Regression analysis of mean quality-adjusted lifetime with censored data

In clinical trials of chronic diseases such as acquired immunodeficiency syndrome, cancer, or cardiovascular diseases, the concept of quality-adjusted lifetime (QAL) has received more and more attention. In this paper, we consider the problem of how the covariates affect the mean QAL when the data are subject to right censoring. We allow a very general form for the mean model as a function of covariates. Using the idea of inverse probability weighting, we first construct a simple weighted estimating equation for the parameters in our mean model. We then find the form of the most efficient estimating equation, which yields the most efficient estimator for the regression parameters. Since the most efficient estimator depends on the distribution of the health history processes, and thus cannot be estimated nonparametrically, we consider different approaches for improving the efficiency of the simple weighted estimating equation using observed data. The applicability of these methods is demonstrated by both simulation experiments and a data example from a breast cancer clinical trial study.     

髋关节骨性关节炎患者生存质量现状及其影响因素分析

目的：探讨髋关节骨性关节炎患者生存质量现状及其影响因素。方法：选择60 例髋关节骨性关节炎患者作为观察组,60 例 健康者作为对照组。采用SF-36 生存质量评价量表,比较观察组与对照组SF-36 量表各维度评分;分析影响患者生存质量的因素。 结果：①观察组SF-36 量表各维度评分均显著低于健康对照组,差异均具有统计学意义（P＜0.05）;②经Pearson 单因素分析, SF-36 量表综合得分在性别、职业、病程、治疗前景、内科慢性疾病数、10m 步行速度及K-L 分级方面的差异均具有统计学意义 （P＜0.05~0.01）;③经多元Logistic 回归分析,病程（beta=0.772,S.E.=0.689,Wald=34.027,P＜0.05,OR=1.99）、治疗前景（beta=0.778,S. E.=0.542,Wald=55.638,P＜0.05,OR=1.88）、内科慢性疾病数（beta=0.929,S.E.=0.301,Wald=12.382,P＜0.05,OR=1.72）、10m 步行速 度（beta=0.661,S.E.=0.381,Wald=19.929,P＜0.05,OR=1.69）及K-L 分级（beta=0.992,S.E.=0.526,Wald=28.371,P＜0.05,OR=2.31）为影 响髋关节骨性关节炎患者生存质量的危险因素。结论：髋关节骨性关节炎患者生存质量明显差于健康者,病程、治疗前景、内科慢 性疾病数、10m步行速度及K-L分级是影响患者生存质量的危险因素。     

Testing equality of survival functions of quality-adjusted lifetime

We present a method for comparing the survival functions of quality-adjusted lifetime from two treatments. This test statistic becomes the ordinary log-rank test when quality-adjusted lifetime is the same as the survival time. Simulation experiments are conducted to examine the behavior of our proposed test statistic under both null and alternative hypotheses. In addition, we apply our method to a breast cancer trial for comparing the distribution of quality-adjusted lifetime between two treatment regimes.     

Efficient estimation of the distribution of quality-adjusted survival time

Quality of life is an important aspect in evaluation of clinical trials of chronic diseases, such as cancer and AIDS. Quality-adjusted survival analysis is a method that combines both the quantity and quality of a patient's life into one single measure. In this paper, we discuss the efficiency of weighted estimators for the distribution of quality-adjusted survival time. Using the general representation theorem for missing data processes, we are able to derive an estimator that is more efficient than the one proposed in Zhao and Tsiatis (1997, Biometrika 84, 339-348). Simulation experiments are conducted to assess the small sample properties of this estimator and to compare it with the semiparametric efficiency bound. The value of this estimator is demonstrated from an application of the method to a data set obtained from a breast cancer clinical trial.     

