Survival studies mainly deal with distribution of time to event. Often in such studies researchers are interested in comparing several treatment or prognostic groups. At the time of analysis, there is an unmeasured ch...Survival studies mainly deal with distribution of time to event. Often in such studies researchers are interested in comparing several treatment or prognostic groups. At the time of analysis, there is an unmeasured chance of making type I error, or finding a falsely significant difference between any two groups. The chance of making type I error is increased, if multiple groups are compared simultaneously. In this paper, survival analysis with Bonferroni correction is explained in easy way to cope up with this issue. The DLHS-3 data are taken to explain this methodology in the context of neonatal survival. Kaplan-meier plot with three survival comparison test is used to elaborate the application of Bonferroni correction.展开更多
To investigate the relationships between clinical findings and symptoms and the survival of patients with Yokkaichi Asthma, in relation to predisposing sulfur dioxide (SO2) exposure, we examined records of 1836 patien...To investigate the relationships between clinical findings and symptoms and the survival of patients with Yokkaichi Asthma, in relation to predisposing sulfur dioxide (SO2) exposure, we examined records of 1836 patients registered in the city of Yokkaichi during 1973-1988 by “Pollution-Related Health Damage Compensation Law.” Complete records were obtained from 735 patients (352 males and 383 females) until December 31, 2007, and were used for the analysis. Ambient SO2 concentrations in the Yokkaichi area were obtained from the Environmental Numeric Database of the National Institute for Environmental Science, Japan. It was found that severity of clinical symptoms and decreased pulmonary function were significantly correlated with predisposing SO2 exposure. A Cox proportional hazards analysis revealed that among all patients (COPD and asthma), age, forced expiratory volume 1.0 (sec) % and smoking affected mortality for both males and females. Significant associations between mortality, vital capacity (percent predicted) and cough and sputum were observed in males. Thus, the survival of patients with Yokkaichi Asthma was affected by severity of clinical symptoms and decreased pulmonary function, which were related to predisposing SO2 exposure. It appeared that the effects of clinical changes were greater in males than in females.展开更多
Lung cancer is one of the leading causes of death worldwide, accounting for an estimated 2.1 million cases in 2018. To analyze the risk factors behind the lung cancer survival, this paper employs two main models: Kapl...Lung cancer is one of the leading causes of death worldwide, accounting for an estimated 2.1 million cases in 2018. To analyze the risk factors behind the lung cancer survival, this paper employs two main models: Kaplan-Meier estimator and Cox proportional hazard model [1]. Also, log-rank test and wald test are utilized to test whether a correlation exists or not, which is discussed in detail in later parts of the paper. The aim is to find out the most influential factors for the survival probability of lung cancer patients. To summarize the results, stage of cancer is always a significant factor for lung cancer survival, and time has to be taken into account when analyzing the survival rate of patients in our data sample, which is from TCGA. Future study on lung cancer is also required to make improvement for the treatment of lung cancer, as our data sample might not represent the overall condition of patients diagnosed with lung cancer;also, more appropriate and advanced models should be employed in order to reflect factors that can affect survival rate of patients with lung cancer in detail.展开更多
Effects of many medical procedures appear after a time lag, when a significant change occurs in subjects’ failure rate. This paper focuses on the detection and estimation of such changes which is important for the ev...Effects of many medical procedures appear after a time lag, when a significant change occurs in subjects’ failure rate. This paper focuses on the detection and estimation of such changes which is important for the evaluation and comparison of treatments and prediction of their effects. Unlike the classical change-point model, measurements may still be identically distributed, and the change point is a parameter of their common survival function. Some of the classical change-point detection techniques can still be used but the results are different. Contrary to the classical model, the maximum likelihood estimator of a change point appears consistent, even in presence of nuisance parameters. However, a more efficient procedure can be derived from Kaplan-Meier estimation of the survival function followed by the least-squares estimation of the change point. Strong consistency of these estimation schemes is proved. The finite-sample properties are examined by a Monte Carlo study. Proposed methods are applied to a recent clinical trial of the treatment program for strong drug dependence.展开更多
