R使用netmeta程序包实现二分类数据的频率学网状meta分析

该研究检索了Cochrane对照试验中心注册,CINAHLEmbaseLILACS数据库MEDLINEMEDLINEIn-ProcessPsycINFO监管机构网站,以及从一开始就发布和未发表的双盲随机对照试验的国际注册2016年1月8日。

研究包括21种抗抑郁药的安慰剂对照和头对头试验,用于成人(≥18岁和两性)的急性治疗,根据标准操作标准诊断为严重抑郁症。

主要结果是疗效(反应率)和可接受性(由于任何原因导致的治疗中断)。我们使用具有随机效应的成对和网络荟萃分析估计概要比值比(OR)。

数据来源于该文章提供的数据,https://data.mendeley.com/datasets/83rthbp8ys/2

1 程序包安装及数据加载

首先是下载和加载netmeta程序包。

##install.packages("netmeta")
library(netmeta)eff <- read.csv("full-efficacy.csv", header = TRUE, stringsAsFactors = FALSE)acc <- read.csv("full-acceptability.csv", header = TRUE,stringsAsFactors = FALSE)

2 模型构建(netmeta)

模型构建首先使用pairwise函数对数据处理其次鞭尸使用核心函数netmeta函数进行模型分析,可以分别选择fixedrandom两类模型。

deff <- pairwise(treat = t, n, event = r, data = eff, studlab = id, sm = "OR")
dacc <- pairwise(treat = t,n, event = r, data = acc, studlab = id,sm = "OR")
e.netmeta <-netmeta(deff, comb.fixed = FALSE, comb.random = TRUE)
e.netmeta
a.netmeta <-netmeta(dacc, comb.fixed = FALSE, comb.random = TRUE)
a.netmeta 

模型结果如下所示(仅展示e.netmeta):

## Number of studies: k = 433
## Number of pairwise comparisons: m = 555
## Number of observations: o = 103155
## Number of treatments: n = 22
## Number of designs: d = 117
## 
## Random effects model
## 
## Treatment estimate (sm = 'OR', comparison: other treatments vs 'agomelatine'):
##                     OR           95%-CI     z  p-value
## agomelatine          .                .     .        .
## amitriptyline   1.2819 [1.0792; 1.5226]  2.83   0.0047
## bupropion       0.9461 [0.7759; 1.1536] -0.55   0.5841
## citalopram      0.9289 [0.7753; 1.1130] -0.80   0.4239
## clomipramine    0.9061 [0.7092; 1.1577] -0.79   0.4304
## desvenlafaxine  0.9078 [0.7258; 1.1355] -0.85   0.3969
## duloxetine      1.1242 [0.9537; 1.3252]  1.40   0.1629
## escitalopram    1.0180 [0.8664; 1.1963]  0.22   0.8281
## fluoxetine      0.9246 [0.8021; 1.0660] -1.08   0.2803
## fluvoxamine     1.0197 [0.8218; 1.2653]  0.18   0.8593
## levomilnacipran 0.9716 [0.7343; 1.2857] -0.20   0.8404
## milnacipran     1.0531 [0.8032; 1.3808]  0.37   0.7082
## mirtazapine     1.1393 [0.9415; 1.3787]  1.34   0.1802
## nefazodone      1.0155 [0.7763; 1.3284]  0.11   0.9109
## paroxetine      1.0562 [0.9170; 1.2165]  0.76   0.4482
## placebo         0.6118 [0.5373; 0.6967] -7.41 < 0.0001
## reboxetine      0.8301 [0.6729; 1.0240] -1.74   0.0821
## sertraline      1.0080 [0.8516; 1.1932]  0.09   0.9259
## trazodone       0.9050 [0.7191; 1.1389] -0.85   0.3947
## venlafaxine     1.0800 [0.9256; 1.2600]  0.98   0.3282
## vilazodone      0.9636 [0.7475; 1.2421] -0.29   0.7746
## vortioxetine    1.0130 [0.8384; 1.2239]  0.13   0.8938
## 
## Quantifying heterogeneity / inconsistency:
## tau^2 = 0.0426; tau = 0.2063; I^2 = 34.1% [26.1%; 41.2%]
## 
## Tests of heterogeneity (within designs) and inconsistency (between designs):
##                      Q d.f.  p-value
## Total           717.35  473 < 0.0001
## Within designs  499.41  347 < 0.0001
## Between designs 217.95  126 < 0.0001
 

3 网络证据图(network plot)

网状证据图是用来表示各种干预措施之间关系的最直观的可视化,是网状meta分析的标配,核心函数为netgraph

  • 网状meta分析的核心结果之一

  • 节点:干预措施的样本量

  • 线条:干预措施头对头试验,粗细代表试验数

##有效性  efficacy
netgraph(e.netmeta,start ="circle", cex = 1, col = "black", plastic = FALSE, points = TRUE,col.points = "steelblue", cex.points =15*sqrt(n.trts/max(n.trts)),thickness = "number.of.studies", lwd.max = 12, lwd.min = 1, multiarm = F)

图片

netgraph(a.netmeta, start ="circle", cex = 0.7, col = "black", plastic = F, points = TRUE, col.points = "darkred",cex.points =15*sqrt(n.trts/max(n.trts)), thickness = "number.of.studies",lwd.max = 12, lwd.min = 1, multiarm = FALSE)

图片

4 森林图(forest plot)

森林图是meta分析的标配,在网状meta中也是一样的,如图所示,森林图给出了各干预措施比较的效应量及95%可信区间,当然,也给出了预测区间。

主要使用forest函数实现。

forest(e.netmeta, ref = "placebo", pooled = "random", digits = 2, col.square = "steelblue",smlab = "Random effects model", label.left = "Favors citalopram",label.right = "Favors the other", leftlabs = "Efficacy", drop = TRUE,sortvar = -TE)

图片

forest(a.netmeta, ref = "placebo", pooled = "random", digits = 2, col.square = "darkred",xlim = c(2, 0.5),smlab = "Random effects model", label.left = "Favors the other",label.right = "Favors citalopram", leftlabs = "Acceptability", drop = T, sortvar = TE)

图片

6 两两比较赛联表(league)

