Showing 5 results for Survival.
Hossein Bagherian, Shaghayegh Haghjooy Javanmard, Mehran Sharifi, Mohammad Sattari,
Volume 79, Issue 3 (6-2021)
Abstract
This review was conducted between December 2018 and March 2019 at Isfahan University of Medical Sciences. A review of various studies revealed what data mining techniques to predict the probability of survival, what risk factors for these predictions, what criteria for evaluating data mining techniques, and finally what data sources for it have been used to predict the survival of breast cancer patients. This review is based on the Prism statement consisting of published studies in the field of predicting the survival of breast cancer patients using data mining techniques from 2005 to 2018 in databases such as Medline, Science Direct, Web of Science, Embase data and Scopus. After searching in these databases, 527 articles were retrieved. After removing duplicates and evaluating the articles, 21 articles were used. The three techniques of logistic regression, decision tree, and support vector machine have been most used in articles. Age, tumor grade, tumor stage, and tumor size are used more than other risk factors. Among the criteria, the accuracy criterion was used in more studies. Most of the studies used the Surveillance, Epidemiology, and End Results Program (SEER) dataset. Typically, in the field of survival probability prediction, data mining techniques in the field of classification are given more attention due to their adaptation to this field. Accordingly, data mining techniques such as decision tree techniques, logistic regression, and support vector machine were used in more studies than other techniques. The use of these techniques can provide a good basis for clinicians to evaluate the effectiveness of different treatments and the impact of each of these methods on patients' longevity and survival. If the output of these techniques is used to provide the data input required by a decision support system, clinicians can provide risk factors related to the patient, the patient's age, and the patient's physical condition when providing services to breast cancer patients. Through the outputs provided by the decision support system, they provided the most optimal decision to choose the best treatment method and consequently increase patient survival.
Saeed Nateghi, Forough Goudarzi , Samad Taghavi Namin , Atefeh Rasouli , Akram Khalili Noushabadi, Safieh Mohammadnejhad ,
Volume 79, Issue 9 (12-2021)
Abstract
Background: Age is a strong risk factor for increasing the risk of severity and death from Covid-19. The risk of hospitalization for Covid-19 disease increases with age. Since the elderly constitute a large proportion of Covid-19 patients, the present study was performed to evaluate the severity of the disease in the hospitalized elderly due to Covid-19 and the delay in hospitalization and death resulting from it, for better disease management.
Methods: The present retrospective cohort study was performed on 444 elderly patients with Covid-19 admitted from 1 April until late October 2020 in Baharloo Hospital in Tehran, Iran. After being diagnosed using the results of RT-PCR and CT scan, patients, were divided into 3 groups: moderate, severe and very severe based on the severity of the disease. Analysis of variance was used to compare quantitative data and a chi-square test was used to examine qualitative variables in disease groups.
Results: From 444 elderly participants in the study, 73% were infected moderately, 15% severely, and 12% had a very severe form. The mean age was 72.90±8.42 and patients with a very severe form of the disease (75.68±8.28) were older. The average time from the onset of symptoms to hospitalization was 7 days. In the elderly with a very severe form of the disease, respiratory dyspnea (P=0.002) and decreased level of consciousness (P<0.0001) were higher. The average hospital stay was 7 days. In very severe form it lasted up to 11 days. ICU mortality and hospitalization were higher in patients with very severe forms of the disease. With the increasing delay in the days of hospitalization, the severity of the disease and mortality has increased.
Conclusion: The study showed that prolonging the onset of symptoms till hospitalization worsens prognosis and also exacerbates the disease and increases mortality in the elderly.
Zeinab Asakereh, Elham Maraghi, Bijan Keikhaei, Amal Saki Malehi ,
Volume 80, Issue 7 (10-2022)
Abstract
Background: In many studies, Cox regression was used to assess the important factors that affect the survival of cancer patients based on demographic and clinical variables. The aim of this study was to determine the factors affecting the survival of patients with Hodgkin's lymphoma using the random survival forest (RSF) method and compare it with the Cox model.
Methods: In this retrospective cohort study, all patients with Hodgkin's lymphoma who were referred to the Oncology and Hematology Center of Ahvaz Shafa Hospital from March 2000 to February 2010 were included. The survival time was calculated from diagnosis to the first recurrence event date (based on month). To assess the process of the disease, demographic characteristics and disease-related variables (including disease stage, chemotherapy, site of lymph involvement, etc.) were extracted from the records of 387 patients with Hodgkin's lymphoma. To investigate the prognostic factors that affect the recurrence of disease the Cox model and RSF were implemented. Moreover, their performance based on the C-index, IBS, and predictor error rate of the two models were compared Data analysis was implemented by using R4.0.3 software (survival and RandomForestSRC packages).