This paper worked on a sample of 6791 logistics establishments registered in Chengdu, China over the period 1984-2016 to understand the survival status of </span><span style="font-family:Verdana;"&g...This paper worked on a sample of 6791 logistics establishments registered in Chengdu, China over the period 1984-2016 to understand the survival status of </span><span style="font-family:Verdana;">logistics service providers (LSPs) by non-parametric Kaplan-Meier estimation, together with Cox proportional hazard regression model, to identify factors affecting the failure of LSPs. In particular, it studies the interaction effect between LSPs’ size and entry timing and location. The empirical results show that: 1) Regarding the survival time, 1365 of the 6791 sample LSPs exited from the market by 2017. The exit rate is 20.1%, and the average life of the 6791 LSPs is about 6 years. 2) The survival of LSPs depends on their typology, ownership structure. And there is no significant difference in the probability of survival for both independent LSPs and logistics branches after controlling the effects of other variables. 3) Location and entry timing also play an important role in the survival of small-scale LSPs, but these factors cannot explain large-scale LSPs’ failure.展开更多
The analysis of survival data is a major focus of statistics. Interval censored data reflect uncertainty as to the exact times the units failed within an interval. This type of data frequently comes from tests or situ...The analysis of survival data is a major focus of statistics. Interval censored data reflect uncertainty as to the exact times the units failed within an interval. This type of data frequently comes from tests or situations where the objects of interest are not constantly monitored. Thus events are known only to have occurred between the two observation periods. Interval censoring has become increasingly common in the areas that produce failure time data. This paper explores the statistical analysis of interval-censored failure time data with applications. Three different data sets, namely Breast Cancer, Hemophilia, and AIDS data were used to illustrate the methods during this study. Both parametric and nonparametric methods of analysis are carried out in this study. Theory and methodology of fitted models for the interval-censored data are described. Fitting of parametric and non-parametric models to three real data sets are considered. Results derived from different methods are presented and also compared.展开更多
In cancer survival analysis, it is very frequently to estimate the confidence intervals for survival probabilities.But this calculation is not commonly involve in most popular computer packages, or only one methods of...In cancer survival analysis, it is very frequently to estimate the confidence intervals for survival probabilities.But this calculation is not commonly involve in most popular computer packages, or only one methods of estimation in the packages. In the present Paper, we will describe a microcomputer Program for estimating the confidence intervals of survival probabilities, when the survival functions are estimated using Kaplan-Meier product-limit or life-table method. There are five methods of estimation in the program (SPCI), which are the classical(based on Greenwood's formula of variance of S(ti), Rothman-Wilson, arcsin transformation, log(-Iog) transformation, Iogit transformation methods. Two example analysis are given for testing the performances of the program running.展开更多
Cox Proportional Hazard model is a popular statistical technique for exploring the relationship between the survival time of neonates and several explanatory variables. It provides an estimate of the study variables’...Cox Proportional Hazard model is a popular statistical technique for exploring the relationship between the survival time of neonates and several explanatory variables. It provides an estimate of the study variables’ effect on survival after adjustment for other explanatory variables, and allows us to estimate the hazard (or risk) of death of newborn in NICU of hospitals in River Nile State-Sudan for the period (2018-2020). Study Data represented (neonate gender, mode of delivery, birth type, neonate weight, resident type, gestational age, and survival time). Kaplan-Meier method is used to estimate survival and hazard function for survival times of newborns that have not completed their first month. Of 700 neonates in the study area, 25% of them died during 2018-2020. Variables of interest that had a significant effect on neonatal death by Cox Proportional Hazard Model analysis were neonate weight, resident type, and gestational age. In Cox Proportional Hazard Model analysis all the variables of interest had an effect on neonatal death, but the variables with a significant effect included, weight of neonate, resident type and gestational age.展开更多
