Alcances de la aleatorización mendeliana para el control de confusores no observables en epidemiología

The Mendelian randomization is an epidemiologic method proposed to control for spurious associations in observational studies. These associations are commonly caused by confusion derived from social, environmental, and behavioral factors, which can be difficult to measure. Mendelian randomization is based on the selection of genetic variants that are used as instrumental variables that influence exposure patterns or are associated with an intermediate phenotype of the disease. The present work aims to discuss how to select the appropriate genetic variants as instrumental variables and to present methodological tools to deal with the limitations of this epidemiological method. The use of instrumental variables for modifiable exposures has the potential to mitigate the effects of common limitations, such as confusion, when robust genetic variants are chosen as instrumental variables.     

Biomarker Validation: Common Data Analysis Concerns

Biomarker validation, like any other confirmatory process based on statistical methodology, must discern associations that occur by chance from those reflecting true biological relationships. Validity of a biomarker is established by authenticating its correlation with clinical outcome. Validated biomarkers can lead to targeted therapy, improve clinical diagnosis, and serve as useful prognostic and predictive factors of clinical outcome. Statistical concerns such as confounding and multiplicity are common in biomarker validation studies. This article discusses four major areas of concern in the biomarker validation process and some of the proposed solutions. Because present‐day statistical packages enable the researcher to address these common concerns, the purpose of this discussion is to raise awareness of these statistical issues in the hope of improving the reproducibility of validation study findings.     

Use of a case-mix approach to study the trends in the incidence of second primary cancers

Purpose

To analyze trends in second primary cancer (SPC) incidence by using a case-mix approach to standardize on first cancer site distribution.

Standardization for Subgroup Analysis in Randomized Controlled Trials

Randomized controlled trials (RCTs) emphasize the average or overall effect of a treatment (ATE) on the primary endpoint. Even though the ATE provides the best summary of treatment efficacy, it is of critical importance to know whether the treatment is similarly efficacious in important, predefined subgroups. This is why the RCTs, in addition to the ATE, also present the results of subgroup analysis for preestablished subgroups. Typically, these are marginal subgroup analysis in the sense that treatment effects are estimated in mutually exclusive subgroups defined by only one baseline characteristic at a time (e.g., men versus women, young versus old). Forest plot is a popular graphical approach for displaying the results of subgroup analysis. These plots were originally used in meta-analysis for displaying the treatment effects from independent studies. Treatment effect estimates of different marginal subgroups are, however, not independent. Correlation between the subgrouping variables should be addressed for proper interpretation of forest plots, especially in large effectiveness trials where one of the goals is to address concerns about the generalizability of findings to various populations. Failure to account for the correlation between the subgrouping variables can result in misleading (confounded) interpretations of subgroup effects. Here we present an approach called standardization, a commonly used technique in epidemiology, that allows for valid comparison of subgroup effects depicted in a forest plot. We present simulations results and a subgroup analysis from parallel-group, placebo-controlled randomized trials of antibiotics for acute otitis media.     

低危险度流行病学和好的流行病学研究方法

本文对低危险度的流行病学研究方法上存在的困难进行了讨论，如确定暴露估计时可能犯的错误，特别是与疾病有关的几种因子的剂量描述。对如何建立好的流行病学研究方法也进行了讨论。研究者必需注意到他的解释将对公共卫生实践产生重要影响，因此对数据的解释应持慎重态度     

On the relationship between nausea and vomiting in patients undergoing chemotherapy

In comparative trials on antiemetic efficacy of different regimens, the positive correlation between the probabilities of vomiting and of nausea could hide some confounding effect. Our work seeks to detect such effects. The data from two large studies on prevention of cisplatin-induced emesis were re-analyzed using two multi-factorial logistic models. The first study compared ondansetron + dexamethasone (Ond + Dex) with metoclopramide + dexamethasone + diphenhydramine (Mtc + Dex + Dip), the second compared Mtc + Dex + Dip with Mtc + prednisolone. A group of 267 patients in the first study and 343 in the second, all evaluable for clinical efficacy, were followed for three subsequent cycles of chemotherapy. The antiemetic regimen administered and the complete protection from acute vomiting and nausea were recorded. In the first study (cycle 1), after adjustment for the presence/absence of vomiting, the two therapies were no longer found significantly different on complete protection from nausea: the greater efficacy of Ond + Dex in preventing nausea was due to a confounding effect. Instead, in the second study, the greater efficacy of Mtc + Dex + Dip in preventing both nausea and vomiting was confirmed. The results indicate that, when a correlation between two responses is detected, multifactorial analyses should be performed to identify the possible presence of some confounding effect. The proof that the presence/absence of vomiting is a confounding factor for the relationship between the different efficacy of the two antiemetic regimens for complete protection from nausea, highlighting the same efficacy of the two therapies in preventing nausea, supports the hypothesis of the existence of two kinds of nausea, one independent of vomiting, the other concomitant with it.     

