• Title, Summary, Keyword: survival

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Follow-Up Study of Survival of Patients with Advanced Cancer in a Hospice Setting

  • Wang, Yu-Mei;Guo, Hai-Qiang
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.7
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    • pp.3357-3360
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    • 2012
  • Objective: This study was to present the survival of advanced cancer patients and explore the influence of various factors on survival time as well as survival rate. The results provide guidelines for clinical practice of cancer treatment. Methods: Follow-up of 674 advanced cancer patients was performed in a hospice. The median survival time and survival rate were calculated, and survival analysis was carried out. Results: The median survival time of all patients dying from cancer was 12.0 months and the average survival time was 25.1 months. The 1-year cumulative survival rate was $0.518{\pm}0.020$ and the 5-year cumulative survival rate was $0.088{\pm}0.012$. The following factors showed significant impacts on survival rate: gender, age, primary diagnosis, surgery and the time when pain appeared. Conclusions: The survival time of patients with advanced cancer was relatively short. Major approaches to extend the survival time include early detection, early diagnosis, effective surgical treatment, pain control, reasonable supply of nutrients and multiple interventions.

Five-Year Survival and Median Survival Time of Nasopharyngeal Carcinoma in Hospital Universiti Sains Malaysia

  • Siti-Azrin, Ab Hamid;Norsa'adah, Bachok;Naing, Nyi Nyi
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.15
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    • pp.6455-6459
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    • 2014
  • Background: Nasopharyngeal carcinoma (NPC) is the fourth most common cancer in Malaysia. The objective of this study was to determine the five-year survival rate and median survival time of NPC patients in Hospital Universiti Sains Malaysia (USM). Methods: One hundred and thirty four NPC cases confirmed by histopathology in Hospital USM between $1^{st}$ January 1998 and $31^{st}$ December 2007 that fulfilled the inclusion and exclusion criteria were retrospectively reviewed. Survival time of NPC patients were estimated by Kaplan-Meier survival analysis. Log-rank tests were performed to compare survival of cases among presenting symptoms, WHO type, TNM classification and treatment modalities. Results: The overall five-year survival rate of NPC patients was 38.0% (95% confidence interval (CI): 29.1, 46.9). The overall median survival time of NPC patients was 31.30 months (95%CI: 23.76, 38.84). The significant factors that altered the survival rate and time were age (p=0.041), cranial nerve involvement (p=0.012), stage (p=0.002), metastases (p=0.008) and treatment (p<0.001). Conclusion: The median survival of NPC patients is significantly longer for age ${\leq}50$ years, no cranial nerve involvement, and early stage and is dependent on treatment modalities.

Comparing Role of Two Chemotherapy Regimens, CMF and Anthracycline-Based, on Breast Cancer Survival in the Eastern Mediterranean Region and Asia by Multivariate Mixed Effects Models: a Meta-Analysis

  • Ghanbari, Saeed;Ayatollahi, Seyyed Mohammad Taghi;Zare, Najaf
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.14
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    • pp.5655-5661
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    • 2015
  • Purpose: To assess the role of two adjuvant chemotherapy regimens, anthracycline-based and CMF on disease free survival and overall survival breast cancer patients by meta-analysis approach in Eastern Mediterranean and Asian countries to determine which is more effective and evaluate the appropriateness and efficiency of two different proposed statistical models. Materials and Methods: Survival curves were digitized and the survival proportions and times were extracted and modeled to appropriate covariates by two multivariate mixed effects models. Studies which reported disease free survival and overall survival curves for anthracycline-based or CMF as adjuvant chemotherapy that were published in English in the Eastern Mediterranean region and Asia were included in this systematic review. The two transformations of survival probabilities (Ln (-Ln(S)) and Ln(S/ (1-S))) as dependent variables were modeled by a multivariate mixed model to same covariates in order to have precise estimations with high power and appropriate interpretation of covariate effects. The analysis was carried out with SAS Proc MIXED and STATA software. Results: A total of 32 studies from the published literature were analysed, covering 4,092 patients who received anthracycline-based and 2,501 treated with CMF for the disease free survival and in order to analyze the overall survival, 13 studies reported the overall survival curves in which 2,050 cases were treated with anthracycline-based and 1,282 with CMF regimens. Conclusions: The findings illustrated that the model with dependent variable Ln (-Ln(S)) had more precise estimations of the covariate effects and showed significant difference between the effects of two adjuvant chemotherapy regimens. Anthracycline-based treatment gave better disease free survival and overall survival. As an IPD meta-analysis in the Italy the results of Angelo et al in 2011 also confirmed that anthracycline-based regimens were more effective for survival of breast cancer patients. The findings of Zare et al 2012 on disease free survival curves in Asia also provided similar evidence.

