A Parametric Estimation Procedure for Relapse Time Distributions

In a relapse clinical trial patients who have recovered from some recurrent disease (e.g.,ulcer or cancer) are examined at a number of predetermined times. A relapse can be detected either at one of these planned inspections or at a spontaneous visit initiated by the patient because of symptoms. In the first case the observations of the time to relapse, X, is interval-censored by two predetermined time-points. In the second case the upper endpoint of the interval is an observation of the time to symptoms,Y . To model the progression of the disease we use a partially observable Markov process. This approach results in a bivariate phase-type distribution for the joint distribution of (X,Y). It is a flexible model which contains several natural distributions for X, and allows the conditional distributions of the marginals to smoothly depend on each other. To estimate the distributions involved we develop an EM-algorithm. The estimation procedure is evaluated and compared with a non-parametric method in a couple of examples based on simulated data.     

试论审判权独立的反向思考

以三权分立思想作为审判权独立的根据在理论上存在不足,三权分立不是法治社会的标志,我国的审判权也不同于西方的司法权。我国的审判权包括普遍意义上的裁判权、具有自身特色的调解权、行政角色浓厚的判决执行权和在政法委统一领导下的政法委决议执行权。从制度功能来看,裁判权、调解权基本等同于司法权,是审判权独立的主体,并且为了防止法官以判逼调,调解权应当独立于裁判权。裁判执行权、政法委决议执行权因不具有居中裁判性质,不是审判权独立的内容。要求审判权完全独立是脱离了中国国情的空想;以审判机构的独立代替审判权独立犯了逻辑上的错误;没有独立地位法官的审判程序将无法克服程序内在的缺陷。审判权独立应当是具有独立地位的办案法官、办案程序与办案保障三者相结合的审判制度。     

论法官在民商事案件证明责任分配中的自由裁量权

充分、有效地与当事人沟通,坚持公平、公正的原则,从而正确运用法官自由裁量权对证明责任进行分配,有利于查清案件事实,促进司法公正。结合审判实际讨论了法官在不同情况下如何坚持一定的原则,根据不同情形,正确运用自由裁量权进行证明责任分配等问题,如在没有法律、法规、及司法解释具体规定的情形下,法官在运用自由裁量权进行证明责任分配时应遵守诚实信用、程序公开透明、公平公正、经验惯例、综合平衡等原则。在双方地位不平等,可能导致显示公平的情形下,法官需要结合具体案情,根据相关原则进行具体证明责任分配。     

中国农村土地制度变迁的政策过程及现实困境

新中国成立以来的农村土地制度历经了从均分化土地私有制到集体所有制,再到家庭承包经营制和承包经营权物权化的复杂变迁过程,当前正沿着“赋予农民长期而有保障的使用权”的方向而不断完善。但农村土地制度仍存在产权不明晰等深层次问题,新时期土地制度变革的关键在于为农民提供更全面、更完整的土地财产权利,真正实现土地要素的财产化、资产化,并最终为土地要素的城乡一体化和市场化奠定坚实的基础。     

Improving precision and power in randomized trials with a two-stage study design: Stratification using clustering method

In a randomized controlled trial (RCT), it is possible to improve precision and power and reduce sample size by appropriately adjusting for baseline covariates. There are multiple statistical methods to adjust for prognostic baseline covariates, such as an ANCOVA method. In this paper, we propose a clustering-based stratification method for adjusting for the prognostic baseline covariates. Clusters (strata) are formed only based on prognostic baseline covariates, not outcome data nor treatment assignment. Therefore, the clustering procedure can be completed prior to the availability of outcome data. The treatment effect is estimated in each cluster, and the overall treatment effect is derived by combining all cluster-specific treatment effect estimates. The proposed implementation of the procedure is described. Simulations studies and an example are presented.     

Regional efficacy evaluation in multi-regional clinical trials using a discounting factor weighted Z test

Multi-regional clinical trial (MRCT) is an efficient design to accelerate drug approval globally. Once the global efficacy of test drug is demonstrated, each local regulatory agency is required to prove effectiveness of test drug in their own population. Meanwhile, the ICH E5/E17 guideline recommends using data from other regions to help evaluate regional drug efficacy. However, one of the most challenges is how to manage to bridge data among multiple regions in an MRCT since various intrinsic and extrinsic factors exist among the participating regions. Furthermore, it is critical for a local agency to determine the proportion of information borrowing from other regions given the ethnic differences between target region and non-target regions. To address these issues, we propose a discounting factor weighted Z statistic to adaptively borrow information from non-target regions. In this weighted Z statistic, the weight is derived from a discounting factor in which the discounting factor denotes the proportion of information borrowing from non-target regions. We consider three ways to construct discounting factors based on the degree of congruency between target and non-target regions either using control group data, or treatment group data, or all data. We use the calibrated power prior to construct discounting factor based on scaled Kolmogorov–Smirnov statistic. Comprehensive simulation studies show that our method has desirable operating characteristics. Two examples are used to illustrate the applications of our proposed approach.     

