以HR，HigherCI，LowerCI為例，表格中要有這三列

先匯入表格lq_2

正態化資料分佈

lnhr <- log(lq_2[,"HR"])
lnuci <- log(lq_2[,"HigherCI"])
lnlci <- log(lq_2[,"LowerCI"])
selnhr <- (lnuci-lnlci)/(2*1.96)

meta分析

MetaHR = metagen(TE = lnhr$HR,
                 seTE = selnhr$HigherCI,
                 sm = "HR",
                 data = lq_2,
                 # studlab = paste(lq_1$Clinic_Pt_Im,lq_1$P.value,sep = " P:"),
                 studlab = lq_2$`Clinic-Pt-Rad`,
                 random = T,
                 #backtransf = T
                 )
 

影象風格設定

settings.meta('JAMA')
settings.meta('RevMan5')
settings.meta('meta4')

settings.meta('reset') # 重置風格

繪製森林圖(經測試選擇某種風格後修改森林圖引數會無效)

具體引數可用 ？forest 查詢 按照自己的需求調整

forest(MetaHR,
       # xlab = "hahahaha",
       label.left = "C-index = 0.840                                                                        ",
       #label.right = " i am right",
       colgap.studlab = "2cm",
       #colgap.forest.left = "0.2cm",
       colgap.forest.right = "0.5cm",
       colgap.right = "1cm",
       random = FALSE, 
       leftlabs = c("Clinic_Pt_Rad", "HR"),
       leftcols = c("studlab","HR"),
       rightcols = c("ci","P.value"),
       )
 

效果圖

參考視訊Meta分析自己用-森林圖 R語言（高分SCI繪圖模仿）03