This paper concerns the Log-rank test for comparing survival curves of neonatal mortality characteristic groups in River Nile State, Sudan. In this paper, log-rank test is used to compare two or more survival curves f...This paper concerns the Log-rank test for comparing survival curves of neonatal mortality characteristic groups in River Nile State, Sudan. In this paper, log-rank test is used to compare two or more survival curves for the characteristics of newborn associated with newborn death after using Kaplan-Meier methods to estimate and graph survival curves for the variable of interest as (sex of newborn, weight of newborn, gestational age, mode of delivery and resident type), at the hospital of River Nile state—Sudan, with a sample size 700 of newborn in which the admission to the Neonatal Intensive Care Unit (NICU) of those hospitals during the period 2018-2020. In term of risk of death for newborn we found that 25% of sample study for newborns who were born in River Nile State-Sudan died. In addition, we conclude that after the log-rank statistics and Kaplan-Meier methods were applied, gender does not affect the newborn’s risk of survival, while the risk of survival increases when the birth weight is greater than 4.35 kg and the gestational age is greater than 42 weeks. There is no difference in the probability of survival for newborns whether the delivery is normal or cesarean. However, newborns are significantly more likely to survive in urban areas than in rural areas.展开更多
BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 ...BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 and 385 patients,respectively),but their results are discordant.AIM To synthetize the available evidence on the effectiveness of lutetium in pre-treated metastatic castration-resistant prostate cancer;and to test the application of a new artificial intelligence technique that synthetizes effectiveness based on reconstructed patient-level data.METHODS We employed a new artificial intelligence method(shiny method)to pool the survival data of these two trials and evaluate to what extent the lutetium cohorts differed from one another.The shiny technique employs an original reconstruction of individual patient data from the Kaplan-Meier curves.The progression-free survival graphs of the two lutetium cohorts were analyzed and compared.RESULTS The hazard ratio estimated was in favor of the vision trial;the difference was statistically significant(P<0.001).These results indicate that further studies on lutetium are needed because the survival data of the two trials published thus far are conflicting.CONCLUSION Our study confirms the feasibility of reconstructing patient-level data from survival graphs in order to generate a survival statistics.展开更多
BACKGROUND Recipient functional status prior to transplantation has been found to impact post-transplant outcomes in heart,liver and kidney transplants.However,information on how functional status,before and after tra...BACKGROUND Recipient functional status prior to transplantation has been found to impact post-transplant outcomes in heart,liver and kidney transplants.However,information on how functional status,before and after transplant impacts post-transplant survival outcomes is lacking.AIM To investigate the impact of recipient functional status on short and long term intestinal transplant outcomes in United States adults.METHODS We conducted a retrospective cohort study on 1254 adults who underwent first-time intestinal transplantation from 2005 to 2022.The primary outcome was mortality.Using the Karnofsky Performance Status,functional impairment was categorized as severe,moderate and normal.Analyses were conducted using Kaplan-Meier curves and multivariable Cox regression.RESULTS The median age was 41 years,majority(53.4%)were women.Severe impairment was present in 28.3%of recipients.The median survival time was 906.6 days.The median survival time was 1331 and 560 days for patients with normal and severe functional impairment respectively.Recipients with severe impairment had a 56%higher risk of mortality at one year[Hazard ratio(HR)=1.56;95%CI:1.23–1.98;P<0.001]and 58%at five years(HR=1.58;95%CI:1.24–2.00;P<0.001)compared to patients with no functional impairment.Recipients with worse functional status after transplant also had poor survival outcomes.CONCLUSION Pre-and post-transplant recipient functional status is an important prognostic indicator for short-and long-term intestinal transplant outcomes.展开更多