赛联表为网状meta两两比较结果,使用netleague函数实现。

league <- netleague(e.netmeta, a.netmeta, backtransf = TRUE, direct = FALSE, fixed = FALSE, digits =2, bracket = "(",separator = " to ")
league
agomelatineamitriptylinebupropioncitalopramclomipraminedesvenlafaxineduloxetineescitalopramfluoxetinefluvoxaminelevomilnacipranmilnacipranmirtazapinenefazodoneparoxetineplaceboreboxetinesertralinetrazodonevenlafaxinevilazodonevortioxetine
agomelatine0.89 (0.73 to 1.07)0.87 (0.70 to 1.09)0.89 (0.72 to 1.10)0.65 (0.48 to 0.86)0.78 (0.61 to 1.01)0.78 (0.65 to 0.93)0.93 (0.77 to 1.12)0.95 (0.81 to 1.12)0.76 (0.60 to 0.96)0.71 (0.53 to 0.94)0.88 (0.65 to 1.19)0.85 (0.69 to 1.05)0.92 (0.69 to 1.22)0.88 (0.76 to 1.03)0.84 (0.73 to 0.97)0.72 (0.57 to 0.91)0.88 (0.73 to 1.06)0.74 (0.58 to 0.96)0.82 (0.69 to 0.97)0.75 (0.57 to 1.00)0.84 (0.67 to 1.03)
0.78 (0.66 to 0.93)amitriptyline0.99 (0.80 to 1.21)1.00 (0.82 to 1.22)0.73 (0.55 to 0.96)0.88 (0.69 to 1.13)0.87 (0.74 to 1.04)1.05 (0.88 to 1.24)1.07 (0.93 to 1.24)0.86 (0.70 to 1.06)0.80 (0.60 to 1.05)0.99 (0.75 to 1.32)0.96 (0.79 to 1.16)1.03 (0.78 to 1.37)1.00 (0.87 to 1.14)0.95 (0.83 to 1.08)0.81 (0.65 to 1.01)0.99 (0.84 to 1.16)0.84 (0.66 to 1.06)0.92 (0.78 to 1.08)0.85 (0.64 to 1.12)0.94 (0.77 to 1.15)
1.06 (0.87 to 1.29)1.35 (1.12 to 1.64)bupropion1.02 (0.81 to 1.28)0.74 (0.55 to 1.00)0.90 (0.69 to 1.17)0.89 (0.72 to 1.09)1.06 (0.87 to 1.30)1.09 (0.91 to 1.31)0.87 (0.68 to 1.12)0.81 (0.60 to 1.09)1.01 (0.73 to 1.38)0.97 (0.78 to 1.21)1.05 (0.78 to 1.41)1.01 (0.84 to 1.21)0.96 (0.82 to 1.14)0.82 (0.64 to 1.05)1.00 (0.82 to 1.23)0.85 (0.66 to 1.10)0.93 (0.77 to 1.13)0.86 (0.64 to 1.16)0.95 (0.76 to 1.20)
1.08 (0.90 to 1.29)1.38 (1.16 to 1.64)1.02 (0.83 to 1.24)citalopram0.72 (0.54 to 0.97)0.88 (0.68 to 1.14)0.87 (0.72 to 1.06)1.04 (0.87 to 1.25)1.07 (0.90 to 1.27)0.86 (0.68 to 1.08)0.79 (0.59 to 1.06)0.99 (0.73 to 1.34)0.95 (0.77 to 1.18)1.03 (0.77 to 1.38)0.99 (0.84 to 1.18)0.95 (0.81 to 1.11)0.81 (0.64 to 1.02)0.99 (0.81 to 1.19)0.84 (0.64 to 1.09)0.91 (0.76 to 1.10)0.84 (0.64 to 1.11)0.94 (0.75 to 1.17)
1.10 (0.86 to 1.41)1.41 (1.12 to 1.79)1.04 (0.80 to 1.35)1.03 (0.80 to 1.31)clomipramine1.21 (0.87 to 1.69)1.20 (0.91 to 1.59)1.44 (1.09 to 1.90)1.48 (1.14 to 1.92)1.18 (0.87 to 1.61)1.10 (0.77 to 1.56)1.36 (0.95 to 1.96)1.32 (0.98 to 1.76)1.42 (1.00 to 2.03)1.37 (1.06 to 1.76)1.31 (1.01 to 1.69)1.12 (0.82 to 1.52)1.36 (1.04 to 1.79)1.15 (0.83 to 1.60)1.26 (0.96 to 1.65)1.17 (0.82 to 1.66)1.29 (0.96 to 1.75)
1.10 (0.88 to 1.38)1.41 (1.13 to 1.76)1.04 (0.82 to 1.32)1.02 (0.82 to 1.28)1.00 (0.75 to 1.32)desvenlafaxine0.99 (0.78 to 1.25)1.19 (0.93 to 1.51)1.22 (0.97 to 1.53)0.97 (0.74 to 1.29)0.90 (0.65 to 1.25)1.12 (0.80 to 1.58)1.08 (0.84 to 1.40)1.17 (0.85 to 1.62)1.13 (0.90 to 1.41)1.08 (0.87 to 1.32)0.92 (0.70 to 1.22)1.12 (0.88 to 1.43)0.95 (0.71 to 1.28)1.04 (0.82 to 1.31)0.96 (0.70 to 1.32)1.07 (0.82 to 1.38)
0.89 (0.75 to 1.05)1.14 (0.97 to 1.34)0.84 (0.70 to 1.02)0.83 (0.70 to 0.98)0.81 (0.64 to 1.02)0.81 (0.65 to 1.00)duloxetine1.20 (1.02 to 1.41)1.23 (1.06 to 1.42)0.98 (0.79 to 1.23)0.91 (0.69 to 1.20)1.13 (0.85 to 1.52)1.09 (0.90 to 1.33)1.18 (0.90 to 1.56)1.14 (0.99 to 1.31)1.09 (0.96 to 1.23)0.93 (0.75 to 1.16)1.13 (0.95 to 1.34)0.96 (0.75 to 1.22)1.05 (0.90 to 1.22)0.97 (0.74 to 1.27)1.08 (0.90 to 1.29)
0.98 (0.84 to 1.15)1.26 (1.08 to 1.47)0.93 (0.78 to 1.11)0.91 (0.79 to 1.06)0.89 (0.70 to 1.13)0.89 (0.72 to 1.10)1.10 (0.95 to 1.28)escitalopram1.03 (0.89 to 1.18)0.82 (0.66 to 1.02)0.76 (0.58 to 1.00)0.95 (0.71 to 1.27)0.91 (0.75 to 1.11)0.99 (0.75 to 1.30)0.95 (0.83 to 1.09)0.91 (0.80 to 1.02)0.78 (0.62 to 0.96)0.94 (0.80 to 1.11)0.80 (0.63 to 1.02)0.88 (0.75 to 1.02)0.81 (0.62 to 1.06)0.90 (0.74 to 1.09)
1.08 (0.94 to 1.25)1.39 (1.21 to 1.58)1.02 (0.87 to 1.21)1.00 (0.87 to 1.16)0.98 (0.79 to 1.22)0.98 (0.80 to 1.20)1.22 (1.06 to 1.39)1.10 (0.97 to 1.25)fluoxetine0.80 (0.66 to 0.98)0.74 (0.57 to 0.96)0.92 (0.70 to 1.21)0.89 (0.76 to 1.05)0.96 (0.74 to 1.25)0.93 (0.83 to 1.03)0.88 (0.81 to 0.97)0.76 (0.62 to 0.92)0.92 (0.80 to 1.06)0.78 (0.62 to 0.98)0.85 (0.76 to 0.97)0.79 (0.61 to 1.02)0.88 (0.73 to 1.05)
0.98 (0.79 to 1.22)1.26 (1.03 to 1.54)0.93 (0.74 to 1.17)0.91 (0.74 to 1.13)0.89 (0.68 to 1.16)0.89 (0.69 to 1.15)1.10 (0.90 to 1.36)1.00 (0.81 to 1.22)0.91 (0.75 to 1.09)fluvoxamine0.93 (0.68 to 1.26)1.15 (0.85 to 1.57)1.11 (0.89 to 1.40)1.20 (0.88 to 1.64)1.16 (0.95 to 1.41)1.10 (0.92 to 1.33)0.95 (0.73 to 1.22)1.15 (0.93 to 1.43)0.98 (0.74 to 1.29)1.07 (0.87 to 1.32)0.99 (0.72 to 1.34)1.09 (0.86 to 1.40)
