TrialCurveAGILE (long-term follow-up): reconstructed Kaplan–Meier curves
Long-term results from the AGILE study of azacitidine plus ivosidenib vs placebo in newly diagnosed IDH1-mutated AML. Curves rebuilt as patient-level data (Guyot 2012) and checked against the statistics printed on the figure.
| Publication | Blood Adv. 2025 Jul 28;9(20):5177–89. doi: 10.1182/bloodadvances.2025016399 |
|---|---|
| DOI | 10.1182/bloodadvances.2025016399 |
| Registry | NCT03173248 |
| Phase | Phase 3 |
| Conditions | Newly Diagnosed Acute Myeloid Leukemia (AML), Untreated AML, AML Arising From Myelodysplastic Syndrome (MDS), Leukemia, Myeloid, Acute |
| Interventions | AG-120, Placebo, Azacitidine |
| Sponsor | Institut de Recherches Internationales Servier |
| Enrolment | 146 |
| Source licence | Figure published under CC BY 4.0 |
Overall survival — ITT population
From figure panel A · validated against the values printed on the figure · curve source: vision model
Reconstructed from the published curve. Median: Ivosidenib + azacitidine 29.3 months; Placebo + azacitidine 8.0 months. Survival at 18 months: Ivosidenib + azacitidine 58%; Placebo + azacitidine 29%. Hazard ratio Ivosidenib + azacitidine vs Placebo + azacitidine 0.43 (95% CI 0.28–0.65).
| Arm | N | Events | Median (Months) |
|---|---|---|---|
| Ivosidenib + azacitidine | 73 | 37 | 29.3 |
| Placebo + azacitidine | 75 | 58 | 8.0 |
- Ivosidenib + azacitidine vs Placebo + azacitidine: reconstructed HR 0.43 (95% CI 0.28–0.65)
Landmark survival (reconstructed)
| Time | Ivosidenib + azacitidine | Placebo + azacitidine |
|---|---|---|
| 6 mo | 73.1% | 53.6% |
| 12 mo | 62.9% | 38.5% |
| 18 mo | 58.3% | 29.3% |
| 24 mo | 54.9% | 17.6% |
| 36 mo | 41.0% | 12.1% |
| 48 mo | 35.9% | — |
Checks against the published figure
- Ivosidenib + azacitidine median: printed 29.3, reconstructed 29.3 pass
- Placebo + azacitidine median: printed 7.9, reconstructed 7.95 pass
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/agile-long-term-follow-up-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/agile-long-term-follow-up-1.csv")
for arm, g in d.groupby("arm"):
KaplanMeierFitter().fit(g.time, g.event, label=arm).plot_survival_function()
Suggested citation: Blood Adv. 2025 Jul 28;9(20):5177–89. doi: 10.1182/bloodadvances.2025016399 doi:10.1182/bloodadvances.2025016399. Reconstructed data: TrialCurve (2026), https://trialcurve.com/trials/agile-long-term-follow-up
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