Six plots were investigated and field data were obtained with the contiguous grid quadrate method in a natural Populus euphratica forest in the upper reaches of the Tarim river.We developed a static life table and a s...Six plots were investigated and field data were obtained with the contiguous grid quadrate method in a natural Populus euphratica forest in the upper reaches of the Tarim river.We developed a static life table and a survival function of Populus pruinosa population based on the population life table and a theory of survival analysis.Survivorship curves,and the mortality rate were determined,and population dynamics were analyzed by using the spectral analysis.The results showed that:1)Survival numbers of P.pruinosa populations were decreased with the increasing of age,and the expecting life of individuals with DBH larger than 40 cm declined obviously.2)The Survivorship curve of the populations was Deevey Ⅲ.Four survival functions showed that the P.pruinosa population declined in young age and stabilized in old age.3)There were two peaks of mortality rate existed in the lifespan:respectively occarred at the first and 11th age class periods.Seedling shortage was the restricting factor of development.4) The spectral analysis of the populations showed that there was a marked periodic fluctuation in the process of natural regeneration.5)The higher mortality rate of P.pruinosa seedlings might be integrated by the interplay of biological characteristics of P.pruinosa and deteriorating habitat(groundwater level decreasing).展开更多
文摘Survival studies mainly deal with distribution of time to event. Often in such studies researchers are interested in comparing several treatment or prognostic groups. At the time of analysis, there is an unmeasured chance of making type I error, or finding a falsely significant difference between any two groups. The chance of making type I error is increased, if multiple groups are compared simultaneously. In this paper, survival analysis with Bonferroni correction is explained in easy way to cope up with this issue. The DLHS-3 data are taken to explain this methodology in the context of neonatal survival. Kaplan-meier plot with three survival comparison test is used to elaborate the application of Bonferroni correction.
文摘To investigate the relationships between clinical findings and symptoms and the survival of patients with Yokkaichi Asthma, in relation to predisposing sulfur dioxide (SO2) exposure, we examined records of 1836 patients registered in the city of Yokkaichi during 1973-1988 by “Pollution-Related Health Damage Compensation Law.” Complete records were obtained from 735 patients (352 males and 383 females) until December 31, 2007, and were used for the analysis. Ambient SO2 concentrations in the Yokkaichi area were obtained from the Environmental Numeric Database of the National Institute for Environmental Science, Japan. It was found that severity of clinical symptoms and decreased pulmonary function were significantly correlated with predisposing SO2 exposure. A Cox proportional hazards analysis revealed that among all patients (COPD and asthma), age, forced expiratory volume 1.0 (sec) % and smoking affected mortality for both males and females. Significant associations between mortality, vital capacity (percent predicted) and cough and sputum were observed in males. Thus, the survival of patients with Yokkaichi Asthma was affected by severity of clinical symptoms and decreased pulmonary function, which were related to predisposing SO2 exposure. It appeared that the effects of clinical changes were greater in males than in females.
文摘Lung cancer is one of the leading causes of death worldwide, accounting for an estimated 2.1 million cases in 2018. To analyze the risk factors behind the lung cancer survival, this paper employs two main models: Kaplan-Meier estimator and Cox proportional hazard model [1]. Also, log-rank test and wald test are utilized to test whether a correlation exists or not, which is discussed in detail in later parts of the paper. The aim is to find out the most influential factors for the survival probability of lung cancer patients. To summarize the results, stage of cancer is always a significant factor for lung cancer survival, and time has to be taken into account when analyzing the survival rate of patients in our data sample, which is from TCGA. Future study on lung cancer is also required to make improvement for the treatment of lung cancer, as our data sample might not represent the overall condition of patients diagnosed with lung cancer;also, more appropriate and advanced models should be employed in order to reflect factors that can affect survival rate of patients with lung cancer in detail.
文摘Effects of many medical procedures appear after a time lag, when a significant change occurs in subjects’ failure rate. This paper focuses on the detection and estimation of such changes which is important for the evaluation and comparison of treatments and prediction of their effects. Unlike the classical change-point model, measurements may still be identically distributed, and the change point is a parameter of their common survival function. Some of the classical change-point detection techniques can still be used but the results are different. Contrary to the classical model, the maximum likelihood estimator of a change point appears consistent, even in presence of nuisance parameters. However, a more efficient procedure can be derived from Kaplan-Meier estimation of the survival function followed by the least-squares estimation of the change point. Strong consistency of these estimation schemes is proved. The finite-sample properties are examined by a Monte Carlo study. Proposed methods are applied to a recent clinical trial of the treatment program for strong drug dependence.