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Results: The results of the Cox model showed that LDH (P=0.001) and classical lymphoma classification (P<0.001) were associated with an increased risk of relapse in patients. However, the results of the RSF model showed that the important variables affecting the recurrence of disease were the stage of disease, chemotherapy, classical lymphoma classification, and hemoglobin, respectively. Also, the RSF model showed a higher (c-index=84.9) than the Cox model (c-index=57.6). Furthermore, the RSF model revealed a lower error rate predictor (0.09) and IBS index (0.175) than the Cox model. So, RSF has performed better than the Cox model in determining prognostic factors based on the suitability indicators of the model.
Conclusion: The RSF has high accuracy than the Cox model when there is a high number of predictors and there is collinearity. It can also identify the important variables that affect the patient's survival.
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Vahid Varmazyari , Amirreza Rashti, Ali Darakhshandeh, Ayda Moghaddas, Azadeh Moghaddas,
Volume 80, Issue 10 (1-2023)
Abstract
Background: Since numerous chemotherapy regimens for the treatment of patients suffering from acute lymphoid leukemia (ALL) have been recently developed, having basic information about the previous results of using the Hyper-CVAD regimen in order to compare with other common chemotherapy regimens is essential. The aim of this study was to evaluate demographic, clinical and outcome of ALL patients receiving Hyper-CVAD regimen.
Methods: In this retrospective study, nighty eligible ALL patients treated with the Hyper-CVAD chemotherapy regimen in Omid Hospital, Isfahan, Iran during April 2016 till April 2019 were considered. We evaluated the demographic variables, pathological data and other clinical factors by an information sheet designed by main investigator. The main purpose of this study was to evaluate overall survival, progression-free survival, and overall response rate of patients along with patients’ clinical characteristics and other relevant factors using Kaplan-Meier or Cox-regression and other statistical analyses.
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Results: The mean overall survival and the median survival of patients were 44.8±2.93 and 36.7±7.47 months; respectively. Also the mean progression free survival of patients was 44.44±3.30 months. More than 84.4% of patients encountered complete remission (CR) after receiving Hyper-CVAD regimen. Reaching to CR had positive significant effects on patients’ overall survival and median survival. However, the bone marrow transplantation variable alone did not affect the patients’ overall survival. The variables such as being B/T Cell ALL, Philadelphia, myeloid marker, and central nervous system involvement did not affect the overall survival of patients but the relapse index indicated the significant effects. The median survival time is higher in patients with no relapse episode. None of the initial lab data had any significant effects on patients’ overall survival.
Conclusion: For the first time in Iran, we have obtained the mean survival outcome of ALL patients after applying the Hyper-CVAD regimen. According to the results, the mean overall survival, progression free survival and other survival items in Iranian patients suffering from ALL and receiving Hyper-CVAD regimen were in consistent with previous studies in the world.
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Tayebeh Lakzaei, Niloofar Khoshnam-Rad , Maryam Edalatifard , Hamidreza Abtahi,
Volume 81, Issue 3 (6-2023)
Abstract
Background: Despite the progress of medical science and organ transplantation, lung transplantation is associated with significant complications and mortality. In Iran, the first lung transplant was performed in 2000 at Imam Khomeini Hospital in Tehran. So far, there has been no assessment of the patients. The main purpose of this study is to investigate the status of lung transplantation status at this center.
Methods: In this retrospective longitudinal study, all lung transplant patients referred to the Lung Transplantation Center of Imam Khomeini Hospital in Tehran from April 2000 to March 2022 were examined. Demographic and clinical data, and information related to their current status, including pulmonary function tests, transplant-related complications, pharmacotherapy, and drug-related adverse events were recorded. Appropriate statistical analysis was applied.
Results: During the study, 20 lung transplants were observed, 20 percent of transplant recipients were women, and 80 percent were men. The mean age of the patients at the time of transplantation was 39.3±11.4 years. The youngest patient at the time of transplantation was 22, and the oldest was 60 years old. The most common indication for transplantation was interstitial lung disease (70%) followed by chronic obstructive respiratory disease. The average forced expiratory volume in one second (FEV1) value of the patients in the first year was about 50%, which gradually decreased to less than 20 percent in the fifth year. The average survival after transplantation was 5.75±4.6 years. The post-transplant one month, three months, one year, three years, and five years survival were 80, 75, 70, 60, and 50 percent, respectively. Chronic lung allograft dysfunction and serious infections are the most common causes of mortality.
Conclusion: The transplant center at Imam Khomeini Hospital is one of the most important lung transplant centers in Iran. The survival status and transplant outcome are comparable with those reported around the world. More attention should be paid to infection control, patient selection, and perioperative care to improve the outcomes of lung transplantation. |
