使用stata绘制元分析forest plot

虽然R里面的survminer提供了ggforest函数来创建一个关于HR的森林图，但是它貌似只能应用于单个模型的分析，其实森林图的使用在元分析非常普遍。在我最近阅读的新英格兰杂志和柳叶刀文章中广泛使用了forest图形，而且排版惊人一致！我现在终于知道它们都用是用的stata软件绘制，虽然我不是很懂这个流行的统计分析软件，但是查找下资料画个图还是没问题的。

下面用例子演示：

在命令行输入数据：

clear
input coef lci uci str20 group str20 subpopulation
.1266349 -.3146492 .5679189 Group1 Sub1
-.3509529 -1.023146 .3212402 Group2 Sub1
.08614 -.2777374 .4500174 Group1 Sub2
-.0951817 -.358211 .1678475 Group2 Sub2
-.0707719 -.4005753 .2590315 Group1 Sub3
-.1216107 -.3963165 .1530952 Group2 Sub3
.1412438 -.3248311 .6073186 Group1 Sub4
-.260193 -.5850677 .0646817 Group2 Sub4
-.1227866 -.5573016 .3117283 Group1 Sub5
-.0232415 -.2844573 .2379743 Group2 Sub5
end

输入绘图命令：

label define refsubpop 1 "Sub3" 2 "Sub1" 3 "Sub2" 4 "Sub4" 5 "Sub5"
encode subpopulation, gen(subpop)
label values subpop refsubpop
codebook subpop
metan coef lci uci, lcols(subpop) by(group)

效果：

森林图

改成Hazard Ratio

HR

代码：

clear
input coef lci uci str20 group str20 subpopulation
.1266349 -.3146492 .5679189 Group1 Sub1
-.3509529 -1.023146 .3212402 Group2 Sub1
.08614 -.2777374 .4500174 Group1 Sub2
-.0951817 -.358211 .1678475 Group2 Sub2
-.0707719 -.4005753 .2590315 Group1 Sub3
-.1216107 -.3963165 .1530952 Group2 Sub3
.1412438 -.3248311 .6073186 Group1 Sub4
-.260193 -.5850677 .0646817 Group2 Sub4
-.1227866 -.5573016 .3117283 Group1 Sub5
-.0232415 -.2844573 .2379743 Group2 Sub5
end

label define refsubpop 1 "Sub3" 2 "Sub1" 3 "Sub2" 4 "Sub4" 5 "Sub5"
encode subpopulation, gen(subpop)
label values subpop refsubpop
codebook subpop
metan coef lci uci, effect(Hazard Ratio) lcols(subpop) by(group)

参考：

https://www.statalist.org/forums/forum/general-stata-discussion/general/1374722-how-to-stratify-results-in-a-forest-plot-by-two-variables
https://stats.stackexchange.com/questions/15025/how-to-combine-two-hazard-ratios-from-the-study-for-a-meta-analysis