Survival in Fry and Juvenile Stages of Masu salmon Oncorhynchus masou : Estimates of Heritabilities and Correlations

  • Choe, Mi-Kyung
    • Journal of Aquaculture
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    • v.12 no.3
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    • pp.185-191
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    • 1999
  • A genetic analysis for survival in fry and juvenile stages of masu salmon was described. Data from two year-classes of masu salmon were analyzed to estimate the heritability for survival during the fresh water-rearing period. The overall survival for each year-class during 8 months of freshwater rearing were 17.8 and 11.6%, respectively. Whirling disease virus (WDV) was the main cause of death in all year-classes. Survival data obtained for offspring of 42 sires and 60 dams of masu salmon (two year classes of data) was analyzed. Average survival rates in the observation period ranged 2-87% for 1994; 0-98% for 1995, repectively. In both year-classes, heritabilities for survival derived from the sire components of variance were low(0.13-0.18), except one. Heritabilities derived from the dam components of variance ranged 0.14-0.61, including non-additive genetic and /or common enviromental effects. Correlations between survival in two long-term periods were all positive and medium to high in magnitude(0.345-0.918). Correlations between survival in non-succeeding periods were, in general, low and insignificant. Correlation between long-term survival and growth rate was found in masu salmon. The corresponding correlation in masu salmon was not significantly different from zero. Correlations between sire survival and body weight, length and condition factor of slaughter were not significant, but varied.

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Review of statistical methods for survival analysis using genomic data

  • Lee, Seungyeoun;Lim, Heeju
    • Genomics & Informatics
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    • v.17 no.4
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    • pp.41.1-41.12
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    • 2019
  • Survival analysis mainly deals with the time to event, including death, onset of disease, and bankruptcy. The common characteristic of survival analysis is that it contains "censored" data, in which the time to event cannot be completely observed, but instead represents the lower bound of the time to event. Only the occurrence of either time to event or censoring time is observed. Many traditional statistical methods have been effectively used for analyzing survival data with censored observations. However, with the development of high-throughput technologies for producing "omics" data, more advanced statistical methods, such as regularization, should be required to construct the predictive survival model with high-dimensional genomic data. Furthermore, machine learning approaches have been adapted for survival analysis, to fit nonlinear and complex interaction effects between predictors, and achieve more accurate prediction of individual survival probability. Presently, since most clinicians and medical researchers can easily assess statistical programs for analyzing survival data, a review article is helpful for understanding statistical methods used in survival analysis. We review traditional survival methods and regularization methods, with various penalty functions, for the analysis of high-dimensional genomics, and describe machine learning techniques that have been adapted to survival analysis.

Estimating the Five-Year Survival of Cervical Cancer Patients Treated in Hospital Universiti Sains Malaysia

  • Razak, Nuradhiathy Abd;Khattak, M.N.;Zubairi, Yong Zulina;Naing, Nyi Nyi;Zaki, Nik Mohamed
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.2
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    • pp.825-828
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    • 2013
  • Objective: The objective of this study was to determine the five-year survival among patients with cervical cancer treated in Hospital Universiti Sains Malaysia. Methods: One hundred and twenty cervical cancer patients diagnosed between $1^{st}$ July 1995 and $30^{th}$ June 2007 were identified. Data were obtained from medical records. The survival probability was determined using the Kaplan-Meier method and the log-rank test was applied to compare the survival distribution between groups. Results: The overall five-year survival was 39.7% [95%CI (Confidence Interval): 30.7, 51.3] with a median survival time of 40.8 (95%CI: 34.0, 62.0) months. The log-rank test showed that there were survival differences between the groups for the following variables: stage at diagnosis (p=0.005); and primary treatment (p=0.0242). Patients who were diagnosed at the latest stage (III-IV) were found to have the lowest survival, 18.4% (95%CI: 6.75, 50.1), compared to stage I and II where the five-year survival was 54.7% (95%CI: 38.7, 77.2) and 40.8% (95%CI: 27.7, 60.3), respectively. The five-year survival was higher in patients who received surgery [52.6% (95%CI: 37.5, 73.6)] as a primary treatment compared to the non-surgical group [33.3% (95%CI: 22.9, 48.4)]. Conclusion: The five-year survival of cervical cancer patients in this study was low. The survival of those diagnosed at an advanced stage was low compared to early stages. In addition, those who underwent surgery had higher survival than those who had no surgery for primary treatment.

