The analysis of incomplete data using stochastic covariates

In the development of many diseases there are often associated random variables which continuously reflect the progress of a subject towards the final expression of the disease (failure). At any given time these processes, which we call stochastic covariates, may provide information about the current hazard and the remaining time to failure. Likewise, in situations when the specific times of key prior events are not known, such as the time of onset of an occult tumour or the time of infection with HIV-1, it may be possible to identify a stochastic covariate which reveals, indirectly, when the event of interest occurred. The analysis of carcinogenicity trials which involve occult tumours is usually based on the time of death or sacrifice and an indicator of tumour presence for each animal in the experiment. However, the size of an occult tumour observed at the endpoint represents data concerning tumour development which may convey additional information concerning both the tumour incidence rate and the rate of death to which tumour-bearing animals are subject. We develop a stochastic model for tumour growth and suggest different ways in which the effect of this growth on the hazard of failure might be modelled. Using a combined model for tumour growth and additive competing risks of death, we show that if this tumour size information is used, assumptions concerning tumour lethality, the context of observation or multiple sacrifice times are no longer necessary in order to estimate the tumour incidence rate. Parametric estimation based on the method of maximum likelihood is outlined and is applied to simulated data from the combined model. The results of this limited study confirm that use of the stochastic covariate tumour size results in more precise estimation of the incidence rate for occult tumours.     

BAYESIAN HIDDEN MARKOV MODELS FOR LONGITUDINAL COUNTS

This paper describes a Bayesian approach to modelling carcinogenity in animal studies where the data consist of counts of the number of tumours present over time. It compares two autoregressive hidden Markov models. One of them models the transitions between three latent states: an inactive transient state, a multiplying state for increasing counts and a reducing state for decreasing counts. The second model introduces a fourth tied state to describe non‐zero observations that are neither increasing nor decreasing. Both these models can model the length of stay upon entry of a state. A discrete constant hazards waiting time distribution is used to model the time to onset of tumour growth. Our models describe between‐animal‐variability by a single hierarchy of random effects and the within‐animal variation by first‐order serial dependence. They can be extended to higher‐order serial dependence and multi‐level hierarchies. Analysis of data from animal experiments comparing the influence of two genes leads to conclusions that differ from those of Dunson (2000). The observed data likelihood defines an information criterion to assess the predictive properties of the three‐ and four‐state models. The deviance information criterion is appropriately defined for discrete parameters.     

上海地区干部健康体检胸部肿瘤的X线分析

目的回顾性分析1996年～2000年上海地区干部在我院健康体检胸部肿瘤的检出情况,探讨健康体检在早期发现胸部肿瘤的意义和方法。方法全部病例均经电视透视发现胸部异常阴影后,再摄取胸部正侧位片,并进一步进行各种检查初步明确诊断,经随访、手术及病理证实。结果被检出的160例胸部肿瘤中,肺恶性肿瘤87例,肺良性肿瘤23例,纵膈肿瘤45例,胸壁横膈肿瘤5例。67例周围型肺癌平均瘤体直径2.2cm,≤2cm的早期肺癌38例占56.72%。在电视透视发现的67例周围型肺癌和45例纵膈肿瘤中,分别有25例(37.31%)和21例(46.67%)在胸部平片中不能显示。结论定期胸部健康体检是早期发现胸部肿瘤的主要方法,在干部保健工作中有重要意义。胸部电视透视是健康体检早期发现胸部肿瘤的重要手段,采用肿瘤追踪筛查方法能有效地提高肺部肿瘤检出率。     

放射治疗可变野准直器的研究与设计

在总结归纳了不同时期放射治疗设备准直器的设计和应用之后,分析了它们的优点以及不足,提出了可变野准直器。它是采用机电一体化和机器人技术原理设计而成,并模拟IMRT的方式进行准直器调强的验证。对提出的可变野准直器的原理和特点进行解释,对设计方案进行了详细阐述。该设备活动空间增大,改进了特殊部位肿瘤的治疗,成为先进放疗系统中最关键的部件之一。     

Attribution of tumour lethality and estimation of the time to onset of occult tumours in the absence of cause-of-death Information

A new statistical approach is developed for estimating the carcinogenic potential of drugs and other chemical substances used by humans. Improved statistical methods are developed for rodent tumorigenicity assays that have interval sacrifices but not cause-of-death data. For such experiments, this paper proposes a nonparametric maximum likelihood estimation method for estimating the distributions of the time to onset of and the time to death from the tumour. The log-likelihood function is optimized using a constrained direct search procedure. Using the maximum likelihood estimators, the number of fatal tumours in an experiment can be imputed. By applying the procedure proposed to a real data set, the effect of calorie restriction is investigated. In this study, we found that calorie restriction delays the tumour onset time significantly for pituitary tumours. The present method can result in substantial economic savings by relieving the need for a case-by-case assignment of the cause of death or context of observation by pathologists. The ultimate goal of the method proposed is to use the imputed number of fatal tumours to modify Peto's International Agency for Research on Cancer test for application to tumorigenicity assays that lack cause-of-death data.     

Mixed‐scale models for survival/sacrifice experiments

Information derived from interim sacrifices or on cause of death is routinely used in the statistical analyses of carcinogenicity experiments involving occult tumours. The authors describe a simple semiparametric model which does not require this information. Natural deaths during the experiment and the usual terminal sacrifice provide sufficient information to ensure that the tumour incidence rates, which are of primary interest in occult‐tumour studies, can be estimated nonparametrically. The advantages of this semiparametric approach to the analysis of survival/sacrifice experiments are illustrated using data from a study on benzyl acetate conducted under the U. S. National Toxicology Program. The results derived compare favourably with those obtained using a previously published approach to the analysis of tumorigenicity data.     

Discrete Scale Models for Survival–Sacrifice Experiments

Analyses of carcinogenicity experiments involving occult (hidden) tumours are usually based on cause-of-death information or the results of many interim sacrifices. A simple compartmental model is described that does not involve the cause of death. The method of analysis requires only one interim sacrifice, in addition to the usual terminal kill, to ensure that the tumour incidence rates can be estimated. One advantage of the approach is demonstrated in the analysis of glomerulosclerosis following exposure to ionizing radiation. Although the semiparametric model involves fewer parameters, estimates of key functions derived in this analysis are similar to those obtained previously by using a nonparametric method that involves many more parameters.     

EZH2的功能及在肿瘤中的表达

EZH2在多种肿瘤中呈高表达,其过表达与组织学分化程度、临床分期、肿瘤大小、淋巴结转移和预后相关。本文就EZH2的结构、功能、与沉默机制相关的其他酶之间的联系,及其在肿瘤中的表达作一综述。     

肿瘤预后的临床试验研究

预后研究是对疾病的发生、发展及转归结局的预测。本文探讨了在肿瘤预后研究中的临床试验研究方法的评价 ,影响预后的因素和肿瘤预后的四种研究方法及其注意事项。并对肿瘤的预后因素与预后结局之间的联系作了初步介绍