1.03 (0.78 to 1.36)1.32 (1.00 to 1.74)0.97 (0.73 to 1.30)0.96 (0.72 to 1.27)0.93 (0.67 to 1.29)0.93 (0.69 to 1.27)1.16 (0.88 to 1.52)1.05 (0.80 to 1.37)0.95 (0.73 to 1.24)1.05 (0.77 to 1.42)levomilnacipran1.24 (0.86 to 1.79)1.20 (0.90 to 1.60)1.30 (0.91 to 1.84)1.25 (0.96 to 1.62)1.19 (0.93 to 1.52)1.02 (0.75 to 1.39)1.24 (0.94 to 1.63)1.05 (0.76 to 1.46)1.15 (0.88 to 1.51)1.06 (0.75 to 1.50)1.18 (0.88 to 1.58)
0.95 (0.72 to 1.25)1.22 (0.94 to 1.57)0.90 (0.68 to 1.19)0.88 (0.67 to 1.16)0.86 (0.63 to 1.17)0.86 (0.64 to 1.17)1.07 (0.82 to 1.39)0.97 (0.74 to 1.26)0.88 (0.69 to 1.12)0.97 (0.73 to 1.28)0.92 (0.65 to 1.31)milnacipran0.97 (0.71 to 1.31)1.04 (0.72 to 1.50)1.00 (0.77 to 1.31)0.96 (0.73 to 1.25)0.82 (0.59 to 1.13)1.00 (0.75 to 1.33)0.85 (0.60 to 1.19)0.93 (0.70 to 1.23)0.85 (0.59 to 1.23)0.95 (0.69 to 1.30)
0.88 (0.73 to 1.06)1.13 (0.94 to 1.34)0.83 (0.67 to 1.02)0.82 (0.67 to 0.99)0.80 (0.62 to 1.02)0.80 (0.63 to 1.01)0.99 (0.82 to 1.18)0.89 (0.75 to 1.07)0.81 (0.70 to 0.95)0.90 (0.72 to 1.11)0.85 (0.64 to 1.14)0.92 (0.70 to 1.22)mirtazapine1.08 (0.81 to 1.44)1.04 (0.88 to 1.22)0.99 (0.85 to 1.16)0.85 (0.67 to 1.07)1.03 (0.86 to 1.25)0.88 (0.68 to 1.12)0.96 (0.80 to 1.14)0.88 (0.66 to 1.18)0.98 (0.79 to 1.23)
0.98 (0.75 to 1.29)1.26 (0.97 to 1.64)0.93 (0.70 to 1.23)0.91 (0.70 to 1.20)0.89 (0.65 to 1.22)0.89 (0.66 to 1.21)1.11 (0.85 to 1.44)1.00 (0.77 to 1.30)0.91 (0.71 to 1.16)1.00 (0.75 to 1.35)0.96 (0.68 to 1.35)1.04 (0.74 to 1.45)1.12 (0.85 to 1.48)nefazodone0.96 (0.74 to 1.25)0.92 (0.72 to 1.18)0.79 (0.58 to 1.07)0.96 (0.73 to 1.26)0.81 (0.59 to 1.13)0.89 (0.68 to 1.16)0.82 (0.58 to 1.16)0.91 (0.68 to 1.22)
0.95 (0.82 to 1.09)1.21 (1.07 to 1.38)0.90 (0.76 to 1.06)0.88 (0.76 to 1.02)0.86 (0.69 to 1.06)0.86 (0.70 to 1.05)1.06 (0.94 to 1.21)0.96 (0.85 to 1.09)0.88 (0.79 to 0.97)0.97 (0.80 to 1.16)0.92 (0.71 to 1.19)1.00 (0.78 to 1.27)1.08 (0.92 to 1.26)0.96 (0.75 to 1.23)paroxetine0.95 (0.88 to 1.04)0.82 (0.67 to 0.99)0.99 (0.86 to 1.14)0.84 (0.67 to 1.05)0.92 (0.81 to 1.05)0.85 (0.66 to 1.10)0.95 (0.79 to 1.13)
1.63 (1.44 to 1.86)2.10 (1.86 to 2.36)1.55 (1.33 to 1.80)1.52 (1.33 to 1.73)1.48 (1.20 to 1.84)1.48 (1.24 to 1.78)1.84 (1.64 to 2.05)1.66 (1.49 to 1.85)1.51 (1.39 to 1.64)1.67 (1.40 to 1.99)1.59 (1.24 to 2.04)1.72 (1.35 to 2.20)1.86 (1.61 to 2.16)1.66 (1.31 to 2.10)1.73 (1.59 to 1.87)placebo0.86 (0.71 to 1.03)1.04 (0.92 to 1.18)0.88 (0.71 to 1.09)0.97 (0.87 to 1.08)0.89 (0.70 to 1.14)0.99 (0.84 to 1.16)
1.20 (0.98 to 1.49)1.54 (1.26 to 1.89)1.14 (0.91 to 1.43)1.12 (0.91 to 1.37)1.09 (0.84 to 1.43)1.09 (0.85 to 1.40)1.35 (1.11 to 1.65)1.23 (1.01 to 1.49)1.11 (0.93 to 1.33)1.23 (0.96 to 1.56)1.17 (0.87 to 1.58)1.27 (0.95 to 1.70)1.37 (1.10 to 1.71)1.22 (0.92 to 1.63)1.27 (1.07 to 1.52)0.74 (0.62 to 0.87)reboxetine1.22 (0.98 to 1.51)1.03 (0.78 to 1.36)1.13 (0.92 to 1.39)1.04 (0.77 to 1.41)1.16 (0.91 to 1.48)
0.99 (0.84 to 1.17)1.27 (1.10 to 1.47)0.94 (0.78 to 1.13)0.92 (0.78 to 1.09)0.90 (0.71 to 1.13)0.90 (0.73 to 1.12)1.12 (0.95 to 1.30)1.01 (0.87 to 1.17)0.92 (0.81 to 1.04)1.01 (0.83 to 1.24)0.96 (0.73 to 1.27)1.04 (0.80 to 1.36)1.13 (0.95 to 1.35)1.01 (0.78 to 1.30)1.05 (0.92 to 1.19)0.61 (0.54 to 0.68)0.82 (0.67 to 1.01)sertraline0.85 (0.67 to 1.08)0.93 (0.80 to 1.08)0.86 (0.65 to 1.13)0.95 (0.78 to 1.16)
1.11 (0.88 to 1.39)1.42 (1.14 to 1.76)1.05 (0.82 to 1.33)1.03 (0.81 to 1.29)1.00 (0.76 to 1.32)1.00 (0.77 to 1.31)1.24 (1.00 to 1.55)1.12 (0.90 to 1.40)1.02 (0.83 to 1.25)1.13 (0.87 to 1.46)1.07 (0.78 to 1.47)1.16 (0.86 to 1.58)1.26 (1.00 to 1.58)1.12 (0.83 to 1.52)1.17 (0.95 to 1.43)0.68 (0.56 to 0.82)0.92 (0.71 to 1.18)1.11 (0.90 to 1.38)trazodone1.09 (0.87 to 1.38)1.01 (0.73 to 1.40)1.12 (0.86 to 1.46)
0.93 (0.79 to 1.08)1.19 (1.03 to 1.37)0.88 (0.73 to 1.04)0.86 (0.73 to 1.01)0.84 (0.67 to 1.05)0.84 (0.68 to 1.03)1.04 (0.90 to 1.20)0.94 (0.82 to 1.08)0.86 (0.77 to 0.96)0.94 (0.78 to 1.15)0.90 (0.69 to 1.17)0.98 (0.75 to 1.26)1.05 (0.89 to 1.24)0.94 (0.73 to 1.21)0.98 (0.87 to 1.10)0.57 (0.51 to 0.63)0.77 (0.64 to 0.93)0.93 (0.81 to 1.07)0.84 (0.68 to 1.03)venlafaxine0.92 (0.71 to 1.20)1.02 (0.85 to 1.23)
1.04 (0.81 to 1.34)1.33 (1.04 to 1.71)0.98 (0.75 to 1.28)0.96 (0.76 to 1.23)0.94 (0.69 to 1.28)0.94 (0.71 to 1.25)1.17 (0.91 to 1.49)1.06 (0.83 to 1.34)0.96 (0.76 to 1.21)1.06 (0.80 to 1.40)1.01 (0.72 to 1.40)1.09 (0.79 to 1.52)1.18 (0.91 to 1.54)1.05 (0.76 to 1.46)1.10 (0.87 to 1.38)0.63 (0.51 to 0.79)0.86 (0.65 to 1.13)1.05 (0.82 to 1.34)0.94 (0.70 to 1.26)1.12 (0.88 to 1.42)vilazodone1.11 (0.83 to 1.49)
0.99 (0.82 to 1.19)1.27 (1.05 to 1.52)0.93 (0.76 to 1.15)0.92 (0.76 to 1.11)0.89 (0.69 to 1.15)0.90 (0.71 to 1.13)1.11 (0.94 to 1.30)1.01 (0.84 to 1.20)0.91 (0.78 to 1.07)1.01 (0.80 to 1.26)0.96 (0.72 to 1.28)1.04 (0.79 to 1.38)1.12 (0.92 to 1.38)1.00 (0.76 to 1.32)1.04 (0.89 to 1.22)0.60 (0.52 to 0.70)0.82 (0.66 to 1.02)1.00 (0.83 to 1.19)0.89 (0.70 to 1.13)1.07 (0.90 to 1.26)0.95 (0.73 to 1.23)vortioxetine

