A case–control study relating railroad worker mortality to diesel exhaust exposure using a threshold regression model

A case–control study of lung cancer mortality in U.S. railroad workers in jobs with and without diesel exhaust exposure is reanalyzed using a new threshold regression methodology. The study included 1256 workers who died of lung cancer and 2385 controls who died primarily of circulatory system diseases. Diesel exhaust exposure was assessed using railroad job history from the US Railroad Retirement Board and an industrial hygiene survey. Smoking habits were available from next-of-kin and potential asbestos exposure was assessed by job history review. The new analysis reassesses lung cancer mortality and examines circulatory system disease mortality. Jobs with regular exposure to diesel exhaust had a survival pattern characterized by an initial delay in mortality, followed by a rapid deterioration of health prior to death. The pattern is seen in subjects dying of lung cancer, circulatory system diseases, and other causes. The unique pattern is illustrated using a new type of Kaplan–Meier survival plot in which the time scale represents a measure of disease progression rather than calendar time. The disease progression scale accounts for a healthy-worker effect when describing the effects of cumulative exposures on mortality.     

后期维特根斯坦对哲学病的探究

维特根斯坦是自康德以来西方哲学史上对哲学的性质问题作深入思考的又一位重要哲学家。他在后期哲学中认为 ,以往哲学总是采取心理主义或本质主义的单一固定模式来理解日常语言 ,结果导致了哲学语言的痼疾。基于此 ,哲学的任务是 :既要全面了解日常语言所描述的问题 ,获得“全貌概观” ,又要依照某种具体情境 ,对日常语言停留在“家族相似”层面上的理解 ,以还日常语言丰富和真实的“游戏”本色。     

魏晋南北朝时期疾疫研究综述（1980～2006）

魏晋南北朝时期是中国古代疾疫的高发阶段,一些学者们对这方面的研究颇为重视。20世纪80年代以来,随着认识和研究的不断深入,研究成果层出不穷,一些独特的研究方法及其特点也逐渐呈现出来。总结经验,抓住薄弱环节,有助于此项研究进一步得到深入。     

Response-adaptive trial designs with accelerated Thompson sampling

In a clinical trial, sometimes it is desirable to allocate as many patients as possible to the best treatment, in particular, when a trial for a rare disease may contain a considerable portion of the whole target population. The Gittins index rule is a powerful tool for sequentially allocating patients to the best treatment based on the responses of patients already treated. However, its application in clinical trials is limited due to technical complexity and lack of randomness. Thompson sampling is an appealing approach, since it makes a compromise between optimal treatment allocation and randomness with some desirable optimal properties in the machine learning context. However, in clinical trial settings, multiple simulation studies have shown disappointing results with Thompson samplers. We consider how to improve short-run performance of Thompson sampling and propose a novel acceleration approach. This approach can also be applied to situations when patients can only be allocated by batch and is very easy to implement without using complex algorithms. A simulation study showed that this approach could improve the performance of Thompson sampling in terms of average total response rate. An application to a redesign of a preference trial to maximize patient's satisfaction is also presented.     

College and University Health Care Professionals: An Expanding Team

Abstract

Factors contributing to students' compliance with mass vaccination programs during meningococcal outbreaks have not been well described. A 1997 mass vaccination campaign at Michigan State University provided an opportunity to study such factors. Of 34 024 students in the target population, 17 538 (51.5%) were vaccinated in 5 days. Vaccination rates were higher for women (47.9%) than for men (43.1 %) and higher for on-campus residents (65.3%) than for off-campus residents (35.6%). For each year of students' age beyond 19, the adjusted odds of vaccination were reduced by 0.82. Adjusted odds ratios for vaccination, with White students as the reference group at 1.0, were 1.33 for Asian American students, 0.97 (not significant) for Hispanic students, 0.82 for African American students, and 0.80 for Native American students. Students from the Colleges of Business, Engineering, Communication, and Natural Science had the highest vaccination rates; those from the College of Arts and Letters had the lowest rates.     