术后疼痛对膝关节盘状半月板损伤患者膝关节功能、生活质量及心理状态的影响及其危险因素的Logistic回归分析

摘要 目的：探讨术后疼痛对膝关节盘状半月板损伤患者膝关节功能、生活质量及心理状态的影响及其危险因素的Logistic回归分析。方法：选取2019年5月～2022年1月福建医科大学附属第一医院收治的膝关节盘状半月板损伤患者120例,均行关节镜手术治疗,观察并评价所有患者手术疗效;根据术后6个月膝关节是否疼痛分为疼痛组（n=16）与无痛组（n=104）。比较两组术前及术后6个月Lysholm膝关节功能评分、健康调查简表（SF-36）评分、焦虑自评量表（SAS）和抑郁自评量表（SDS）评分。单因素及多因素Logistic回归分析术后疼痛的危险因素。结果：120例膝关节盘状半月板损伤患者术前、术后3个月、术后6个月Lysholm评分分别为（56.97±8.62）分、（78.09±10.53）分、（89.26±8.14）分,术后3个月、术后6个月Lysholm评分均显著高于术前（均P＜0.001）。临床疗效显示行关节镜手术后优良率为86.67%（104/120）。术后6个月两组Lysholm评分、SF-36评分均高于手术前,但疼痛组低于无痛组（P＜0.05）;术后6个月两组SAS评分、SDS评分均低于手术前,但疼痛组高于无痛组（P＜0.05）。单因素分析发现,年龄、BMI、撕裂类型、滑膜切除、术后冷敷、开始负重时间与术后痛疼有关（P＜0.05）;而性别、受教育程度、吸烟史、饮酒史、ASA分级、患侧、病程、损伤部位、手术方式与术后痛疼无关（P＞0.05）。多因素Logistic回归分析显示,年龄、BMI≥24 kg/m²、纵裂或其他撕裂、滑膜切除、开始负重时间＜4周及术后6个月SAS评分、SDS评分是术后疼痛的独立危险因素,而术后冷敷是术后疼痛的保护因素（P＜0.05）。结论：术后疼痛对膝关节盘状半月板损伤患者膝关节功能、生活质量及心理状态产生明显负面影响。年龄、BMI≥24 kg/m²、混合性撕裂、滑膜切除、开始负重时间＜4周以及术后6个月SAS评分、SDS评分是术后疼痛危险因素,而术后冷敷是其保护因素,临床可据此施以针对性防治措施。     

Cox回归模型在肝癌病人生存分析中应用的研究

生存时间是癌症患者和临床医师共同关心的焦点,也是临床癌症诊治工作的重要指标之一．生存分析是研究多种因素与生存时间的关系以及关系程度的大小．Cox回归模型是生存分析中常用的方法之一．本文利用Cox回归模型对786名肝癌患者进行生存分析,确定影响肝癌患者预后的主要因素是癌栓、肝癌部位、治疗方式、肝脏储备功能、端粒酶活性、细胞增殖活性、γ-GT(γ-谷氮酰转肽酶)、术后复发等．为临床研究延长肝癌病人的生存期,提高其生存率提供了有力的依据．     

Joint Modelling of Repeated Measures and Survival Time Data

In many clinical trials both repeated measures data and event history data are simultaneously observed from the same subject. These two types of responses are usually correlated, because they are from the same subject. In this article, we propose a joint model for the combined analysis of repeated measures data and event history data in the framework of hierarchical generalized linear models. The correlation between repeated measures and event time is modelled by introducing a shared random effect. The model parameters are estimated using the hierarchical‐likelihood approach. The proposed model is illustrated using a real data set for the renal transplant patients.     

基于Logistic回归模型分析维持性血液透析患者肌少症的危险因素及其对患者生活质量、负性情绪及生存状况的影响

摘要 目的：基于Logistic回归模型分析维持性血液透析（MHD）患者肌少症的危险因素及其对患者生活质量、负性情绪及生存状况的影响。方法：选取江苏省人民医院肾内科肾脏病重症病房于2019年2月-2021年2月期间收治的MHD患者289例,收集所有患者的一般资料,根据是否患有肌少症将患者分为肌少症组（n=71）及非肌少症组（n=218）。采用单因素和多因素Logistic回归模型分析MHD患者肌少症的危险因素,并观察两组生活质量、负性情绪及生存状况。结果：肌少症组、非肌少症组在年龄、透析时间、规律运动、体质量指数（BMI）、人体蛋白质含量（PM）、去脂体质量（FFM）、改良定量主观评估表（MQSGA）评分、血磷、超敏C反应蛋白（hs-CRP）、血肌酐、前白蛋白、白蛋白组间对比差异有统计学意义（P<0.05）。多因素Logistic回归分析,结果显示年龄偏大、透析时间偏长、BMI下降、MQSGA评分偏高、hs-CRP偏高、血肌酐偏高是MHD患者发生肌少症的危险因素,高血磷、规律运动则是其保护因素（P<0.05）。肌少症组患者的精神健康、生理职能、总体健康、生理功能、社会功能、活力、躯体疼痛、情感职能评分均低于非肌少症组（P<0.05）。肌少症组患者的抑郁自评量表（SDS）、焦虑自评量表（SAS）评分高于非肌少症组（P<0.05）。随访1年后,肌少症组的死亡率明显高于非肌少症组（P<0.05）。结论：MHD患者并发肌少症受到年龄、透析时间、BMI、MQSGA评分、hs-CRP、血肌酐、血磷、规律运动等因素的影响,且并发肌少症的患者其抑郁焦虑程度更重,生活质量更差,生存期缩短。     

