「r<-图形」ezcox 森林图中点估计方块大小设定

这篇文章与 https://github.com/ShixiangWang/MessageBoard/issues/69 与 https://github.com/ShixiangWang/ezcox/issues/12 相关。

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之前开发的 ezcox 包提供了批量建模和展示森林图的功能，我自认为森林图要比 ggpubr 提供的 ggforest 好看。森林图的绘制实际是基于 forestmodel 的实现。

forestmodel 一个简单的使用示例如下：

library("forestmodel")
#> 载入需要的程辑包：ggplot2
library("survival")
library("dplyr")
#> 
#> 载入程辑包：'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
pretty_lung <- lung %>%
  transmute(time,
            status,
            Age = age,
            Sex = factor(sex, labels = c("Male", "Female")),
            ECOG = factor(lung$ph.ecog),
            `Meal Cal` = meal.cal)

print(forest_model(coxph(Surv(time, status) ~ ., pretty_lung)))

有读者说展示点估计的方块比较大，能否方便调节。我检查了下这个设置的底层代码，发现默认设定是 5，由于 forestmodel 包本身没有支持这个设定的修改，所以我只有改源码解决。

安装修改后的版本：

remotes::install_github("ShixiangWang/forestmodel")

修改方式如下：

pretty_lung <- lung %>%
  transmute(time,
            status,
            Age = age,
            Sex = factor(sex, labels = c("Male", "Female")),
            ECOG = factor(lung$ph.ecog),
            `Meal Cal` = meal.cal)

print(forest_model(coxph(Surv(time, status) ~ ., pretty_lung),
                   format_options= forestmodel::forest_model_format_options(point_size = 3)))

这个修改也可以直接应用到 ezcox 的图形绘制中去。

不需要更新 ezcox

library(ezcox)
#> Welcome to 'ezcox' package!
#> =======================================================================
#> You are using ezcox version 0.4.0
#> 
#> Github page  : https://github.com/ShixiangWang/ezcox
#> Documentation: https://shixiangwang.github.io/ezcox/articles/ezcox.html
#> 
#> Run citation("ezcox") to see how to cite 'ezcox'.
#> =======================================================================
#> 
show_forest(lung, covariates = c("sex", "ph.ecog"), controls = "age", 
            format_options= forestmodel::forest_model_format_options(point_size = 3))
#> => Processing variable sex
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.
#> => Processing variable ph.ecog
#> ==> Building Surv object...
#> ==> Building Cox model...
#> ==> Done.