生存资料回归模型分析--Cox比例风险假设的拟合优度法

本文目的是介绍一些检验比例风险假设的方法。图示法是通过绘图然后由人工进行判断是否符合比例风险假设,因而具有一定的主观性。在图示法的基础上,本文介绍了从客观角度检验比例风险假设的一些常用方法,主要包括两类:一类是基于残差的检验;另一类则是构建协变量与时间的交互项并对其进行检验的方法。首先阐述了上述方法的原理,然后基于SAS软件并通过一个实例介绍上述方法的实现。     

生存资料回归模型分析——生存资料Cox比例风险回归模型分析

本文目的是介绍生存资料Cox比例风险回归模型分析的概念、作用及使用SAS软件实现计算的方法。首先介绍相关基本概念,包括"Cox比例风险回归模型简介""模型假定及其检验""参数解释"和"参数估计与假设检验";然后通过一个实例并基于SAS软件演示如何实施生存资料Cox比例风险回归模型分析,内容包括"产生SAS数据集""绘制生存曲线图""判断PH假定是否成立"和"算出参数估计值与假设检验结果"。结果表明:当生存资料满足PH假定时,Cox比例风险回归模型可用于生存资料影响因素分析、校正混杂因素后的组间比较以及对每个个体进行预后指数和生存率的预测。     

生存资料回归模型分析——生存资料参数回归模型分析SAS实现

本文目的是介绍生存资料参数回归模型的SAS实现,包括创建SAS数据集、依据图示法选择模型、拟合参数模型和似然比检验。利用SAS中的LIFEREG过程绘制生存函数关于生存时间的关系图,拟合对应的参数分布回归模型,通过拟合优度检验选择最优的参数回归模型,最后对相关结果进行解释。     

生存资料回归模型分析——生存资料及其统计分析方法概述

本文目的是全面介绍生存资料的特点及其常用统计分析方法。生存资料具有以下四个特点:①同时具有生存结局和生存时间;②生存时间可能含有删失数据或截尾数据;③生存时间的分布通常不服从正态分布,常呈指数分布、Weibull分布、对数正态分布;④影响生存时间的因素较复杂且不易控制。生存资料统计分析方法涉及统计描述、差异性分析和回归分析三大类,其中,统计描述主要有Kaplan-Meier(卡普兰-迈耶)估计法和Life table(寿命表)估计法;差异性分析主要有对数秩检验(log-rank test)和威尔考克森检验(Wilcoxon test);而回归分析主要有Cox比例和非比例风险回归模型、参数回归模型。在对生存资料进行统计分析时,需要合理选择统计分析方法,方可全面而又深入地揭示生存资料的内在变化规律。     

如何正确运用χ2检验——横断面设计四格表资料的χ2检验

本文目的是介绍横断面设计四格表资料的χ²检验及SAS和R软件实现。具体介绍了3种方法,即“Pearson?sχ²检验”“校正的Pearson?sχ²检验”和“似然比χ²检验”。内容涉及前述提及的3种统计分析方法的检验假设、计算原理与公式、前提条件、SAS与R软件的实现、结果解释以及结论陈述。     

如何正确运用χ2检验——生存资料的似然比检验和六种非参数检验与SAS实现

本文目的是介绍生存资料的似然比检验与六种非参数检验以及SAS实现。基于生存资料服从指数分布的假定，推导出似然比检验方法；而六种非参数检验方法的主要区别在于它们具有不同的权函数。在未分层和分层的条件下，都可以运用前述提及的七种生存资料假设检验方法，它们的共同点是其检验统计量都服从χ²分布。本文通过两个实例，并借助SAS软件，实现两组或多组生存资料的各种假设检验，对输出结果作出解释，并给出统计结论和专业结论。     

如何正确运用χ2检验——生存资料的三种特殊检验与SAS实现

本文目的是介绍生存资料的三种特殊检验以及SAS实现。具体地说,就是生存资料的多重比较、趋势检验和协变量检验。在多重比较中,涉及“两两比较”和“与对照组比较”两种情形;在趋势检验中,涉及“对数秩检验法”和“威尔科克森检验法”两种算法;在协变量检验中,涉及“单协变量检验法”和“逐次增加一个协变量的多协变量检验法”。本文结合一个实例并借助SAS软件实现前述提及的三种特殊检验,对输出结果作出解释,并给出统计结论和专业结论。     