文摘This paper worked on a sample of 6791 logistics establishments registered in Chengdu, China over the period 1984-2016 to understand the survival status of </span><span style="font-family:Verdana;">logistics service providers (LSPs) by non-parametric Kaplan-Meier estimation, together with Cox proportional hazard regression model, to identify factors affecting the failure of LSPs. In particular, it studies the interaction effect between LSPs’ size and entry timing and location. The empirical results show that: 1) Regarding the survival time, 1365 of the 6791 sample LSPs exited from the market by 2017. The exit rate is 20.1%, and the average life of the 6791 LSPs is about 6 years. 2) The survival of LSPs depends on their typology, ownership structure. And there is no significant difference in the probability of survival for both independent LSPs and logistics branches after controlling the effects of other variables. 3) Location and entry timing also play an important role in the survival of small-scale LSPs, but these factors cannot explain large-scale LSPs’ failure.
文摘The analysis of survival data is a major focus of statistics. Interval censored data reflect uncertainty as to the exact times the units failed within an interval. This type of data frequently comes from tests or situations where the objects of interest are not constantly monitored. Thus events are known only to have occurred between the two observation periods. Interval censoring has become increasingly common in the areas that produce failure time data. This paper explores the statistical analysis of interval-censored failure time data with applications. Three different data sets, namely Breast Cancer, Hemophilia, and AIDS data were used to illustrate the methods during this study. Both parametric and nonparametric methods of analysis are carried out in this study. Theory and methodology of fitted models for the interval-censored data are described. Fitting of parametric and non-parametric models to three real data sets are considered. Results derived from different methods are presented and also compared.
文摘In cancer survival analysis, it is very frequently to estimate the confidence intervals for survival probabilities.But this calculation is not commonly involve in most popular computer packages, or only one methods of estimation in the packages. In the present Paper, we will describe a microcomputer Program for estimating the confidence intervals of survival probabilities, when the survival functions are estimated using Kaplan-Meier product-limit or life-table method. There are five methods of estimation in the program (SPCI), which are the classical(based on Greenwood's formula of variance of S(ti), Rothman-Wilson, arcsin transformation, log(-Iog) transformation, Iogit transformation methods. Two example analysis are given for testing the performances of the program running.
文摘Cox Proportional Hazard model is a popular statistical technique for exploring the relationship between the survival time of neonates and several explanatory variables. It provides an estimate of the study variables’ effect on survival after adjustment for other explanatory variables, and allows us to estimate the hazard (or risk) of death of newborn in NICU of hospitals in River Nile State-Sudan for the period (2018-2020). Study Data represented (neonate gender, mode of delivery, birth type, neonate weight, resident type, gestational age, and survival time). Kaplan-Meier method is used to estimate survival and hazard function for survival times of newborns that have not completed their first month. Of 700 neonates in the study area, 25% of them died during 2018-2020. Variables of interest that had a significant effect on neonatal death by Cox Proportional Hazard Model analysis were neonate weight, resident type, and gestational age. In Cox Proportional Hazard Model analysis all the variables of interest had an effect on neonatal death, but the variables with a significant effect included, weight of neonate, resident type and gestational age.
文摘This paper concerns the Log-rank test for comparing survival curves of neonatal mortality characteristic groups in River Nile State, Sudan. In this paper, log-rank test is used to compare two or more survival curves for the characteristics of newborn associated with newborn death after using Kaplan-Meier methods to estimate and graph survival curves for the variable of interest as (sex of newborn, weight of newborn, gestational age, mode of delivery and resident type), at the hospital of River Nile state—Sudan, with a sample size 700 of newborn in which the admission to the Neonatal Intensive Care Unit (NICU) of those hospitals during the period 2018-2020. In term of risk of death for newborn we found that 25% of sample study for newborns who were born in River Nile State-Sudan died. In addition, we conclude that after the log-rank statistics and Kaplan-Meier methods were applied, gender does not affect the newborn’s risk of survival, while the risk of survival increases when the birth weight is greater than 4.35 kg and the gestational age is greater than 42 weeks. There is no difference in the probability of survival for newborns whether the delivery is normal or cesarean. However, newborns are significantly more likely to survive in urban areas than in rural areas.
