直接効果・間接効果の推定および未測定の交絡に対する感度解析

要旨あり疫学研究のデザインとデータ解析：最近の理論的展開と実践研究詳

Simultaneous Modeling of Disease Screening and Severity Prediction: A Multi-task and Sparse Regularization Approach

Disease prediction is one of the central problems in biostatistical research. Some biomarkers are not only helpful in diagnosing and screening diseases but also associated with the severity of the diseases. It should be helpful to construct a prediction model that can estimate severity at the diagnosis or screening stage from perspectives such as treatment prioritization. We focus on solving the combined tasks of screening and severity prediction, considering a combined response variable such as \{healthy, mild, intermediate, severe\}. This type of response variable is ordinal, but since the two tasks do not necessarily share the same statistical structure, the conventional cumulative logit model (CLM) may not be suitable. To handle the composite ordinal response, we propose the Multi-task Cumulative Logit Model (MtCLM) with structural sparse regularization. This model is sufficiently flexible that can fit the different structures of the two tasks and capture their shared structure of them. In addition, MtCLM is valid as a stochastic model in the entire predictor space, unlike another conventional and flexible model, the non-parallel cumulative logit model (NPCLM). We conduct simulation experiments and real data analysis to illustrate the prediction performance and interpretability

Sarcopenia, intramuscular fat deposition, and visceral adiposity independently predict the outcomes of hepatocellular carcinoma

Background & AimsObesity defined by body mass index (BMI) significantly increases the risk of hepatocellular carcinoma (HCC). In contrast, not only obesity but also underweight is associated with poor prognosis in patients with HCC. Differences in body composition rather than BMI were suggested to be true determinants of prognosis. However, this hypothesis has not been demonstrated conclusively.MethodsWe measured skeletal muscle index (SMI), mean muscle attenuation (MA), visceral adipose tissue index, subcutaneous adipose tissue index, and visceral to subcutaneous adipose tissue area ratios (VSR) via computed tomography in a large-scale retrospective cohort of 1257 patients with different stages of HCC, and comprehensively analyzed the impact of body composition on the prognoses.ResultsAmong five body composition components, low SMI (called sarcopenia), low MA (called intramuscular fat [IMF] deposition), and high VSR (called visceral adiposity) were significantly associated with mortality, independently of cancer stage or Child-Pugh class. A multivariate analysis revealed that sarcopenia (hazard ratio [HR], 1.52; 95% confidence interval [CI], 1.18–1.96; p=0.001), IMF deposition (HR, 1.34; 95% CI, 1.05–1.71; p=0.020), and visceral adiposity (HR, 1.35; 95% CI, 1.09–1.66; p=0.005) but not BMI were significant predictors of survival. The prevalence of poor prognostic body composition components was significantly higher in underweight and obese patients than in normal weight patients.ConclusionsSarcopenia, IMF deposition, and visceral adiposity independently predict mortality in patients with HCC. Body composition rather than BMI is a major determinant of prognosis in patients with HCC

Efficacy of glutathione for the treatment of nonalcoholic fatty liver disease: an open-label, single-arm, multicenter, pilot study

Background: Glutathione plays crucial roles in the detoxification and antioxidant systems of cells and has been used to treat acute poisoning and chronic liver diseases by intravenous injection. This is a first study examining the therapeutic effects of oral administration of glutathione in patients with nonalcoholic fatty liver disease (NAFLD). Methods: The study was an open label, single arm, multicenter, pilot trial. Thirty-four NAFLD patients diagnosed using ultrasonography were prospectively evaluated. All patients first underwent intervention to improve their lifestyle habits (diet and exercise) for 3 months, followed by treatment with glutathione (300 mg/day) for 4 months. We evaluated their clinical parameters before and after glutathione treatment. We also quantified liver fat and fibrosis using vibration-controlled transient elastography. The primary outcome of the study was the change in alanine aminotransferase (ALT) levels. Results: Twenty-nine patients finished the protocol. ALT levels significantly decreased following treatment with glutathione for 4 months. In addition, triglycerides, non-esterified fatty acids, and ferritin levels also decreased with glutathione treatment. Following dichotomization of ALT responders based on a median 12.9% decrease from baseline, we found that ALT responders were younger in age and did not have severe diabetes compared with ALT non-responders. The controlled attenuation parameter also decreased in ALT responders. Conclusions: This pilot study demonstrates the potential therapeutic effects of oral administration of glutathione in practical dose for patients with NAFLD. Large-scale clinical trials are needed to verify its efficacy. Trial registration: UMIN000011118 (date of registration: July 4, 2013)

