Bayesian Models for Multiple Outcomes Nested in Domains

Summary We consider the problem of estimating the effect of exposure on multiple continuous outcomes, when the outcomes are measured on different scales and are nested within multiple outcome classes, or “domains.” Our Bayesian model extends the linear mixed models approach to allow the exposure effect to differ across domains and across outcomes within domains. Our model can be parameterized to allow shrinkage of the effects within the different levels of nesting, or to allow fixed domain‐specific effects with no shrinkage. Our model also allows covariate effects to differ across outcomes and domains. Our methodology is applied to data on prenatal methylmercury exposure and multiple outcomes in four domains measured at 9 years of age on children enrolled in the Seychelles Child Development Study. We use three different priors and found that our main conclusions were not sensitive to the choice of prior. Simulation studies examine the model performance under alternative scenarios. Our results demonstrate that a sizeable increase in power is possible.     

Identifiability of causal effects for binary variables with baseline data missing due to death

We discuss identifiability and estimation of causal effects of a treatment in subgroups defined by a covariate that is sometimes missing due to death, which is different from a problem with outcomes censored by death. Frangakis et al. (2007, Biometrics 63, 641-662) proposed an approach for estimating the causal effects under a strong monotonicity (SM) assumption. In this article, we focus on identifiability of the joint distribution of the covariate, treatment and potential outcomes, show sufficient conditions for identifiability, and relax the SM assumption to monotonicity (M) and no-interaction (NI) assumptions. We derive expectation-maximization algorithms for finding the maximum likelihood estimates of parameters of the joint distribution under different assumptions. Further we remove the M and NI assumptions, and prove that signs of the causal effects of a treatment in the subgroups are identifiable, which means that their bounds do not cover zero. We perform simulations and a sensitivity analysis to evaluate our approaches. Finally, we apply the approaches to the National Study on the Costs and Outcomes of Trauma Centers data, which are also analyzed by Frangakis et al. (2007) and Xie and Murphy (2007, Biometrics 63, 655-658).     

A Robust Method for Estimating Optimal Treatment Regimes

Summary A treatment regime is a rule that assigns a treatment, among a set of possible treatments, to a patient as a function of his/her observed characteristics, hence “personalizing” treatment to the patient. The goal is to identify the optimal treatment regime that, if followed by the entire population of patients, would lead to the best outcome on average. Given data from a clinical trial or observational study, for a single treatment decision, the optimal regime can be found by assuming a regression model for the expected outcome conditional on treatment and covariates, where, for a given set of covariates, the optimal treatment is the one that yields the most favorable expected outcome. However, treatment assignment via such a regime is suspect if the regression model is incorrectly specified. Recognizing that, even if misspecified, such a regression model defines a class of regimes, we instead consider finding the optimal regime within such a class by finding the regime that optimizes an estimator of overall population mean outcome. To take into account possible confounding in an observational study and to increase precision, we use a doubly robust augmented inverse probability weighted estimator for this purpose. Simulations and application to data from a breast cancer clinical trial demonstrate the performance of the method.     

Self-efficacy and the promotion of health for depressed single mothers

Single mothers are a vulnerable population at risk for poor mental and physical health. This paper discusses the mental and physical health of single mothers, as well as the psychosocial and socio-economic risk factors placing single mothers at risk for poor health outcomes. Some of these include, gender, income level, educational status, social support, stress and certain personality characteristics. Theoretical models with the potential to explore ways to promote health in depressed single mothers will also be presented. The paper concludes with the application of these models to primary prevention and the promotion of health for single mothers along with recommendations for future research.     

自控镇痛技术在老年患者术后康复治疗中的护理体会

目的探讨老年患者术后应用自控镇痛技术对康复治疗的临床护理。方法将304例患者随机分成两组,治疗组给予术后自控镇痛,对照组给予阿片类或吗啡类止痛,分别对镇痛效果、胃肠道恢复时间、尿潴留发生率、睡眠情绪满意率几方面进行对比。结果两组间在镇痛评分（VAS）和睡眠情绪满意率存在统计学差异（P〈0.05）;而术后胃肠道恢复时间、尿潴留发生率两组间差异无统计学意义（P〉0.05）。结论良好的自控镇痛技术能提高老年患者术后镇痛质量和睡眠情绪满意度。何丽娟,汪凤梅,余丽花     

Cistanches alleviates sevoflurane‐induced cognitive dysfunction by regulating PPAR‐γ‐dependent antioxidant and anti‐inflammatory in rats