Healthy Barbs: Activism Confronts Mortality

Barbara Brenner, JD, was the Executive Director of Breast Cancer Action (BCA) from 1995–2010. Before that, she was a longtime activist in the anti-war movement and an attorney who, for most of her career, practiced public policy law. After she was diagnosed with breast cancer in 1993 at the age of 41, she took the helm of BCA. Under her leadership, the organization moved into a position of national advocacy—demanding research on the causes and prevention of breast cancer, including the role of industrial pollutants. Barbara started the “Think Before You Pink” campaign, encouraging people to question whether companies that display pink ribbons actually produce products that harm women's health or generate any funds to fight breast cancer. Her blog, “Healthy Barbs,” challenged readers to critique routine healthcare practices and policies. Barbara received numerous awards, including a Jefferson Award for Public Service in 2007, the Smith College Medal in 2012, and the ACLU-Northern California's Lola Hanzel Courageous Advocacy Award in 2012. Barbara had a recurrence of breast cancer in 1996. She died of complications associated with amyotrophic lateral sclerosis, ALS, on May 10, 2013.     

Efficient heterogeneous sampling for stochastic simulation with an illustration in health care applications

In modeling disease transmission, contacts are assumed to have different infection rates. A proper simulation must model the heterogeneity in the transmission rates. In this article, we present a computationally efficient algorithm that can be applied to a population with heterogeneous transmission rates. We conducted a simulation study to show that the algorithm is more efficient than other algorithms for sampling the disease transmission in a subset of the heterogeneous population. We use a valid stochastic model of pandemic influenza to illustrate the algorithm and to estimate the overall infection attack rates of influenza A (H1N1) in a Canadian city.     

我国古代政府的疫病控制措施

疫病是人类共同的敌人,在历史发展过程中,它无时无刻不在威胁着我们祖先的身体健康和生命安全。直到医学科学高度发达的今天,我们仍然不能摆脱疫病造成的恐惧和苦难。我国是世界文明发祥地之一,很早以前就有了同疫病做斗争的经验和教训,在长期艰苦不懈的探索中,我们的祖先不断发现治疗疾病和控制传染的办法,无论是医家还是政府,都为我们留下了宝贵的财富。了解历史,能够为当前有效预防和控制SARS的再次出现提供借鉴和帮助。     

A SEMI-MARKOV MODEL FOR EAR INFECTION

A recent study of the prevalence of middle ear infection among Australian aborigines reports, for different age groups, the number currently infected, the number currently not infected and the number who are currently not infected but have scarring of the ear drum showing evidence of a previous infection. Incidence and recovery are modelled by a semi-Markov model in which incidence of the infection is allowed to be nonstationary.     

Risk/Benefit Assessments of Human Diseases: Optimum Dose for Intervention

A simple procedure is proposed in order to quantify the tradeoff between a loss suffered from an illness due to exposure to a microbial pathogen and a loss due to a toxic effect, perhaps a different illness, induced by a disinfectant employed to reduce the microbial exposure. Estimates of these two types of risk as a function of disinfectant dose and their associated relative losses provide information for the estimation of the optimum dose of disinfectant that minimizes the total expected loss. The estimates of the optimum dose and expected relative total loss were similar regardless of whether the beta-Poisson, log-logistic, or extreme value function was used to model the risk of illness due to exposure to a microbial pathogen. This is because the optimum dose of the disinfectant and resultant expected minimum loss depend upon the estimated slope (first derivative) of the models at low levels of risk, which appear to be similar for these three models at low levels of risk. Similarly, the choice among these three models does not appear critical for estimating the slope at low levels of risk for the toxic effect induced by the use of a disinfectant. For the proposed procedure to estimate the optimum disinfectant dose, it is not necessary to have absolute values for the losses due to microbial-induced or disinfectant-induced illness, but only relative losses are required. All aspects of the problem are amenable to sensitivity analyses. The issue of risk/benefit tradeoffs, more appropriately called risk/risk tradeoffs, does not appear to be an insurmountable problem.