Application of the Principal Components Method and the Proportional Hazards Regression Model to Analysis of Survival Data

One of factor analysis techniques, viz. the principal components method, and the proportional hazards regression model (Cox, 1972) are applied in this work to study the significance of various factors characterizing the patient, the disease, and the method of treatment in the survival. The application of these methods to analysis of survival data for cervical cancer patients has shown, in particular, the tumor growth rate to be the crucial factor in distribution of the patients survival time and to be even more important than the therapy characteristics.     

Joint Analysis of Survival Time and Longitudinal Categorical Outcomes

In biomedical or public health research, it is common for both survival time and longitudinal categorical outcomes to be collected for a subject, along with the subject’s characteristics or risk factors. Investigators are often interested in finding important variables for predicting both survival time and longitudinal outcomes which could be correlated within the same subject. Existing approaches for such joint analyses deal with continuous longitudinal outcomes. New statistical methods need to be developed for categorical longitudinal outcomes. We propose to simultaneously model the survival time with a stratified Cox proportional hazards model and the longitudinal categorical outcomes with a generalized linear mixed model. Random effects are introduced to account for the dependence between survival time and longitudinal outcomes due to unobserved factors. The Expectation–Maximization (EM) algorithm is used to derive the point estimates for the model parameters, and the observed information matrix is adopted to estimate their asymptotic variances. Asymptotic properties for our proposed maximum likelihood estimators are established using the theory of empirical processes. The method is demonstrated to perform well in finite samples via simulation studies. We illustrate our approach with data from the Carolina Head and Neck Cancer Study (CHANCE) and compare the results based on our simultaneous analysis and the separately conducted analyses using the generalized linear mixed model and the Cox proportional hazards model. Our proposed method identifies more predictors than by separate analyses.     

Survival analysis in clinical trials: past developments and future directions

The field of survival analysis emerged in the 20th century and experienced tremendous growth during the latter half of the century. The developments in this field that have had the most profound impact on clinical trials are the Kaplan-Meier (1958, Journal of the American Statistical Association 53, 457-481) method for estimating the survival function, the log-rank statistic (Mantel, 1966, Cancer Chemotherapy Report 50, 163-170) for comparing two survival distributions, and the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-220) proportional hazards model for quantifying the effects of covariates on the survival time. The counting-process martingale theory pioneered by Aalen (1975, Statistical inference for a family of counting processes, Ph.D. dissertation, University of California, Berkeley) provides a unified framework for studying the small- and large-sample properties of survival analysis statistics. Significant progress has been achieved and further developments are expected in many other areas, including the accelerated failure time model, multivariate failure time data, interval-censored data, dependent censoring, dynamic treatment regimes and causal inference, joint modeling of failure time and longitudinal data, and Baysian methods.     

Cox Regression in Nested Case–Control Studies with Auxiliary Covariates

Summary Nested case–control (NCC) design is a popular sampling method in large epidemiological studies for its cost effectiveness to investigate the temporal relationship of diseases with environmental exposures or biological precursors. Thomas' maximum partial likelihood estimator is commonly used to estimate the regression parameters in Cox's model for NCC data. In this article, we consider a situation in which failure/censoring information and some crude covariates are available for the entire cohort in addition to NCC data and propose an improved estimator that is asymptotically more efficient than Thomas' estimator. We adopt a projection approach that, heretofore, has only been employed in situations of random validation sampling and show that it can be well adapted to NCC designs where the sampling scheme is a dynamic process and is not independent for controls. Under certain conditions, consistency and asymptotic normality of the proposed estimator are established and a consistent variance estimator is also developed. Furthermore, a simplified approximate estimator is proposed when the disease is rare. Extensive simulations are conducted to evaluate the finite sample performance of our proposed estimators and to compare the efficiency with Thomas' estimator and other competing estimators. Moreover, sensitivity analyses are conducted to demonstrate the behavior of the proposed estimator when model assumptions are violated, and we find that the biases are reasonably small in realistic situations. We further demonstrate the proposed method with data from studies on Wilms' tumor.     