6 节点分割法(netsplit)

不一致性是指网状meta分析中直接证据和间接证据存在差异,这会影响网状meta分析的真实性,因此需要在进行网状meta分析时进行检测,并分析不一致性的产生原因。对于三个治疗措施形成的闭合环,就可以直接比较直接证据和间接证据之间的不一致性。对于四个研究形成的闭合环,可以分割成两个闭合的三角形环,进而分析直接证据和间接证据之间的不一致性。

常用的不一致检验方法为节点分割法,使用netsplit函数实现:

netsplit(e.netmeta)
## Separate indirect from direct evidence (SIDE) using back-calculation method
## 
## Random effects model: 
## 
##                      comparison  k   prop    nma direct indir.    RoR     z p-value
##       amitriptyline:agomelatine  0      0 1.2819      . 1.2819      .     .       .
##           bupropion:agomelatine  0      0 0.9461      . 0.9461      .     .       .
##          citalopram:agomelatine  0      0 0.9289      . 0.9289      .     .       .
##        clomipramine:agomelatine  0      0 0.9061      . 0.9061      .     .       .
##      desvenlafaxine:agomelatine  0      0 0.9078      . 0.9078      .     .       .
##          duloxetine:agomelatine  1   0.08 1.1242 1.3162 1.1087 1.1873  0.56  0.5763
##        escitalopram:agomelatine  2   0.10 1.0180 0.8117 1.0431 0.7782 -0.90  0.3671
##          fluoxetine:agomelatine  4   0.26 0.9246 0.9841 0.9050 1.0874  0.50  0.6144
##         fluvoxamine:agomelatine  0      0 1.0197      . 1.0197      .     .       .
##     levomilnacipran:agomelatine  0      0 0.9716      . 0.9716      .     .       .
##         milnacipran:agomelatine  0      0 1.0531      . 1.0531      .     .       .
##         mirtazapine:agomelatine  0      0 1.1393      . 1.1393      .     .       .
##          nefazodone:agomelatine  0      0 1.0155      . 1.0155      .     .       .
##          paroxetine:agomelatine  5   0.28 1.0562 1.1715 1.0151 1.1540  0.89  0.3740
##             placebo:agomelatine 13   0.57 0.6118 0.6423 0.5742 1.1186  0.84  0.4022
##          reboxetine:agomelatine  0      0 0.8301      . 0.8301      .     .       .
##          sertraline:agomelatine  0      0 1.0080      . 1.0080      .     .       .
##           trazodone:agomelatine  0      0 0.9050      . 0.9050      .     .       .
##         venlafaxine:agomelatine  2   0.10 1.0800 0.7374 1.1293 0.6529 -1.66  0.0970
##          vilazodone:agomelatine  0      0 0.9636      . 0.9636      .     .       .
##        vortioxetine:agomelatine  0      0 1.0130      . 1.0130      .     .       .
##         amitriptyline:bupropion  0      0 1.3549      . 1.3549      .     .       .
##        amitriptyline:citalopram  0      0 1.3800      . 1.3800      .     .       .
##      amitriptyline:clomipramine  0      0 1.4147      . 1.4147      .     .       .
##    amitriptyline:desvenlafaxine  0      0 1.4120      . 1.4120      .     .       .
##        amitriptyline:duloxetine  0      0 1.1402      . 1.1402      .     .       .
##      amitriptyline:escitalopram  0      0 1.2592      . 1.2592      .     .       .
##        amitriptyline:fluoxetine 12   0.17 1.3863 1.0645 1.4642 0.7271 -1.78  0.0751
##       amitriptyline:fluvoxamine  3   0.15 1.2571 1.0897 1.2886 0.8457 -0.58  0.5605
##   amitriptyline:levomilnacipran  0      0 1.3193      . 1.3193      .     .       .
##       amitriptyline:milnacipran  2   0.17 1.2172 1.1673 1.2274 0.9510 -0.14  0.8865
##       amitriptyline:mirtazapine  4   0.15 1.1251 1.0455 1.1397 0.9173 -0.34  0.7325
##        amitriptyline:nefazodone  0      0 1.2624      . 1.2624      .     .       .
##        amitriptyline:paroxetine 13   0.27 1.2137 1.0677 1.2734 0.8385 -1.19  0.2326
##           amitriptyline:placebo 22   0.41 2.0951 2.6250 1.7952 1.4622  3.04  0.0024
##        amitriptyline:reboxetine  0      0 1.5442      . 1.5442      .     .       .
##        amitriptyline:sertraline  7   0.31 1.2716 1.2908 1.2632 1.0218  0.13  0.8948
##         amitriptyline:trazodone  3   0.19 1.4165 1.2748 1.4511 0.8785 -0.46  0.6458
##       amitriptyline:venlafaxine  2   0.06 1.1869 1.1829 1.1872 0.9963 -0.01  0.9905
##        amitriptyline:vilazodone  0      0 1.3303      . 1.3303      .     .       .
##      amitriptyline:vortioxetine  0      0 1.2655      . 1.2655      .     .       .
##            bupropion:citalopram  0      0 1.0186      . 1.0186      .     .       .
##          bupropion:clomipramine  0      0 1.0442      . 1.0442      .     .       .
##        bupropion:desvenlafaxine  0      0 1.0422      . 1.0422      .     .       .
##            bupropion:duloxetine  0      0 0.8416      . 0.8416      .     .       .
##          bupropion:escitalopram  2   0.17 0.9294 0.9319 0.9289 1.0033  0.01  0.9894
##            bupropion:fluoxetine  3   0.19 1.0232 0.8415 1.0726 0.7846 -1.13  0.2601
##           bupropion:fluvoxamine  0      0 0.9278      . 0.9278      .     .       .
##       bupropion:levomilnacipran  0      0 0.9738      . 0.9738      .     .       .
##           bupropion:milnacipran  0      0 0.8984      . 0.8984      .     .       .
##           bupropion:mirtazapine  0      0 0.8304      . 0.8304      .     .       .
##            bupropion:nefazodone  0      0 0.9317      . 0.9317      .     .       .
##            bupropion:paroxetine  1   0.05 0.8958 1.0008 0.8909 1.1234  0.29  0.7743
##               bupropion:placebo 17   0.75 1.5464 1.4492 1.8839 0.7693 -1.45  0.1472
##            bupropion:reboxetine  0      0 1.1398      . 1.1398      .     .       .
##            bupropion:sertraline  1 < 0.01 0.9386 0.9375 0.9386 0.9988 -0.00  0.9991
##             bupropion:trazodone  1   0.08 1.0455 2.0952 0.9811 2.1357  1.72  0.0859
##           bupropion:venlafaxine  1   0.09 0.8761 1.1722 0.8510 1.3774  1.03  0.3052
##            bupropion:vilazodone  0      0 0.9819      . 0.9819      .     .       .
##          bupropion:vortioxetine  0      0 0.9340      . 0.9340      .     .       .
##         citalopram:clomipramine  1   0.08 1.0251 0.5674 1.0811 0.5248 -1.43  0.1524
##       citalopram:desvenlafaxine  0      0 1.0232      . 1.0232      .     .       .
##           citalopram:duloxetine  0      0 0.8263      . 0.8263      .     .       .
##         citalopram:escitalopram 13   0.43 0.9124 0.7465 1.0587 0.7052 -2.28  0.0226
##           citalopram:fluoxetine  2   0.11 1.0046 0.9632 1.0101 0.9536 -0.20  0.8390
##          citalopram:fluvoxamine  1   0.09 0.9109 1.1071 0.8937 1.2388  0.56  0.5728
##      citalopram:levomilnacipran  0      0 0.9560      . 0.9560      .     .       .
##          citalopram:milnacipran  0      0 0.8820      . 0.8820      .     .       .
##          citalopram:mirtazapine  1   0.06 0.8153 1.3238 0.7926 1.6702  1.21  0.2263
##           citalopram:nefazodone  0      0 0.9148      . 0.9148      .     .       .
##           citalopram:paroxetine  1   0.06 0.8795 1.3555 0.8575 1.5808  1.39  0.1631
##              citalopram:placebo 11   0.47 1.5182 1.5025 1.5324 0.9805 -0.15  0.8833
##           citalopram:reboxetine  1   0.12 1.1190 1.7296 1.0517 1.6446  1.57  0.1167
##           citalopram:sertraline  3   0.11 0.9215 0.8849 0.9259 0.9557 -0.17  0.8682
##            citalopram:trazodone  0      0 1.0264      . 1.0264      .     .       .
