基于线性视觉模拟标尺的评审方法在科研课题立项评审中的应用及其对照分析

北京大学人民医院对医院研究与发展基金实施全过程管理,从课题申报、立项评审、中期评估、结题都有严格的管理规定.为了保证科研课题立项评审的公正、公平,北京大学人民医院建立了基于线性视觉模拟标尺评分方法的评审方法,并应用于医院研究与发展基金的课题立项评审.从评审结果的对照分析表明,基于线性视觉模拟标尺的评审方法具有与传统的Liken相同的评审可信度,可应用于课题立项评审;与传统的Liken量表评审方法相比,基于线性视觉模拟标尺的评审方法的评审区分度更好.     

The role of IL-6, IL-8 and MCP-1 and their promoter polymorphisms IL-6 -174GC, IL-8 -251AT and MCP-1 -2518AG in the risk of venous thromboembolism: a case-control study

Introduction

Cytokines increased the risk of venous thromboembolism (VTE) in some case-control studies, but not in a prospective study. Data concerning the role of cytokines in the risk of VTE are limited. We examined in a case-control study the association of VTE and levels of interleukin (IL)-6, IL-8 and monocyte chemotactic protein-1 (MCP-1) and assessed whether promoter polymorphisms (IL-6 -174GC, IL-8 -251AT, MCP-1 -2518AG) would affect the thrombotic risk and cytokine levels.

Materials and methods

The study included 119 patients (94 women) with a first event of VTE aged between 18-60 years, and 126 healthy controls (100 women) matched for age (± 5 years). Blood was collected > 7 months after the thrombotic event. Odds ratios (ORs) were calculated per increase of cytokines levels by 1 pg/mL.

Results

ORs adjusted for age and sex were 1.520 [95% Confidence Interval (CI) 1.177 - 1.962] for IL-6, 1.095 (95% CI 1.002 - 1.196) for IL-8 and 1.000 (0.988 - 1.012) for MCP-1. With additional adjustment for ethnic composition, body mass index (BMI) and high sensitive C-reactive protein (hs-CRP), risk estimates remained significant for IL-6 and became of borderline statistical significance for IL-8. Polymorphisms did not influence the thrombotic risk and the cytokine levels in study participants.

Conclusion

VTE was associated with IL-6 and IL-8 levels, and for IL-6 this association was independent of BMI and hs-CRP. Thus far, a causal relationship between inflammation and VTE remains to be clarified and more prospective data are warranted.     

相关性和一致性：这对相仿概念和测量方法的回顾与阐明

概述：一致性(agreement)和相关性(correlation)是两个广泛使用的概念,用来评估变量之间的关联。虽然二者相似且相关,但是它们代表关联完全不同的概念。评估变量之间的一致性假设变量测量的是相同的结构,而在变量测量完全不同的结构时也可以评估它们之间的相关性。这种概念上的差异就要求使用不同的统计方法,并且当评估一致性或相关性时,统计方法根据数据的分布和研究者的兴趣可能会有所不同。例如, Pearson相关性,作为评估连续变量之间相关性的一种普遍测量方法,只有用于符合线性关系的变量时才能提供有用的信息;当用于不符合线性关系的变量时就无法提供准确信息甚至会产生误导。同样地,内部相关性,作为一种评估连续变量之间一致性的常用方法,如果一致性不好的实质正好是研究兴趣所在,那么该测量就不能为研究者提供充分的信息。本报告回顾了一致性和相关性的概念,并讨论了几种常用方法在应用中的差异。