改良拔河针法对膝关节骨性关节炎患者远期关节功能和生活质量的影响

摘要 目的：探讨改良拔河针法对膝关节骨性关节炎患者远期关节功能和生活质量的影响，以期为膝关节骨性关节炎患者的治疗提供更加合理方案。方法：选取2016年3月至2019年10月深圳市中西医结合医院收治的60例膝关节骨性关节炎患者为研究对象。采用系统随机化法分为常规针刺组、改良拔河针法组各30例。常规针刺组采用常规针刺治疗，改良拔河针法组采用改良拔河针法治疗。分别于疗程结束时比较两组临床有效率，于治疗前、治疗后及治疗后3个月比较两组患者疼痛评级指数（PRI）评分、Oswestry功能障碍指数问卷表（ODI）评分及简明健康状况调查量表（SF-36）评分。结果：改良拔河针法组临床有效率86.67%，略高于常规针刺组的80.00%，但组间比较差异无统计学意义（P＞0.05）。组内比较显示，两组患者治疗后、治疗后3个月的PRI评分、ODI评分及SF-36评分较治疗前均降低（P＜0.05），且治疗后3个月的PRI评分、ODI评分及SF-36评分低于治疗后（P＜0.05）。组间比较显示，两组患者治疗前、治疗后PRI评分、ODI评分及SF-36评分比较差异均无统计学意义（P＞0.05），但改良拔河针法组治疗后3个月的ODI评分及SF-36评分优于常规针刺组（P＜0.05）。结论：改良拔河针法治疗膝关节骨性关节炎患者可获得普通针刺法相当的临床效果，且在改善患者远期关节功能和生活质量方面效果更佳，值得临床推广应用。     

Regression Calibration in Semiparametric Accelerated Failure Time Models

Summary In large cohort studies, it often happens that some covariates are expensive to measure and hence only measured on a validation set. On the other hand, relatively cheap but error‐prone measurements of the covariates are available for all subjects. Regression calibration (RC) estimation method ( Prentice, 1982 , Biometrika 69 , 331–342) is a popular method for analyzing such data and has been applied to the Cox model by Wang et al. (1997, Biometrics 53 , 131–145) under normal measurement error and rare disease assumptions. In this article, we consider the RC estimation method for the semiparametric accelerated failure time model with covariates subject to measurement error. Asymptotic properties of the proposed method are investigated under a two‐phase sampling scheme for validation data that are selected via stratified random sampling, resulting in neither independent nor identically distributed observations. We show that the estimates converge to some well‐defined parameters. In particular, unbiased estimation is feasible under additive normal measurement error models for normal covariates and under Berkson error models. The proposed method performs well in finite‐sample simulation studies. We also apply the proposed method to a depression mortality study.     

加速康复外科理论对老年股骨颈骨折患者髋关节功能、生活质量及术后认知功能的影响

摘要 目的：探讨加速康复外科理论（ERAS）对老年股骨颈骨折（FNF）患者髋关节功能、生活质量以及术后认知功能的影响。方法：选取2018年7月~2019年10月期间我院收治的80例老年FNF患者,按照随机数字表法分为对照组（n=40）和研究组（n=40）,对照组给予常规围术期处理,研究组围术期应用ERAS进行处理,比较两组患者围术期指标、髋关节功能、生活质量、术后认知功能及并发症发生情况。结果：研究组术中出血量少于对照组,手术时间、住院时间短于对照组（P<0.05）。研究组术后6个月髋关节功能的优良率为92.50%（37/40）,高于对照组的70.00%（28/40）（P<0.05）。两组术后6个月SF-36各维度评分均升高,且研究组高于对照组（P<0.05）。两组术后简易智力状态量表（MMSE）评分均较术前降低,但研究组高于对照组（P<0.05）;研究组的认知功能障碍（POCD）发生率低于对照组（P<0.05）。研究组的并发症总发生率为7.50%（3/40）,低于对照组的25.00%（10/40）（P<0.05）。结论：老年FNF患者应用ERAS进行围术期处理,可促进患者术后恢复,减轻认知功能损害及并发症发生率,同时还可有效改善髋关节功能及生活质量。