Exposure to PM2.5 and Lung Function Growth in Pre- and Early-Adolescent Schoolchildren: A Longitudinal Study Involving Repeated Lung Function Measurements in Japan.

Rationale: Epidemiological evidence indicates that ambient exposure to particulate matter ⩽2.5 μm in aerodynamic diameter (PM2.5) has adverse effects on lung function growth in children, but it is not actually clear whether exposure to low-level PM2.5 results in long-term decrements in lung function growth in pre- to early-adolescent schoolchildren. Objectives: To examine long-term effects of PM2.5 within the 4-year average concentration range of 10-19 μg/m3 on lung function growth with repeated measurements of lung function tests. Methods: Longitudinal analysis of 6,233 lung function measurements in 1,466 participants aged 8-12 years from 16 school communities in 10 cities around Japan, covering a broad area of the country to represent concentration ranges of PM2.5, was done with a multilevel linear regression model. Forced expiratory volume in 1 second, forced vital capacity (FVC), and maximal expiratory flow at 50% of FVC were used as lung function indicators to examine the effects of 10-μg/m3 increases in the PM2.5 concentration on relative growth per each 10-cm increase in height. Results: The overall annual mean PM2.5 level was 13.5 μg/m3 (range, 10.4-19.0 μg/m3). We found no association between any of the lung function growth indicators and increases in PM2.5 levels in children of either sex, even after controlling for potential confounders. Analysis with two-pollutant models with O3 or NO2 did not change the null results. Conclusions: This nationwide longitudinal study suggests that concurrent, long-term exposure to PM2.5 at concentrations ranging from 10.4 to 19.0 μg/m3 has little effect on lung function growth in preadolescent boys or pre- to early-adolescent girls

Causal mediation analysis with multiple causally non-ordered mediators

In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries

Using a Marginal Structural Model to Design a Theory-Based Mass Media Campaign.

The essential first step in the development of mass media health campaigns is to identify specific beliefs of the target audience. The challenge is to prioritize suitable beliefs derived from behavioral theory. The purpose of this study was to identify suitable beliefs to target in a mass media campaign to change behavior using a new method to estimate the possible effect size of a small set of beliefs.Data were drawn from the 2010 Japanese Young Female Smoker Survey (n = 500), conducted by the Japanese Ministry of Health, Labor and Welfare. Survey measures included intention to quit smoking, psychological beliefs (attitude, norms, and perceived control) based on the theory of planned behavior and socioeconomic status (age, education, household income, and marital status). To identify suitable candidate beliefs for a mass media health campaign, we estimated the possible effect size required to change the intention to quit smoking among the population of young Japanese women using the population attributable fraction from a marginal structural model.Thirteen percent of study participants intended to quit smoking. The marginal structural model estimated a population attributable fraction of 47 psychological beliefs (21 attitudes, 6 norms, and 19 perceived controls) after controlling for socioeconomic status. The belief, "I could quit smoking if my husband or significant other recommended it" suggested a promising target for a mass media campaign (population attributable fraction = 0.12, 95% CI = 0.02-0.23). Messages targeting this belief could possibly improve intention rates by up to 12% among this population. The analysis also suggested the potential for regulatory action.This study proposed a method by which campaign planners can develop theory-based mass communication strategies to change health behaviors at the population level. This method might contribute to improving the quality of future mass health communication strategies and further research is needed