##          citalopram:venlafaxine  2   0.05 0.8601 1.7421 0.8265 2.1078  2.09  0.0365
##           citalopram:vilazodone  2   0.38 0.9640 0.9358 0.9813 0.9536 -0.19  0.8516
##         citalopram:vortioxetine  0      0 0.9170      . 0.9170      .     .       .
##     clomipramine:desvenlafaxine  0      0 0.9981      . 0.9981      .     .       .
##         clomipramine:duloxetine  0      0 0.8060      . 0.8060      .     .       .
##       clomipramine:escitalopram  0      0 0.8901      . 0.8901      .     .       .
##         clomipramine:fluoxetine  4   0.19 0.9800 0.6108 1.0955 0.5576 -2.07  0.0389
##        clomipramine:fluvoxamine  2   0.06 0.8886 1.8541 0.8450 2.1942  1.41  0.1572
##    clomipramine:levomilnacipran  0      0 0.9326      . 0.9326      .     .       .
##        clomipramine:milnacipran  1   0.12 0.8604 0.8696 0.8592 1.0121  0.03  0.9798
##        clomipramine:mirtazapine  0      0 0.7953      . 0.7953      .     .       .
##         clomipramine:nefazodone  0      0 0.8923      . 0.8923      .     .       .
##         clomipramine:paroxetine  6   0.44 0.8579 0.9052 0.8227 1.1003  0.44  0.6617
##            clomipramine:placebo  0      0 1.4810      . 1.4810      .     .       .
##         clomipramine:reboxetine  0      0 1.0916      . 1.0916      .     .       .
##         clomipramine:sertraline  2   0.16 0.8989 0.9547 0.8883 1.0746  0.23  0.8204
##          clomipramine:trazodone  1   0.10 1.0013 1.6162 0.9476 1.7056  1.14  0.2524
##        clomipramine:venlafaxine  2   0.13 0.8390 0.6046 0.8797 0.6872 -1.08  0.2811
##         clomipramine:vilazodone  0      0 0.9404      . 0.9404      .     .       .
##       clomipramine:vortioxetine  0      0 0.8945      . 0.8945      .     .       .
##       desvenlafaxine:duloxetine  1   0.14 0.8075 0.8285 0.8041 1.0304  0.10  0.9223
##     desvenlafaxine:escitalopram  0      0 0.8917      . 0.8917      .     .       .
##       desvenlafaxine:fluoxetine  0      0 0.9818      . 0.9818      .     .       .
##      desvenlafaxine:fluvoxamine  0      0 0.8903      . 0.8903      .     .       .
##  desvenlafaxine:levomilnacipran  0      0 0.9343      . 0.9343      .     .       .
##      desvenlafaxine:milnacipran  0      0 0.8620      . 0.8620      .     .       .
##      desvenlafaxine:mirtazapine  0      0 0.7968      . 0.7968      .     .       .
##       desvenlafaxine:nefazodone  0      0 0.8940      . 0.8940      .     .       .
##       desvenlafaxine:paroxetine  0      0 0.8595      . 0.8595      .     .       .
##          desvenlafaxine:placebo  9   0.96 1.4837 1.4711 1.8067 0.8142 -0.44  0.6590
##       desvenlafaxine:reboxetine  0      0 1.0936      . 1.0936      .     .       .
##       desvenlafaxine:sertraline  0      0 0.9006      . 0.9006      .     .       .
##        desvenlafaxine:trazodone  0      0 1.0031      . 1.0031      .     .       .
##      desvenlafaxine:venlafaxine  0      0 0.8406      . 0.8406      .     .       .
##       desvenlafaxine:vilazodone  0      0 0.9421      . 0.9421      .     .       .
##     desvenlafaxine:vortioxetine  0      0 0.8962      . 0.8962      .     .       .
##         duloxetine:escitalopram  3   0.19 1.1043 0.8436 1.1744 0.7183 -1.73  0.0834
##           duloxetine:fluoxetine  2   0.04 1.2158 1.2298 1.2152 1.0120  0.04  0.9713
##          duloxetine:fluvoxamine  0      0 1.1025      . 1.1025      .     .       .
##      duloxetine:levomilnacipran  0      0 1.1570      . 1.1570      .     .       .
##          duloxetine:milnacipran  0      0 1.0675      . 1.0675      .     .       .
##          duloxetine:mirtazapine  0      0 0.9868      . 0.9868      .     .       .
##           duloxetine:nefazodone  0      0 1.1071      . 1.1071      .     .       .
##           duloxetine:paroxetine  7   0.28 1.0644 0.9756 1.1018 0.8855 -0.85  0.3975
##              duloxetine:placebo 21   0.65 1.8374 1.9167 1.6999 1.1275  1.01  0.3148
##           duloxetine:reboxetine  0      0 1.3543      . 1.3543      .     .       .
##           duloxetine:sertraline  0      0 1.1153      . 1.1153      .     .       .
##            duloxetine:trazodone  0      0 1.2423      . 1.2423      .     .       .
##          duloxetine:venlafaxine  2   0.12 1.0410 0.8989 1.0623 0.8462 -0.76  0.4462
##           duloxetine:vilazodone  0      0 1.1667      . 1.1667      .     .       .
##         duloxetine:vortioxetine  6   0.46 1.1098 1.3793 0.9188 1.5011  2.46  0.0141
##         escitalopram:fluoxetine  3   0.11 1.1010 1.1260 1.0979 1.0256  0.12  0.9028
##        escitalopram:fluvoxamine  0      0 0.9983      . 0.9983      .     .       .
##    escitalopram:levomilnacipran  0      0 1.0478      . 1.0478      .     .       .
##        escitalopram:milnacipran  0      0 0.9667      . 0.9667      .     .       .
##        escitalopram:mirtazapine  0      0 0.8936      . 0.8936      .     .       .
##         escitalopram:nefazodone  0      0 1.0025      . 1.0025      .     .       .
##         escitalopram:paroxetine  3   0.14 0.9639 0.9924 0.9594 1.0344  0.18  0.8556
##            escitalopram:placebo 20   0.57 1.6639 1.4412 2.0122 0.7162 -3.00  0.0027
##         escitalopram:reboxetine  0      0 1.2264      . 1.2264      .     .       .
##         escitalopram:sertraline  3   0.11 1.0099 0.8644 1.0296 0.8395 -0.72  0.4724
##          escitalopram:trazodone  0      0 1.1249      . 1.1249      .     .       .
##        escitalopram:venlafaxine  2   0.08 0.9426 1.2105 0.9219 1.3130  1.06  0.2899
##         escitalopram:vilazodone  0      0 1.0565      . 1.0565      .     .       .
##       escitalopram:vortioxetine  0      0 1.0050      . 1.0050      .     .       .
##          fluoxetine:fluvoxamine  2   0.11 0.9068 0.9700 0.8992 1.0788  0.25  0.8014
##      fluoxetine:levomilnacipran  0      0 0.9516      . 0.9516      .     .       .
##          fluoxetine:milnacipran  2   0.27 0.8780 1.1789 0.7874 1.4972  1.43  0.1517
##          fluoxetine:mirtazapine  6   0.22 0.8116 0.7559 0.8281 0.9128 -0.48  0.6312
##           fluoxetine:nefazodone  3   0.14 0.9106 0.9633 0.9025 1.0673  0.18  0.8586
##           fluoxetine:paroxetine 12   0.23 0.8755 0.9421 0.8566 1.0998  0.79  0.4297
##              fluoxetine:placebo 39   0.47 1.5113 1.4097 1.6086 0.8764 -1.56  0.1180
##           fluoxetine:reboxetine  4   0.25 1.1139 1.2160 1.0816 1.1243  0.56  0.5785
##           fluoxetine:sertraline  6   0.19 0.9173 0.7004 0.9786 0.7157 -2.03  0.0426
##            fluoxetine:trazodone  4   0.12 1.0217 0.8357 1.0506 0.7955 -0.73  0.4683
##          fluoxetine:venlafaxine 14   0.33 0.8562 0.8008 0.8849 0.9049 -0.82  0.4097
##           fluoxetine:vilazodone  0      0 0.9596      . 0.9596      .     .       .
##         fluoxetine:vortioxetine  0      0 0.9128      . 0.9128      .     .       .
##     fluvoxamine:levomilnacipran  0      0 1.0495      . 1.0495      .     .       .
##         fluvoxamine:milnacipran  2   0.21 0.9683 0.5832 1.1054 0.5276 -1.82  0.0690
##         fluvoxamine:mirtazapine  2   0.19 0.8950 0.8764 0.8993 0.9745 -0.09  0.9264
##          fluvoxamine:nefazodone  0      0 1.0042      . 1.0042      .     .       .
