Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis

Summary With increasing frequency, epidemiologic studies are addressing hypotheses regarding gene‐environment interaction. In many well‐studied candidate genes and for standard dietary and behavioral epidemiologic exposures, there is often substantial prior information available that may be used to analyze current data as well as for designing a new study. In this article, first, we propose a proper full Bayesian approach for analyzing studies of gene–environment interaction. The Bayesian approach provides a natural way to incorporate uncertainties around the assumption of gene–environment independence, often used in such an analysis. We then consider Bayesian sample size determination criteria for both estimation and hypothesis testing regarding the multiplicative gene–environment interaction parameter. We illustrate our proposed methods using data from a large ongoing case–control study of colorectal cancer investigating the interaction of N‐acetyl transferase type 2 (NAT2) with smoking and red meat consumption. We use the existing data to elicit a design prior and show how to use this information in allocating cases and controls in planning a future study that investigates the same interaction parameters. The Bayesian design and analysis strategies are compared with their corresponding frequentist counterparts.     

Estimating absolute and relative case fatality ratios from infectious disease surveillance data

Knowing which populations are most at risk for severe outcomes from an emerging infectious disease is crucial in deciding the optimal allocation of resources during an outbreak response. The case fatality ratio (CFR) is the fraction of cases that die after contracting a disease. The relative CFR is the factor by which the case fatality in one group is greater or less than that in a second group. Incomplete reporting of the number of infected individuals, both recovered and dead, can lead to biased estimates of the CFR. We define conditions under which the CFR and the relative CFR are identifiable. Furthermore, we propose an estimator for the relative CFR that controls for time-varying reporting rates. We generalize our methods to account for elapsed time between infection and death. To demonstrate the new methodology, we use data from the 1918 influenza pandemic to estimate relative CFRs between counties in Maryland. A simulation study evaluates the performance of the methods in outbreak scenarios. An R software package makes the methods and data presented here freely available. Our work highlights the limitations and challenges associated with estimating absolute and relative CFRs in practice. However, in certain situations, the methods presented here can help identify vulnerable subpopulations early in an outbreak of an emerging pathogen such as pandemic influenza.     

Estimating Propensity Scores and Causal Survival Functions Using Prevalent Survival Data

Summary This article develops semiparametric approaches for estimation of propensity scores and causal survival functions from prevalent survival data. The analytical problem arises when the prevalent sampling is adopted for collecting failure times and, as a result, the covariates are incompletely observed due to their association with failure time. The proposed procedure for estimating propensity scores shares interesting features similar to the likelihood formulation in case‐control study, but in our case it requires additional consideration in the intercept term. The result shows that the corrected propensity scores in logistic regression setting can be obtained through standard estimation procedure with specific adjustments on the intercept term. For causal estimation, two different types of missing sources are encountered in our model: one can be explained by potential outcome framework; the other is caused by the prevalent sampling scheme. Statistical analysis without adjusting bias from both sources of missingness will lead to biased results in causal inference. The proposed methods were partly motivated by and applied to the Surveillance, Epidemiology, and End Results (SEER)‐Medicare linked data for women diagnosed with breast cancer.     

Dietary fibre intake associated with reduced risk of oesophageal cancer in Xinjiang,China

Objective: To ascertain the relationship between dietary fibre intake and risk of oesophageal cancer in remote northwest China, where the cancer incidence is known to be high. Methods: A case–control study was conducted during 2008–2009 in the Urumqi and Shihezi, Xinjiang Uyghur Autonomous Region of China. Participants were 359 incident oesophageal cancer patients and 380 hospital-based controls. Information on habitual foods consumption was obtained by face-to-face interview, from which dietary fibre intakes were estimated using the Chinese food composition tables. Results: The oesophageal cancer patients reported lower intake levels of total dietary fibre and fibre derived from vegetables and fruits than those of controls. Overall, regular intake of fibre was inversely associated with the oesophageal cancer risk, the adjusted odds ratio being 0.47 (95% confidence interval 0.32–0.69) for the highest (>27 g) versus the lowest (<16 g) tertile of daily intake, with a significant dose-response relationship (p = 0.004). Similar reductions in risk were also apparent for high intake levels of vegetable fibre and fruit fibre, but to a lesser extent for cereal fibre. Conclusion: Habitual intake of dietary fibre was associated with a reduced risk of oesophageal cancer for adults in northwest China.     

ICJ's Decision in Australia v. Japan: Giving up the Spear or Refining the Scientific Design?

The case Whaling in the Antarctic (Australia v. Japan) decided by the International Court of Justice is a landmark that introduces new parameters for measuring the “reasonableness” of scientific research by permit under the International Convention on Whaling. However, aspects of these parameters and how they may be applied in future cases remain uncertain. Because the Court's interpretation of the language “for purposes of scientific research” avoids defining scientific research, the Court's decision provides only a limited degree of clarification for States that intend to operate scientific whaling programs under Article VIII of the Convention. The Court's reasonableness test is unlikely to prevent scientific whaling. States who no longer support the dual object and purpose of the Whaling Convention may want to consider negotiating a new international instrument that would be more protective of whales and their habitat.     