如何正确运用Z检验——定性资料一致性Z检验及SAS实现

本文目的是介绍定性资料一致性Z检验的原理、方法和SAS实现。文中涉及两个方面的内容，包括介绍定性资料一致性Z检验的原理和方法以及基于SAS软件实现定性资料一致性Z检验。文中给出了SAS输出结果并对其进行解释，再分别得出统计学结论和专业结论。     

如何正确运用χ~2检验——人-时间资料独立性检验与SAS实现

本文目的是介绍"未分层人-时间资料"和"分层人-时间资料"的独立性检验与SAS实现方法。在"人-时间资料"中,处理因素各水平组中的样本含量都以"人-年数"来表达。进而,需采用"发病密度"取代通常定性资料分析中的"发病率"。本文详细介绍"未分层人-时间资料"和"分层人-时间资料"的"发病密度"比较的具体方法,并通过两个实例,展示使用SAS软件实现计算的全过程,包括SAS程序代码、SAS输出结果、结果解释和结论陈述。     

如何正确运用χ~2检验——人-时间资料率比分析与SAS实现

本文目的是介绍"分层人-时间资料"率比分析方法与SAS实现方法,具体内容包括以下四个方面:(1)分层人-时间资料中第i层率比的点估计和置信区间估计;(2)不同层间率比的齐性检验;(3)合并率比的点估计与置信区间估计;(4)分层人-时间资料中发病密度的线性趋势检验。通过两个实例,展示基于SAS软件实现前述四个分析内容的统计计算过程,包括提供SAS程序代码、对SAS输出结果进行解释,并给出统计结论和专业结论。     

Proportional Hazards Modeling of Saccadic Response Times During Reading

In this article we use proportional hazards models to examine how low‐level processes affect the probability of making a saccade over time, through the period of fixation, during reading. We apply the Cox proportional hazards model to investigate how launch distance (relative to word beginning), fixation location (relative to word center), and word frequency affect the hazard of a saccadic response. This model requires that covariates have a constant impact on the hazard over time, the assumption of proportional hazards. We show that this assumption is not supported. The impact of the covariates changes with the time passed since fixation onset. To account for the non‐proportional hazards we fit step functions of time, resulting in a model with time‐varying effects on the hazard. We evaluate the ability to predict the timing of saccades on held‐out fixation data. The model with time‐varying effects performs better in predicting the timing of saccades for fixations as short as 100 ms and as long as 500 ms, when compared both to a baseline model without covariates and a model which assumes constant covariate effects. This result suggests that the time‐varying effects model better recovers the time course of low‐level processes that influence the decision to move the eyes.     

Neutrophil-to-Lymphocyte Ratio Predicts in-Hospital Mortality in Intracerebral Hemorrhage

ObjectivesThe neutrophil-to-lymphocyte ratio is gaining popularity as a low-cost biomarker of inflammation and outcome prediction. Intracerebral hemorrhage has high mortality and disability, which strongly influences societal development. This study aimed to research whether the neutrophil-to-lymphocyte ratio can predict hospital mortality in patients with severe intracerebral hemorrhage.Materials and methodsIt was a retrospective analysis of prospectively collected data. The survival analysis and proportional hazards models analyzed clinical data from the Medical Information Mart for Intensive Care III database of patients with intracerebral hemorrhage.ResultsThe records of 1,000 patients were included in our study. Two hundred forty-seven individuals died in the hospital, while 753 survived to discharge. According to data analysis, the neutrophil-to-lymphocyte ratio of the death group (11.21±7.81) significantly exceeded the survival group (7.94±6.04). The univariate Cox regression revealed that the neutrophil-to-lymphocyte ratio is a potential predictor of in-hospital mortality (HR:1.044; 95% CI:1.029-1.059; p <0.001). Furthermore, the proportional hazards model demonstrated that the risk of in-hospital death increased 2.34-fold for each increase in neutrophil-to-lymphocyte ratio when other factors were held constant. Following the ROC analysis, the Kaplan-Meier based on the proportional hazards model showed that patients with a neutrophil-to-lymphocyte ratio >7.68 on the first day of hospitalization had a higher risk of death.ConclusionsIn patients with severe intracerebral hemorrhage, the neutrophil-to-lymphocyte ratio is a potential predictor of in-hospital mortality.     