##          fluvoxamine:paroxetine  2   0.08 0.9655 0.8810 0.9729 0.9055 -0.28  0.7787
##             fluvoxamine:placebo 11   0.37 1.6667 2.0337 1.4836 1.3708  1.69  0.0915
##          fluvoxamine:reboxetine  0      0 1.2284      . 1.2284      .     .       .
##          fluvoxamine:sertraline  2   0.09 1.0116 1.5585 0.9685 1.6091  1.34  0.1802
##           fluvoxamine:trazodone  0      0 1.1268      . 1.1268      .     .       .
##         fluvoxamine:venlafaxine  1   0.05 0.9442 0.4229 0.9810 0.4311 -1.76  0.0792
##          fluvoxamine:vilazodone  0      0 1.0583      . 1.0583      .     .       .
##        fluvoxamine:vortioxetine  0      0 1.0067      . 1.0067      .     .       .
##     levomilnacipran:milnacipran  0      0 0.9226      . 0.9226      .     .       .
##     levomilnacipran:mirtazapine  0      0 0.8528      . 0.8528      .     .       .
##      levomilnacipran:nefazodone  0      0 0.9568      . 0.9568      .     .       .
##      levomilnacipran:paroxetine  0      0 0.9199      . 0.9199      .     .       .
##         levomilnacipran:placebo  5   1.00 1.5881 1.5881      .      .     .       .
##      levomilnacipran:reboxetine  0      0 1.1705      . 1.1705      .     .       .
##      levomilnacipran:sertraline  0      0 0.9639      . 0.9639      .     .       .
##       levomilnacipran:trazodone  0      0 1.0737      . 1.0737      .     .       .
##     levomilnacipran:venlafaxine  0      0 0.8997      . 0.8997      .     .       .
##      levomilnacipran:vilazodone  0      0 1.0084      . 1.0084      .     .       .
##    levomilnacipran:vortioxetine  0      0 0.9592      . 0.9592      .     .       .
##         milnacipran:mirtazapine  0      0 0.9243      . 0.9243      .     .       .
##          milnacipran:nefazodone  0      0 1.0371      . 1.0371      .     .       .
##          milnacipran:paroxetine  2   0.40 0.9971 0.9517 1.0283 0.9255 -0.31  0.7587
##             milnacipran:placebo  0      0 1.7212      . 1.7212      .     .       .
##          milnacipran:reboxetine  0      0 1.2686      . 1.2686      .     .       .
##          milnacipran:sertraline  1   0.02 1.0447 2.0870 1.0299 2.0264  0.75  0.4556
##           milnacipran:trazodone  0      0 1.1637      . 1.1637      .     .       .
##         milnacipran:venlafaxine  0      0 0.9751      . 0.9751      .     .       .
##          milnacipran:vilazodone  0      0 1.0929      . 1.0929      .     .       .
##        milnacipran:vortioxetine  0      0 1.0396      . 1.0396      .     .       .
##          mirtazapine:nefazodone  0      0 1.1220      . 1.1220      .     .       .
##          mirtazapine:paroxetine  5   0.22 1.0787 0.9653 1.1127 0.8676 -0.75  0.4553
##             mirtazapine:placebo 12   0.34 1.8621 1.7805 1.9058 0.9342 -0.43  0.6659
##          mirtazapine:reboxetine  0      0 1.3725      . 1.3725      .     .       .
##          mirtazapine:sertraline  1   0.08 1.1302 0.9741 1.1458 0.8502 -0.50  0.6138
##           mirtazapine:trazodone  2   0.18 1.2589 1.5017 1.2127 1.2384  0.70  0.4859
##         mirtazapine:venlafaxine  2   0.14 1.0549 1.3661 1.0124 1.3493  1.22  0.2208
##          mirtazapine:vilazodone  0      0 1.1824      . 1.1824      .     .       .
##        mirtazapine:vortioxetine  0      0 1.1247      . 1.1247      .     .       .
##           nefazodone:paroxetine  2   0.16 0.9614 0.7517 1.0065 0.7468 -0.85  0.3962
##              nefazodone:placebo  8   0.63 1.6597 1.7354 1.5368 1.1293  0.48  0.6285
##           nefazodone:reboxetine  0      0 1.2233      . 1.2233      .     .       .
##           nefazodone:sertraline  1   0.12 1.0074 1.1667 0.9874 1.1816  0.41  0.6789
##            nefazodone:trazodone  0      0 1.1221      . 1.1221      .     .       .
##          nefazodone:venlafaxine  0      0 0.9403      . 0.9403      .     .       .
##           nefazodone:vilazodone  0      0 1.0538      . 1.0538      .     .       .
##         nefazodone:vortioxetine  0      0 1.0025      . 1.0025      .     .       .
##              paroxetine:placebo 46   0.53 1.7263 1.6524 1.8138 0.9110 -1.14  0.2554
##           paroxetine:reboxetine  3   0.31 1.2724 1.2385 1.2881 0.9615 -0.20  0.8411
##           paroxetine:sertraline  2   0.08 1.0478 0.8952 1.0620 0.8429 -0.70  0.4867
##            paroxetine:trazodone  2   0.12 1.1671 1.7157 1.1093 1.5467  1.36  0.1739
##          paroxetine:venlafaxine  3   0.09 0.9780 0.6303 1.0189 0.6186 -2.25  0.0243
##           paroxetine:vilazodone  0      0 1.0961      . 1.0961      .     .       .
##         paroxetine:vortioxetine  0      0 1.0427      . 1.0427      .     .       .
##              placebo:reboxetine 10   0.62 0.7371 0.7123 0.7788 0.9145 -0.50  0.6157
##              placebo:sertraline 18   0.47 0.6070 0.6270 0.5898 1.0630  0.52  0.6009
##               placebo:trazodone  8   0.42 0.6761 0.5699 0.7653 0.7446 -1.47  0.1410
##             placebo:venlafaxine 22   0.46 0.5665 0.5614 0.5709 0.9833 -0.17  0.8668
##              placebo:vilazodone  6   0.90 0.6350 0.6472 0.5318 1.2171  0.52  0.6024
##            placebo:vortioxetine 14   0.83 0.6040 0.5766 0.7538 0.7649 -1.42  0.1565
##           reboxetine:sertraline  0      0 0.8235      . 0.8235      .     .       .
##            reboxetine:trazodone  0      0 0.9173      . 0.9173      .     .       .
##          reboxetine:venlafaxine  1   0.07 0.7686 1.0446 0.7519 1.3894  0.85  0.3956
##           reboxetine:vilazodone  0      0 0.8615      . 0.8615      .     .       .
##         reboxetine:vortioxetine  0      0 0.8195      . 0.8195      .     .       .
##            sertraline:trazodone  1   0.06 1.1139 0.5595 1.1659 0.4799 -1.60  0.1095
##          sertraline:venlafaxine  3   0.10 0.9334 0.8472 0.9436 0.8979 -0.45  0.6520
##           sertraline:vilazodone  0      0 1.0461      . 1.0461      .     .       .
##         sertraline:vortioxetine  0      0 0.9951      . 0.9951      .     .       .
##           trazodone:venlafaxine  2   0.13 0.8379 0.6311 0.8743 0.7218 -1.03  0.3052
##            trazodone:vilazodone  0      0 0.9392      . 0.9392      .     .       .
##          trazodone:vortioxetine  0      0 0.8934      . 0.8934      .     .       .
##          venlafaxine:vilazodone  0      0 1.1208      . 1.1208      .     .       .
##        venlafaxine:vortioxetine  2   0.15 1.0661 0.8452 1.1114 0.7605 -1.17  0.2412
##         vilazodone:vortioxetine  0      0 0.9512      . 0.9512      .     .       .
## 
## Legend:
##  comparison - Treatment comparison
##  k          - Number of studies providing direct evidence
##  prop       - Direct evidence proportion
##  nma        - Estimated treatment effect (OR) in network meta-analysis
##  direct     - Estimated treatment effect (OR) derived from direct evidence
##  indir.     - Estimated treatment effect (OR) derived from indirect evidence
##  RoR        - Ratio of Ratios (direct versus indirect)
##  z          - z-value of test for disagreement (direct versus indirect)
##  p-value    - p-value of test for disagreement (direct versus indirect)
forest(netsplit(e.netmeta))