Case reports of adverse effects of herbal medicinal products (HMPs): A quality assessment

Background

Case reports provide essential information on adverse effects. Yet there is little consistency in the quality and format of reporting them.

Aim

In this study, we aimed to assess the quality of case reports of adverse effect of herbal medicinal products (HMPs) published during three time periods, 1986-1988, 1996-1998, and 2006-2008.

Methods

We conducted literature searches in four major databases: Medline, EMBASE, AMED, and CINALH. Each case report was subject to specific inclusion criteria related to the intervention (i.e. herbal medicine) and outcome measurement (i.e. adverse effect). A 21-item scale was used to assess the quality of all included reports. Each report was categorised into low quality (score between 0 and 14), lower medium quality (score between 15 and 21), upper medium quality (score between 22 and 28), and high quality (score between 29 and 42).

Results

In total, 137 case reports were included. The percentage of high quality case reports rose from 0% in 1986-1988 to 27.9% in 1996-1998 and 34.2% in 2006-2008; conversely, the percentages of low quality case reports dropped from 13.3% in 1986-1988 to 0% in 1996-1998 and 2.5% in 2006-2008.

Conclusion

These findings are consistent with the notion that the quality of case reports is improving. However, due to several caveats, our data should be interpreted with caution.     

Asthma,allergy and the risk of prostate cancer: Results from the Montreal PROtEuS study

BackgroundThe few previous studies examining the association between asthma or allergy and prostate cancer (PCa) risk were inconclusive. This study aimed to evaluate these associations, and to explore in details the possible influence of current versus former allergic condition, age at onset, time since onset, and duration of each allergic condition.MethodsDetailed information on self-reported asthma and allergy was collected in the context of a large population-based case–control study conducted in Montreal, Canada. Study subjects included 1936 cases, diagnosed between 2005 and 2009, and 1995 population controls. Unconditional multivariate logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusting for age, ancestry and familial history of prostate cancer.ResultsThe ORs were 1.11 (95% CI: 0.89–1.40) and 0.98 (95% CI: 0.84–1.14) for ever reporting of asthma and allergy, respectively. These ORs did not substantially vary according to status (former or current), age at onset, time since onset, and duration of each allergic condition. PCa screening was not associated with allergic diseases reporting.ConclusionsOverall, our findings are in line with the absence of an association between a history of asthma or allergy, and PCa risk.     

颅骨过度气化1例影像表现并文献复习

目的:颅骨过度气化(Craniocervical bone pneumatisation)比较少见,近年来对其报道和认识逐渐增多。本文介绍一例偶然发现的颅骨过度气化的影像表现并对相关文献进行复习。方法:分析我院1例颅骨过度气化的影像学图像。并从国外pubmed数据库(www.pubmed.gov)及国内中国知网数据库(www.cnki.net)查找发表的文献进行文献复习。结果:颅骨过度气化表现为颅骨的气腔形成并局部膨出,多为偶然发现或因并发症就诊,可涉及颅盖骨、颅底骨及颈椎等,近年来对其认识逐渐增多。结论:颅骨过度气化尽管少见,对征象的认知有助于相关科室医师正确识别此征象,从而有利于临床一些相关疑难病例的诊断和操作并对防止漏、误诊具有一定的意义。     

成人腹膜后节细胞神经纤维瘤1例暨文献复习

原发性腹膜后节细胞神经纤维瘤在临床上是属于极少见的病例,通常患者就诊时无明显临床症状。本文报道1例43岁成年男性的腹膜后节细胞神经纤维瘤并进行相关文献的复习。已有研究证实影像学检查可对原发性腹膜后肿瘤的良恶性鉴别提供重要依据,节细胞神经纤维瘤的影像学检查亦具有其特征性表现,但最终本病的确诊仍依赖病理及免疫组化技术。影像学检查是确定原发性腹膜后肿瘤的治疗计划的必要措施。目前手术已成为治疗腹膜后节细胞神经纤维瘤的首选治疗。辅以血管外科技术,肿瘤的根治性切除已在临床上广泛开展。通过手术治疗后尽管有二次复发可能,但腹膜后节细胞神经瘤预后仍较好。     

Design and analysis of multiple diseases genome-wide association studies without controls

In genome-wide association studies (GWAS), multiple diseases with shared controls is one of the case–control study designs. If data obtained from these studies are appropriately analyzed, this design can have several advantages such as improving statistical power in detecting associations and reducing the time and cost in the data collection process. In this paper, we propose a study design for GWAS which involves multiple diseases but without controls. We also propose corresponding statistical data analysis strategy for GWAS with multiple diseases but no controls. Through a simulation study, we show that the statistical association test with the proposed study design is more powerful than the test with single disease sharing common controls, and it has comparable power to the overall test based on the whole dataset including the controls. We also apply the proposed method to a real GWAS dataset to illustrate the methodologies and the advantages of the proposed design. Some possible limitations of this study design and testing method and their solutions are also discussed. Our findings indicate that the proposed study design and statistical analysis strategy could be more efficient than the usual case–control GWAS as well as those with shared controls.