泳道图 (Swimmer Plot)¶

用途：展示每个受试者的治疗暴露时间、疗效响应状态和事件时间线，常用于肿瘤学临床试验。

交互式图表¶

每个条形代表一位受试者，颜色表示最佳总体响应。悬停查看详情。

生成代码¶

RPython

library(plotly)

swimmer_data <- data.frame(
  Subject = paste0("S", 1:20),
  Response = factor(c(rep("CR", 3), rep("PR", 5), rep("SD", 7), rep("PD", 5)),
                    levels = c("CR", "PR", "SD", "PD")),
  Start = rep(0, 20),
  Duration = c(24, 20, 18, 22, 19, 16, 15, 14, 13, 12, 
               11, 10, 9, 8, 7, 6, 5, 4, 3, 2)
)

colors_swim <- c("CR" = "#2ca02c", "PR" = "#1f77b4", 
                 "SD" = "#ff7f0e", "PD" = "#d62728")

fig <- plot_ly(swimmer_data, 
               x = ~Duration, y = ~reorder(Subject, Duration),
               type = "bar", orientation = "h",
               color = ~Response, colors = colors_swim,
               marker = list(line = list(color = "white", width = 1)),
               hovertemplate = "Subject: %{y}<br>Duration: %{x} months<br>Response: %{color}<extra></extra>")

fig <- fig %>% layout(
  title = "Swimmer Plot — Individual Patient Response",
  xaxis = list(title = "Time on Treatment (months)"),
  yaxis = list(title = "", showticklabels = FALSE),
  barmode = "stack"
)
fig

import plotly.express as px
import pandas as pd

swimmer_data = pd.DataFrame({
    "Subject": [f"S{i}" for i in range(1, 21)],
    "Response": ["CR"]*3 + ["PR"]*5 + ["SD"]*7 + ["PD"]*5,
    "Duration": [24,20,18,22,19,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2]
})

color_map = {"CR": "#2ca02c", "PR": "#1f77b4", 
             "SD": "#ff7f0e", "PD": "#d62728"}

fig = px.bar(swimmer_data, 
             x="Duration", y="Subject",
             color="Response", color_discrete_map=color_map,
             orientation="h",
             title="Swimmer Plot — Individual Patient Response")
fig.update_layout(yaxis={"categoryorder": "total ascending"})
fig.show()

关键参数¶

参数	说明
`orientation="h"`	水平条形图
`barmode="stack"`	堆叠显示不同阶段
颜色映射	CR=绿, PR=蓝, SD=橙, PD=红

AI Prompt 模板¶

生成一张泳道图 (swimmer plot)，展示每例受试者的治疗持续时间
和最佳总体响应 (BOR)。x 轴为治疗时长（月），y 轴为受试者 ID，
条形按响应类型着色：CR 绿色、PR 蓝色、SD 橙色、PD 红色。

参考方法¶

描述性统计