Generalized phase I-II designs to increase long term therapeutic success rate

Designs for early phase dose finding clinical trials typically are either phase I based on toxicity, or phase I-II based on toxicity and efficacy. These designs rely on the implicit assumption that the dose of an experimental agent chosen using these short-term outcomes will maximize the agent's long-term therapeutic success rate. In many clinical settings, this assumption is not true. A dose selected in an early phase oncology trial may give suboptimal progression-free survival or overall survival time, often due to a high rate of relapse following response. To address this problem, a new family of Bayesian generalized phase I-II designs is proposed. First, a conventional phase I-II design based on short-term outcomes is used to identify a set of candidate doses, rather than selecting one dose. Additional patients then are randomized among the candidates, patients are followed for a predefined longer time period, and a final dose is selected to maximize the long-term therapeutic success rate, defined in terms of duration of response. Dose-specific sample sizes in the randomization are determined adaptively to obtain a desired level of selection reliability. The design was motivated by a phase I-II trial to find an optimal dose of natural killer cells as targeted immunotherapy for recurrent or treatment-resistant B-cell hematologic malignancies. A simulation study shows that, under a range of scenarios in the context of this trial, the proposed design has much better performance than two conventional phase I-II designs.     

The potential for bias in reporting of industry-sponsored clinical trials

Concerns about potentially misleading reporting of pharmaceutical industry research have surfaced many times. The potential for duality (and thereby conflict) of interest is only too clear when you consider the sums of money required for the discovery, development and commercialization of new medicines. As the ability of major, mid-size and small pharmaceutical companies to innovate has waned, as evidenced by the seemingly relentless decline in the numbers of new medicines approved by Food and Drug Administration and European Medicines Agency year-on-year, not only has the cost per new approved medicine risen: so too has the public and media concern about the extent to which the pharmaceutical industry is open and honest about the efficacy, safety and quality of the drugs we manufacture and sell. In 2005 an Editorial in Journal of the American Medical Association made clear that, so great was their concern about misleading reporting of industry-sponsored studies, henceforth no article would be published that was not also guaranteed by independent statistical analysis. We examine the precursors to this Editorial, as well as its immediate and lasting effects for statisticians, for the manner in which statistical analysis is carried out, and for the industry more generally.     

家电行业员工流动性与对策——以慈溪家电企业员工流动性实证分析为例

在知识经济时代,企业内员工的流动性大幅度增加,尤其是中小企业更加明显,不仅会影响到企业的长远发展,对社会稳定也造成了一定的影响。文章采用调查问卷的方式,对慈溪市家电企业员工流动的影响因素进行实证分析,从企业角度提出了进行人力资源规划、健全企业选拔和用人机制、提倡以人为本的企业文化建设等过程性管理措施,以期对慈溪市家电企业加强员工的有效管理,降低其流动率有所帮助。     

Can a treatment be licenced on the basis of post‐treatment predictive biomarkers?

In recent years, there has been a great deal of literature published concerning the identification of predictive biomarkers and indeed, an increasing number of therapies have been licenced on this basis. However, this progress has been made almost exclusively on the basis of biomarkers measured prior to exposure to treatment. There are quite different challenges when the responding population can only be identified on the basis of outcomes observed following exposure to treatment, especially if it represents only a small proportion of patients. The purpose of this paper is to explore whether or when a treatment could be licenced on the basis of post‐treatment predictive biomarkers (PTPB), the focus is on oncology but the concepts should apply to all therapeutic areas. We review the potential pitfalls in hypothesising the presence of a PTPB. We also present challenges in trial design required to confirm and licence on the basis of a PTPB: what's the control population?, could there be a detriment to non‐responders by exposure to the new treatment?, can responders be identified rapidly?, could prior exposure to the new treatment adversely affect performance of the control in responders? Nevertheless, if the patients to be treated could be rapidly identified after prior exposure to treatment, and without harm to non‐responders, in appropriately designed and analysed trials, may be more targeted therapies could be made available to patients. Copyright © 2014 John Wiley & Sons, Ltd.