文摘BACKGROUND Lutetium has been shown to be an important potential innovation in pre-treated metastatic castration-resistant prostate cancer.Two clinical trials have evaluated lutetium thus far(therap and vision with 99 and 385 patients,respectively),but their results are discordant.AIM To synthetize the available evidence on the effectiveness of lutetium in pre-treated metastatic castration-resistant prostate cancer;and to test the application of a new artificial intelligence technique that synthetizes effectiveness based on reconstructed patient-level data.METHODS We employed a new artificial intelligence method(shiny method)to pool the survival data of these two trials and evaluate to what extent the lutetium cohorts differed from one another.The shiny technique employs an original reconstruction of individual patient data from the Kaplan-Meier curves.The progression-free survival graphs of the two lutetium cohorts were analyzed and compared.RESULTS The hazard ratio estimated was in favor of the vision trial;the difference was statistically significant(P<0.001).These results indicate that further studies on lutetium are needed because the survival data of the two trials published thus far are conflicting.CONCLUSION Our study confirms the feasibility of reconstructing patient-level data from survival graphs in order to generate a survival statistics.
文摘BACKGROUND Recipient functional status prior to transplantation has been found to impact post-transplant outcomes in heart,liver and kidney transplants.However,information on how functional status,before and after transplant impacts post-transplant survival outcomes is lacking.AIM To investigate the impact of recipient functional status on short and long term intestinal transplant outcomes in United States adults.METHODS We conducted a retrospective cohort study on 1254 adults who underwent first-time intestinal transplantation from 2005 to 2022.The primary outcome was mortality.Using the Karnofsky Performance Status,functional impairment was categorized as severe,moderate and normal.Analyses were conducted using Kaplan-Meier curves and multivariable Cox regression.RESULTS The median age was 41 years,majority(53.4%)were women.Severe impairment was present in 28.3%of recipients.The median survival time was 906.6 days.The median survival time was 1331 and 560 days for patients with normal and severe functional impairment respectively.Recipients with severe impairment had a 56%higher risk of mortality at one year[Hazard ratio(HR)=1.56;95%CI:1.23–1.98;P<0.001]and 58%at five years(HR=1.58;95%CI:1.24–2.00;P<0.001)compared to patients with no functional impairment.Recipients with worse functional status after transplant also had poor survival outcomes.CONCLUSION Pre-and post-transplant recipient functional status is an important prognostic indicator for short-and long-term intestinal transplant outcomes.
文摘Six plots were investigated and field data were obtained with the contiguous grid quadrate method in a natural Populus euphratica forest in the upper reaches of the Tarim river.We developed a static life table and a survival function of Populus pruinosa population based on the population life table and a theory of survival analysis.Survivorship curves,and the mortality rate were determined,and population dynamics were analyzed by using the spectral analysis.The results showed that:1)Survival numbers of P.pruinosa populations were decreased with the increasing of age,and the expecting life of individuals with DBH larger than 40 cm declined obviously.2)The Survivorship curve of the populations was Deevey Ⅲ.Four survival functions showed that the P.pruinosa population declined in young age and stabilized in old age.3)There were two peaks of mortality rate existed in the lifespan:respectively occarred at the first and 11th age class periods.Seedling shortage was the restricting factor of development.4) The spectral analysis of the populations showed that there was a marked periodic fluctuation in the process of natural regeneration.5)The higher mortality rate of P.pruinosa seedlings might be integrated by the interplay of biological characteristics of P.pruinosa and deteriorating habitat(groundwater level decreasing).