This study aimed to investigate the protective effects and underlying mechanisms of cistanche on sevoflurane‐induced aged cognitive dysfunction rat model. Aged (24 months) male SD rats were randomly assigned to four groups: control group, sevoflurane group, control + cistanche and sevoflurane + cistanche group. Subsequently, inflammatory cytokine levels were measured by ELISA, and the cognitive dysfunction of rats was evaluated by water maze test, open‐field test and the fear conditioning test. Three days following anaesthesia, the rats were killed and hippocampus was harvested for the analysis of relative biomolecules. The oxidative stress level was indicated as nitrite and MDA concentration, along with the SOD and CAT activity. Finally, PPAR‐γ antagonist was used to explore the mechanism of cistanche in vivo. The results showed that after inhaling the sevoflurane, 24‐ but not 3‐month‐old male SD rats developed obvious cognitive impairments in the behaviour test 3 days after anaesthesia. Intraperitoneal injection of cistanche at the dose of 50 mg/kg for 3 consecutive days before anaesthesia alleviated the sevoflurane‐induced elevation of neuroinflammation levels and significantly attenuated the hippocampus‐dependent memory impairments in 24‐month‐old rats. Cistanche also reduced the oxidative stress by decreasing nitrite and MDA while increasing the SOD and CAT activity. Moreover, such treatment also inhibited the activation of microglia. In addition, we demonstrated that PPAR‐γ inhibition conversely alleviated cistanche‐induced protective effect. Taken together, we demonstrated that cistanche can exert antioxidant, anti‐inflammatory, anti‐apoptosis and anti‐activation of microglia effects on the development of sevoflurane‐induced cognitive dysfunction by activating PPAR‐γ signalling.     

不同麻醉方式分娩镇痛对产程及母婴结局的影响

目的:探讨不同麻醉方式分娩镇痛对产程及母婴结局的影响。方法:选取2016年7月至2018年7月我院收治的154例分娩镇痛产妇为研究对象,根据随机抽签原则将受试者进行分组,对照组77例产妇接受常规的静脉麻醉镇痛,研究组77例产妇接受硬膜外麻醉镇痛,比较两组产妇的产程时间、疼痛分级、母婴结局及24h泌乳情况。结果:研究组产妇的产程时间显著短于对照组(P0.05),0级及Ⅰ级疼痛的比率显著低于对照组(P0.05),Ⅱ级及Ⅲ级疼痛的比率显著高于对照组(P0.05),产妇阴道助产、中转剖宫产、尿潴留及产后出血量均显著少于对照组(P0.05),新生儿宫内窘迫及窒息的发生率显著低于对照组(P0.05)。两组新生儿出生后1 min、5 min及10 min的Apgar评分比较无统计学差异(P0.05),研究组产妇产后24h有效泌乳率显著高于对照组(P0.05)。结论:硬膜外麻醉镇痛可有效缩短产程时间,减轻疼痛,改善母婴结局,促进产后泌乳。     

Influence of ABCB1 genetic variants in breast cancer treatment outcomes

BackgroundTransportation of anticancer drugs such as anthracyclines across the membrane is regulated by P-glycoprotein encoded by the human multidrug resistance gene 1 (ABCB1). Polymorphisms in the ABCB1 gene (1236C > T, 2677G > T/A, 3435C > T) have been found to be associated with intrinsic and acquired cross resistance to these anticancer drugs. Therefore, the aim of this study is to evaluate the influence of ABCB1 gene polymorphisms in breast cancer treatment outcomes in terms of response and toxicity.MethodResponse to neo-adjuvant chemotherapy was evaluated in 100 patients while grade 2–4 toxicity was followed in 207 patients, who had undergone FEC/FAC chemotherapy. Genotyping for ABCB1 polymorphisms was done by PCR-RFLP. Chi square and logistic regression analyses were used to calculate Odd's ratio using SPSS ver 17.0. A meta analysis was also performed using Comprehensive Meta Analysis Ver 2.ResultsIn response evaluation, 1236C > T polymorphism was significantly associated with treatment response for CT genotype [OR = 5.17(1.3–20.2), P = 0.018] and in dominant model (CC vs CT + TT) [OR = 4.63(1.25–17.0), P = 0.021]. In the toxicity group, the T allele of 1236C>T was associated with grade 2–4 tocxicity [OR 1.48(1.00–2.20), P = 0.049] and the association was also significant in the recessive model [OR 1.88(1.05–3.39), P = 0.033]. For other two SNPs 2677G>T/A and 3435C>T no association was seen with either treatment response or grade 2–4 toxicity. In meta analysis, no overall association was found.ConclusionIn our study, significant association was seen for ABCB1 1236C>T polymorphism with treatment response. The meta analysis did not show overall association with treatment outcomes.