Graphing survival curve estimates for time-dependent covariates

Graphical representation of statistical results is often used to assist readers in the interpretation of the findings. This is especially true for survival analysis where there is an interest in explaining the patterns of survival over time for specific covariates. For fixed categorical covariates, such as a group membership indicator, Kaplan-Meier estimates (1958) can be used to display the curves. For time-dependent covariates this method may not be adequate. Simon and Makuch (1984) proposed a technique that evaluates the covariate status of the individuals remaining at risk at each event time. The method takes into account the change in an individual's covariate status over time. The survival computations are the same as the Kaplan-Meier method, in that the conditional survival estimates are the function of the ratio of the number of events to the number at risk at each event time. The difference between the two methods is that the individuals at risk within each level defined by the covariate is not fixed at time 0 in the Simon and Makuch method as it is with the Kaplan-Meier method. Examples of how the two methods can differ for time dependent covariates in Cox proportional hazards regression analysis are presented.     

WHO Ⅲ级脑膜瘤的生存分析

目的探讨WHOⅢ级脑膜瘤患者的预后影响因素。方法收集14例(男性4例,女性10例)经手术及病理诊断的WHOⅢ级脑膜瘤患者的临床及随访资料。应用Kaplan-Meier法和Cox回归模型对其性别、年龄、肿瘤部位、KPS评分、肿瘤切除程度,手术后放疗等临床特征进行单因素和多因素生存分析。结果本组14例患者的平均存活时间为60个月,中位生存时间为77个月,3年生存率为59%,5年生存率为51%,8年生存率为38%。12例大体全切的患者中平均复发时间为60个月,中位复发时间为43个月,3年复发率为55%,5年复发率为37%。单因素分析发现:性别(P=0.009)和手术切除程度(P=0.03)对WHOⅢ级脑膜瘤患者的生存时间有影响。Cox多因素预后分析未发现对生存时间和复发时间有影响的因素。结论手术全切是延长WHOⅢ级脑膜瘤患者生存期的重要因素。     

Variation in Major Depressive Disorder Onset by Place of Origin Among U.S. Latinos

Using a nationally representative sample of 2514 U.S. Latinos, this study examined the extent to which major depressive disorder (MDD) onset differs by place of origin and the factors associated with it. The Kaplan-Meier method estimated the survival and hazard functions for MDD onset by place of origin, and Cox proportional hazards models identified its associative factors. Approximately 13% of the sample had experienced MDD in their lifetimes. Cuban respondents showed the highest survival function, while Puerto Ricans showed the lowest. With the entire sample, the smoothed hazard function showed that the risk of MDD onset peaked in the late 20s and early 80s. Puerto Rican respondents showed the highest risk of MDD during their 20s and 30s, whereas Cuban respondents showed a relatively stable pattern over time. The results from the Cox proportional hazards model indicated that age, sex, and marital status were significantly related to MDD onset (p < .05). In addition, the effect of U.S.-born status on MDD onset was greater among Mexican respondents than among Puerto Ricans. Findings from the present study demonstrate that different Latino subgroups experience different and unique patterns of MDD onset over time. Future research should account for the role of immigration status in examining MDD onset.     

Community Hospital-based Stroke Programs: North Carolina, Oregon, and New York. III. Factors influencing survival after stroke: proportional hazards analysis of 4219 patients

The possible effect of age, race, sex, consciousness upon admission, geographic location, and history of selected risk factors on the survival after stroke due to infarction or hemorrhage was determined using proportional hazards analysis (Cox regression). For each diagnostic category the most significant prognostic factor was consciousness upon admission. Increasing age, cardiac disease, or previous stroke also decreased the survival time of patients with infarctions. For patients with cerebral hemorrhage, no other variable was significant after control for consciousness level.     

Factors associated with mortality in patients with early-onset Alzheimer's disease: a five-year longitudinal study

To identify neuropsychiatric and somatic factors related to survival in early-onset Alzheimer's disease, we longitudinally studied 108 patients (35 male, 73 female) with early-onset Alzheimer's disease who were 46 to 64 years old at onset and 50 to 69 years old when diagnosed at our institution. A five-year follow-up, 30 patients had died. Pneumonia was the most common cause (73%), followed by malignancy (20%) and heart disease (7%). Kaplan-Meier survival curves showed a lower survival rate in patients with early-onset Alzheimer's disease than in age- and sex-matched life-table data in Japan. In Cox proportional hazards analysis, male gender, early disease onset, concurrent physical illness at time of diagnosis, and a low mini-mental state examination score increased the likelihood of death in patients with early-onset Alzheimer's disease. Our study confirmed that these patients have considerable excess mortality and a different pattern of cause of death than in the general population. Gender, age at onset, physical illness, and cognitive function strongly influenced survival. These factors may be predictors of mortality in patients with early-onset Alzheimer's disease that are useful in counseling patients and their families.