结果同样可以使用森林图展示(展示部分):

图片

7 热图(netheat plot)

  • 一种判断不一致性的方法,图中的灰色方块在row方向中越大表示研究越重要,颜色越红代表研究一致性越大。

netheat(e.netmeta, nchar.trts = 4,random = TRUE)

图片

8 排序图(SURCA plot)

对干预措施的优劣进行排序是网状meta分析的一大特色,也是一个主要的优势。目前排序的方法比较多,最常用的有SUCRA法和P得分法,其中,SUCRA法是最为常用的方法,该值越大为最佳干预措施的可能性越大。

netrank(e.netmeta, small.values = "bad") #可做条形图
##                 P-score
## amitriptyline    0.9840
## mirtazapine      0.8460
## duloxetine       0.8367
## venlafaxine      0.7506
## paroxetine       0.6937
## milnacipran      0.6427
## escitalopram     0.5799
## fluvoxamine      0.5766
## nefazodone       0.5608
## vortioxetine     0.5606
## sertraline       0.5493
## agomelatine      0.5248
## levomilnacipran  0.4607
## vilazodone       0.4374
## bupropion        0.3761
## citalopram       0.3207
## clomipramine     0.2962
## fluoxetine       0.2939
## desvenlafaxine   0.2908
## trazodone        0.2865
## reboxetine       0.1318
## placebo          0.0000

