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JCOG1306: reconstructed Kaplan–Meier curves

Updated 2026-09-25 · reconstructed by TrialCurve from a CC BY-licensed publication

Perioperative Adriamycin plus ifosfamide vs. gemcitabine plus docetaxel for high-risk soft tissue sarcomas: randomised, phase II/III study JCOG1306. Curves rebuilt as patient-level data (Guyot 2012) and checked against the statistics printed on the figure.

PublicationBr J Cancer. 2022 Jul 23;127(8):1487–96. doi: 10.1038/s41416-022-01912-5
DOI10.1038/s41416-022-01912-5
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Source licenceFigure published under CC BY 4.0

Overall survival

From figure panel a · validated against the values printed on the figure · curve source: pixel measurement confirmed by vision model

Reconstructed from the published curve. Median: AI not reached; GD not reached. Survival at 1 years: AI 100%; GD 99%. Hazard ratio AI vs GD 0.39 (95% CI 0.12–1.25).

0%20%40%60%80%100%01234YearsAIGD
ArmNEventsMedian (Years)
AI704not reached
GD7310not reached

Landmark survival (reconstructed)

TimeAIGD
1 yr100.0%98.6%
2 yr94.1%91.5%
3 yr91.4%79.6%

Checks against the published figure

Download pseudo-IPD (CSV)

Progression-free survival

From figure panel b · validated against the values printed on the figure · curve source: pixel measurement confirmed by vision model

Reconstructed from the published curve. Median: AI not reached; GD 4.3 years. Survival at 1 years: AI 91%; GD 79%. Hazard ratio AI vs GD 0.43 (95% CI 0.23–0.82).

0%20%40%60%80%100%01234YearsAIGD
ArmNEventsMedian (Years)
AI7014not reached
GD73294.3

Landmark survival (reconstructed)

TimeAIGD
1 yr91.0%78.6%
2 yr81.7%64.2%
3 yr79.0%59.3%

Checks against the published figure

Download pseudo-IPD (CSV)

About these data

Pseudo-IPD reproduces the published curves and numbers at risk; the rows are not real patients. Cite the publication (DOI above) and TrialCurve. The source figure is © the authors (CC BY 4.0); the charts here are redrawn from the reconstruction.

Load these data in R or Python
# R
library(survival)
d <- read.csv("https://trialcurve.com/data/trials/jcog1306-1.csv")
survfit(Surv(time, event) ~ arm, data = d)
coxph(Surv(time, event) ~ arm, data = d)

# Python
import pandas as pd
from lifelines import KaplanMeierFitter
d = pd.read_csv("https://trialcurve.com/data/trials/jcog1306-1.csv")
for arm, g in d.groupby("arm"):
    KaplanMeierFitter().fit(g.time, g.event, label=arm).plot_survival_function()

Suggested citation: Br J Cancer. 2022 Jul 23;127(8):1487–96. doi: 10.1038/s41416-022-01912-5 doi:10.1038/s41416-022-01912-5. Reconstructed data: TrialCurve (2026), https://trialcurve.com/trials/jcog1306

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