Discount Survival Models

  • Shim, Joo-Y.;Sohn, Joong-K.
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.2
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    • pp.227-234
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    • 1996
  • The discount survival model is proposed for the application of the Cox model on the analysis of survival data with time-varying effects of covariates. Algorithms for the recursive estimation of the parameter vector and the retrospective estimation of the survival function are suggested. Also the algorithm of forecasting of the survival function of individuals of specific covariates in the next time interval based on the information gathered until the end of a certain time interval is suggested.

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Multiprocess Discount Survival Models With Survival Times

  • Shim, Joo-Yong
    • Journal of the Korean Statistical Society
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    • v.26 no.2
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    • pp.277-288
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    • 1997
  • For the analysis of survival data including covariates whose effects vary in time, the multiprocess discount survival model is proposed. The parameter vector modeling the time-varying effects of covariates is to vary between time intervals and its evolution between time intervals depends on the perturbation of the next time interval. The recursive estimation of the parameter vector can be obtained at the end of each time interval. The retrospective estimation of the survival function and the forecasting of the survival function of individuals of the specific covariates also can be obtained based on the information gathered until the end of the time interval.

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Comparison between Overall, Cause-specific, and Relative Survival Rates Based on Data from a Population-based Cancer Registry

  • Utada, Mai;Ohno, Yuko;Shimizu, Sachiko;Hori, Megumi;Soda, Midori
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.11
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    • pp.5681-5685
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    • 2012
  • Three kinds of survival rates are generally used depending on the purpose of the investigation: overall, cause-specific, and relative. The differences among these 3 survival rates are derived from their respective formulas; however, reports based on actual cancer registry data are few because of incomplete information and short follow-up duration recorded on cancer registration. The aim of this study was to numerically and visually compare these 3 survival rates on the basis of data from the Nagasaki Prefecture Cancer Registry. Subjects were patients diagnosed with cancer and registered in the registry between 1999 and 2003. We calculated the proportion of cause of death and 5-year survival rates. For lung, liver, or advanced stage cancers, the proportions of cancer-related death were high and the differences in survival rates were small. For prostate or early stage cancers, the proportions of death from other causes were high and the differences in survival rates were large. We concluded that the differences among the 3 survival rates increased when the proportion of death from other causes increased.

Performance Status and Quality Life of Patients with Hematopoietic Stem Cell Transplantation According to Period of Survival (조혈모세포이식 후 생존기간에 따른 수행능력과 삶의 질)

  • Woo, Hyae-Deok;Park, Jeong-Sook
    • Asian Oncology Nursing
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    • v.12 no.2
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    • pp.132-138
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    • 2012
  • Purpose: The purpose of this study was to identify the performance status and quality of life (QOL) of patients after hematopoietic stem cell transplantation (HSCT) according to period of survival. Methods: Participants consists of 83 HSCT patients who were being treated regularly at out-patient clinic in two general hospitals in D city. Data were collected using questionnaires that were modified by Functional Assessment of Cancer Therapy-Bone Marrow Transplabtation (FACT-BMT) scale and Eastern Cooperative Oncology Group (ECOG). Results: The unrelated HSCT group's survival period was significantly worse than related HSCT group and autologous HSCT group. Performance status of the group with more than 3 years survival was significantly higher than that of the group with less than a year survival. The mean score of total QOL of HSCT patients was 2.69 out of 4. Total QOL was not significantly different among period of survival less than 1 year, 1-3 years, and more than 3 years. But BMT QOL was shown that the group with more than 3 years survival was higher than the groups with less than a year survival. Conclusion: Performance status and BMT QOL of the group with less than 1 year survival was significantly lowered than the groups with more than 3 years survival.