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NMA(网状meta分析)stata简易教程(1)

在上次交流的过程中,有很多童鞋问到了,stataNMA的作图过程和数据格式,这些都是最关注的问题。现结合stata作图教程,展示一下基本过程。

1、深入学习,可百度如下内容:

Graphs to Enhance Understanding & Improve  Interpretability of the Evidence from Network Meta-Analysis 用绘图方式来了解Network Meta-Analysis

提高认识&增强可解释性

example datasets from 实例数据来自以下三篇文献

Cipriani A, Barbui C, Salanti G, Rendell J, Brown R, Stockton S, et al. Comparative efficacy and

acceptability of antimanic drugs in acute mania: a multiple-treatments meta-analysis. Lancet

2011, 378: 1306-1315. (12种新型抗抑郁药疗效及依从性荟萃分析)

Trikalinos TA, Alsheikh-Ali AA, Tatsioni A, Nallamothu BK, Kent DM. Percutaneous coronary

interventions for non-acute coronary artery disease: a quantitative 20-year synopsis and a  

network meta-analysis. Lancet 2009, 373: 911-918. 

Singh JA, Christensen R, Wells GA, Suarez-Almazor ME, Buchbinder R, Lopez-Olivo MA, et

A network meta-analysis of randomized controlled trials of biologics for rheumatoid arthritis:

a Cochrane overview. CMAJ 2009, 181: 787-796. 

 

2、数据格式

下面是猴哥的某篇文章(在qq群共享文件中)的数据格式(原版),做stata之前,整理了三种格式。童鞋们可以参照一下。

2.1 Gemtc长数据格式 gemtcdata  longdata

 

2.2 stata mvmeta数据格式  mvmetadata

 

2.3 stata配对数据格式 pairwisedata

 

 

3、Installation of the STATA routines 安装STATA

For the routines that produce the presented graphs:

net from http://www.mtm.uoi.gr

net install network_graphs, replace

To see the help files for any routine type help and the name of the command. For example:

. help mvmeta

. help networkplot

 

4 、示例

Producing the network plot 制作网状图—用的是配对的数据pairwise

Open the dataset acute mania efficacy pairwise.dta:

use "acute mania efficacy pairwise.dta", replace

This network compares the efficacy of 14 pharmacological interventions for acute mania. It

includes 47 studies (36 two-arm and 11 three-arm trials) that provide in total 69 pairwise comparisons (equal to the number of observations).

这个network meta-analysis对比了治疗急性躁狂的14种药物干预措施。纳入了47个研究(36个双臂研究和11个三臂研究),提供了69对比较。

在研究中看出,1-36为双臂,47后为三臂研究

 

 

 

 

Open the data editor window:

#输入

Edit

The variable study contains the ID number of each study. The variables t1 and t2, r1 and r2, n1 and n2 contain the name of the treatments (abbreviated), the number of events and the total number of patients in arms 1 and 2. For each multi-arm study with T number of arms there are observations (with the same study ID) equal to the number of pairwise comparisons that this study provides. The variables logOR and selogOR contain the log-odds ratio and its standard error for the comparison t1 vs. t2. Finally, the variable allocation_concealment contains the judgments for the risk of bias regarding the appropriate conduct of allocation concealment (U=unclear, L=low).

变量study:研究的ID号。

变量t1:干预措施1;变量t2:干预措施2。

变量r1:事件发生数1;变量r2:事件发生数2。 R表示事件发生数

变量n1:病人总数1;变量n2:病人总数2。

对于每一个研究有T个观察结果,T=T×(T-1)/2,即双臂研究有2组对比,三臂研究有3组对比,四臂研究有6组对比。

变量logOR:t1 vs. t2的对数差异比。

变量selogOR:logOR的标准误。

变量allocation_concealment:根据分配隐藏得到的偏倚风险的判断(U=unclear, L=low)。

 

##预处理

use "F:\【Network Meta-Analysis - 网状meta分析】使用STATA软件绘图\example_datasets\acute mania efficacy pairwise.dta"

 

 

 

 

 

//我们开始第一张图:g1网状图

networkplot t1 t2

 

//很简单,有没有?

 

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本文由 GCBI学院 作者:乞嘚咙咚呛咚呛 发表,转载请注明来源!

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