years. The result showed that there is no significant relation between sex and survival time of patient (p>0.05) however age at time of infarction has a significant relation with survival of patient (p<0.05).Conclusion: According to Aalen’s Additive Hazard Model as age at time of infarction increases, survival risk of AMI patients increases.

Often, reliability systems suffer shocks from external stress factors, stressing the system at random. These random shocks may have non-ignorable effects on the reliability of the system. In this paper, we provide sufficient and necessary conditions on components' lifetimes and their survival probabilities from random shocks for comparing the lifetimes of two $(n-1)$-out-of-$n$ systems in two cases: (i) when components are independent, and then (ii) when components are dependent.

Background: Recent studies have shown that effective genes on survival time of cancer patients play an important role as a risk factor or preventive factor. Present study was designed to determine effective genes on survival time for diffuse large B-cell lymphoma patients and predict the survival time using these selected genes.Materials & Methods: Present study is a cohort study was conducted on 40 patients with diffuse large B-cell lymphoma. For these patients, 2042 gene expression was measured. In order to predict the survival time, the composition of the semi-parametric Additive survival Model with two gene selection methods elastic net and lasso were used. Two methods were evaluated by plotting area under the ROC curve over time and calculating the integral of this curve.Results: Based on our findings, the elastic net method identified 10 genes, and Lasso-Cox method identified 7 genes. GENE3325X increased the survival time (P=0.006), Whereas GENE3980X and GENE377X reduced the survival time (P=0.004). These three genes were selected as important genes in both methods.Conclusion: This study showed that the elastic net method outperformed the common Lasso method in terms of predictive power. Moreover, apply the Additive Model instead Cox regression and using microarray data is usable way for predict the survival time of patients.

Background and Objectives: Colorectal cancer is the fourth leading cause of cancer death worldwide. Annually 1430000 cases would be diagnosed and half of these people would die of the disease. In Iran, colorectal cancer is the fifth common cancer among men and is the thirdamong women. This study was designed to estimate survival rates for patients with colorectal cancer and related factors.Methods: During the 1384 to 1388 years 24, 807 patients diagnosed with colorectal cancer were recorded in the Cancer Registry of the Ministry of Health and Medical Education. Age, gender, marital status, education, occupation, place of residence, tumor diagnosis, the clinical and demographic factors in colorectal cancer as effective on survival entered in Aalen’s Additive Hazard Model and diagram Aalen's was used to study the effects of these factors over time. R 3.2.0 software was used for data analysis.Results: Stage of tumor had a significant association with survival rates. In this study 1 to 5 year survival rate for patients with stage II tumors, was 100%, 98%, 96%, 93% and 93% respectively and for patients with stage III tumors 99%, 97%, 94%, 90% and 84%, respectively.Conclusion: In spite of using Cox Model in survival analysis by many researchers, Aalen’s Model may yield new insights in prognostic studies of survival time of patients with colorectal cancer over time. Our results suggest that early detection of patients in primary stage is important to increase survival.

Whether directly in the form of expenses or indirectly, the objective of maintenance in the mining industry is self-evident in time losses and loss of production. In this paper, the reliability-based maintenance is examined with a different insight than before. The system goes back to the Good As New (GAN) state or too Bad As Old (BAO) maintenance state; why so, the maintenance of the system shifts to the midrange state. On the other hand, the implementation of repairs is strongly influenced by the environmental factors that are known as the “ risk factors” . Therefore, an analysis requires a Model that integrates two basic elements: (1) incompleteness of the maintenance effect and (2) risk factors. Thus, an extensive proportional Hazard ratio Model (EPHM) is used as a combination of the Proportional Hazard Model (PHM) and the Hybrid Imperfect Preventive Maintenance Model (HIPM) in order to analyze these elements. In this regards, four different preventive maintenance strategies are proposed. All four strategies are time-based including constant interval or periodic (the first and second strategies) and cyclic interval (the third and fourth strategies). The proposed method is applied for a Komatsu HD785-5 dump-truck in the Songun copper mine as a case study. The PM intervals with a mean value of risk factors for the four activities to reach the 80% reliability for the first and second strategies are about 5 and 48 hours. These intervals for the third strategy are calculated as 48. 36, 11. 58, 10. 25, and 9. 035, and for the fourth strategy are 5. 06, 4. 078, 3. 459, and 1. 92.

One of the most important parts of the driver reaction is detecting Hazard in prominent time. A Hazard is detected in the right time if it is completely visible for the driver. There are various Hazard types such as fixed obstacles، pedestrians، and animals that some of them cross the road. Right-time Hazard detection and the post-reaction is of high importance in accident prevention. It is assumed، in this paper، that increasing crossing speed of Hazards affects the driver's Hazard detection. Different driver types including novice، low-experienced، and experienced drivers are chosen and various environmental scenarios are also designed. The eventual suggested Model is Fuzzy Sugeno that estimates relation between the driver's detection score and the Hazards' crossing speed. The results show that Hazards' crossing and also increased crossing speed raises drivers' detection score and decreases reaction time. The increasing slope of the drivers' detection score diagram in relation with Hazards' crossing speed in different conditions is 2% to 50%. The results are useful in training and Hazard perception and detection tests، especially، for novice drivers and also، in making fixed and low-speed crossing Hazards recognizable.