疾病家庭聚集性研究中对照的选择及其影响

本文讨论了疾病家庭聚集性研究中不同对照的特点。揭示在没有混杂因素作用的情况下，两种对照的任一种都可以通过与病例组比较，对疾病的家庭聚集性作出检验。但用指示对照有关的个体组成的对照具有较大的检验效能。若存在混杂因素，需采用分层分析方法或者标准化法对其进行控制，然后通过病例组与对照组的比较，对疾病的家庭聚集性作出推断。     

Use of folic acid supplementation and risk for dizygotic twinning

BACKGROUND: An increase in dizygotic twinning rate after folic acid supplementation has previously been described, but in a recent study from China, no such effect was seen. AIMS: To further investigate the association between use of folic acid supplement and dizygotic twinning. STUDY DESIGN: Using the Swedish Medical Birth Registry, the rate of dizygotic twinning among infants of women who reported the use of folic acid was studied, taking a number of confounders into consideration. Comparisons were made with all women recorded in the register. OUTCOME MEASURE: Unlike-sexed twin pairs were used as representatives of dizygotic twinning. RESULTS: A number of confounders for the association between folic acid use and twinning were identified and taken into consideration. Women who were immigrants (who used less folic acid and had slightly lower twinning rates than women born in Sweden) and women who reported subfertility problems or treatment for subfertility (who had a high use of folic acid and a high twinning rate) were excluded, and adjustment was then made for year of birth, maternal age, parity, and smoking in early pregnancy. Folic acid use and twinning risk increased with maternal age and decreased with parity. Smokers used less folic acid than nonsmokers. Concomitant use of other drugs was no important confounder except for those used at subfertility. The odds ratio (OR) for dizygotic twinning after folic acid supplementation was then 1.71 (95%CI=1.21-2.42) and for the years 2000-2001 even 2.09 (95%CI=1.39-3.12). CONCLUSION: There is an increase in twinning rate after folic acid supplementation in a Western population which should be taken into consideration when folic acid supplementation or food fortification is recommended.     

广东阳江高本底地区居民癌症及其相关因素研究主要结果

目的综合分析阳江高本底地区居民癌症及其相关因素研究结果,讨论该研究的学术意义.方法合并分析19972～1986年和1987～1998年癌症死亡观察资料,同时分析混淆因素、人群可比性、人体免疫功能研究等资料.结果对环境和宿主的可能致癌与致突变因素进行分类研究表明两地区基本符合"齐同对比"原则,两人群是可比的;高本底地区居民白细胞介素-2分泌细胞(IL-2SC)水平明显高于对照;根据1979～1998年125079人共累积观察1992 940人年的癌症死亡率分析资料,整个高本底地区全癌死亡的相对危险为1.00(95%CI,0.89～1.14),与对照地区差异没有显著性,不同剂量组及其部位别的癌症死亡相对危险均未发现与剂量呈一致性变化趋势;全部实体癌的超额相对危险系数(ERR/Sv),在整个高本底地区估算为-0.06(95%CI,-0.60～0.67).结论未发现高本底地区居民癌症死亡增加,也未发现高本底地区有辐射相关的部位别癌症死亡的增加,相反,存在高本底辐射刺激免疫功能增强的趋势.     

Methods to assess intended effects of drug treatment in observational studies are reviewed

BACKGROUND AND OBJECTIVE: To review methods that seek to adjust for confounding in observational studies when assessing intended drug effects. METHODS: We reviewed the statistical, economical and medical literature on the development, comparison and use of methods adjusting for confounding. RESULTS: In addition to standard statistical techniques of (logistic) regression and Cox proportional hazards regression, alternative methods have been proposed to adjust for confounding in observational studies. A first group of methods focus on the main problem of nonrandomization by balancing treatment groups on observed covariates: selection, matching, stratification, multivariate confounder score, and propensity score methods, of which the latter can be combined with stratification or various matching methods. Another group of methods look for variables to be used like randomization in order to adjust also for unobserved covariates: instrumental variable methods, two-stage least squares, and grouped-treatment approach. Identifying these variables is difficult, however, and assumptions are strong. Sensitivity analyses are useful tools in assessing the robustness and plausibility of the estimated treatment effects to variations in assumptions about unmeasured confounders. CONCLUSION: In most studies regression-like techniques are routinely used for adjustment for confounding, although alternative methods are available. More complete empirical evaluations comparing these methods in different situations are needed.