9 漏斗图(funnel plot)

发表偏倚检测实际上是和传统meta分析一致的,主要靠漏斗图来实现。解读方法看是否对称,是一个主观判断。

colors <- c(
agom = "thistle", amit = "lightgreen", 
bupr = "coral3", cita = "cadetblue4", 
clom = "orange3",esci = "pink",
fluv = "dodgerblue4", miln = "goldenrod4", 
mirt = "yellow3", nefa = "darkgrey",
paro = "gray9", rebo = "lightblue3", 
sert = "lightslateblue", traz = "red4", 
venl= "mediumvioletred")trts_ef <- substr(e.netmeta$trts, 0, 4)
trts_ac <- substr(a.netmeta$trts, 0, 4)
comparison_ef<- trts_ef[trts_ef != "fluo"]
comparison_ac <- trts_ac[trts_ac != "fluo"]
ord_ef<- c(comparison_ef, "fluo")
ord_ac <- c(comparison_ac, "fluo")

然后使用funnel函数进行漏斗图进行绘制:

funnel(netmeta_ef,order = ord_ef, pch = rep(19), col = colors, legend = FALSE, linreg = TRUE, text.linreg = "(Egger's test)", pos.tests = "topright")
legend("topleft", legend = comparison_ef, pch = rep(19),col = colors, cex = 0.75) 

图片

funnel(
netmeta_ac, 
order = ord_ac, 
pch = rep(19),
col = colors, 
legend = FALSE, 
linreg = TRUE, 
text.linreg = "(Egger's test)", 
pos.tests = "topright")
legend("topleft", legend = comparison_ac,
pch = rep(19),
col = colors, 
cex = 0.75) 

图片

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处:http://www.hqwc.cn/news/572941.html

如若内容造成侵权/违法违规/事实不符,请联系编程知识网进行投诉反馈email:809451989@qq.com,一经查实,立即删除!

相关文章

集合系列(十五) -CopyOnWriteArrayList详解

一、摘要 在介绍 CopyOnWriteArrayList 之前&#xff0c;我们一起先来看看如下方法执行结果&#xff0c;代码内容如下&#xff1a; public static void main(String[] args) {List<String> list new ArrayList<String>();list.add("1");list.add(&quo…

Elasticsearch-相关性

相关性描述的是⼀个⽂档和查询语句匹配的程度。ES 会对每个匹配查询条件的结果进⾏算分_score。_score 的评分越高&#xff0c;相关度越高。 ES 5.0之前使用TF-IDF 相关性算法&#xff0c; 5.0之后使用了BM25算法 TF-IDF 公式 score(q,d) queryNorm(q) coord(q,d) …

将jupyter notebook文件导出为pdf(简单有效)

1.打开jupyter notebook笔记&#xff1a; 2.点击file->print Preview 3.在新打开的页面右键打印 4.另存为PDF 5.保存即可 6.pdf效果 &#xff08;可能有少部分图片显示不了&#xff09; 网上也有其他方法&#xff0c;比如将其转换为.tex再转为PDF等&#xff0c;但个人觉…

如何在 Mac/Windows 上从 iPhone 备份中恢复短信?

- “如何从 iPhone 备份中提取短信&#xff1f;” 短信正在取代日常生活和工作中的电话和电子邮件。 iPhone 上的短信现在是您与朋友、家人、亲人和同事最重要的沟通方式之一。有时&#xff0c;您可能想在 iPhone 上保留一些您不想丢失的特殊消息&#xff0c;也许这是朋友的一…

以太网链路聚合——增加带宽,解决生成树收敛慢的问题

目录 一.对STP生成树的补充 1.STP接口状态 2.STP生成树的改进 二.网络可靠性 1.单板可靠性 2.设备可靠性 3.链路可靠性 三.链路聚合 1.多条链路聚合增加带宽 2.链路聚合术语 四.链路聚合模式 1.手动模式 2.LASP模式 &#xff08;1).LASP术语 &#xff08;2&…

Pillow教程07:调整图片的亮度+对比度+色彩+锐度

---------------Pillow教程集合--------------- Python项目18&#xff1a;使用Pillow模块&#xff0c;随机生成4位数的图片验证码 Python教程93&#xff1a;初识Pillow模块&#xff08;创建Image对象查看属性图片的保存与缩放&#xff09; Pillow教程02&#xff1a;图片的裁…

快速幂算法在Java中的应用

引言&#xff1a; 在计算机科学和算法领域中&#xff0c;快速幂算法是一种用于高效计算幂运算的技术。在实际编程中&#xff0c;特别是在处理大数幂运算时&#xff0c;快速幂算法能够显著提高计算效率。本文将介绍如何在Java中实现快速幂算法&#xff0c;并给出一些示例代码和应…

保姆级指导0基础如何快速搭建“对话机器人”类ChatGPT

参考了CDSN上的文章&#xff0c;但发现不work&#xff0c; 不是这里有问题&#xff0c;就是那里有问题&#xff0c;查阅了大量的资料&#xff0c;做了无数次试验&#xff0c;终于整理出来了一个完整的教程&#xff0c;保可用&#xff0c;保真~~~~~如果各位遇到什么问题&#xf…

Ceph——部署

Ceph简介 Ceph是一款开源的 SDS 分布式存储&#xff0c;它具备极高的可用性、扩展性和易用性&#xff0c;可用于存 储海量数据 Ceph的存储节点可部署在通用服务器上&#xff0c;这些服务器的 CPU 可以是 x86 架构的&#xff0c;也可以 是 ARM 架构的。 Ceph 存储节点之间相互…

边缘计算迎来“量子飞跃”!支持抗量子密码,AMD推出FPGA新系列

3月6日&#xff0c;AMD宣布推出AMD Spartan™ UltraScale™ FPGA系列&#xff0c;这是AMD成本优化FPGA和自适应SoC广泛产品组合的最新成员。 距离1月22日&#xff0c;AMD推出业界首款符合VESA DisplayPort 2.1标准的FPGA和自适应SoC实现&#xff0c;也才过了一个多月的时间。 S…

华为实验-基于用户和应用的安全策略

CLI举例&#xff1a;基于用户和应用的安全策略 通过配置安全策略&#xff0c;实现基于用户、时间段以及应用的访问控制。 组网需求 如图1所示&#xff0c;某企业在网络边界处部署了FW作为安全网关。 企业根据员工级别和职能不同划分了三种用户&#xff1a;高层管理者、市场员…

YOLOv8项目实践——目标检测、实例分割、姿态估计、目标追踪算法原理及模型部署(Python实现带界面)

简介 Ultralytics YOLOv8是一种前沿的、最先进的&#xff08;SOTA&#xff09;模型&#xff0c;它在前代YOLO版本的成功基础上进行了进一步的创新&#xff0c;引入了全新的特性和改进&#xff0c;以进一步提升性能和灵活性。作为一个高速、精准且易于操作的设计&#xff0c;YO…