TrialCurveVIM: reconstructed Kaplan–Meier curves
Active symptom control with or without oral vinorelbine in patients with relapsed malignant pleural mesothelioma (VIM): A randomised, phase 2 trial. Curves rebuilt as patient-level data (Guyot 2012) and checked against the statistics printed on the figure.
| Publication | eClinicalMedicine. 2022 May 19;48:101432. doi: 10.1016/j.eclinm.2022.101432 |
|---|---|
| DOI | 10.1016/j.eclinm.2022.101432 |
| Registry | NCT02139904 |
| Phase | Phase 2 |
| Conditions | Mesothelioma |
| Interventions | Vinorelbine, Active Symptom Control |
| Sponsor | Wales Cancer Trials Unit |
| Enrolment | 154 |
| Source licence | Figure published under CC BY 4.0 |
Progression-free survival
From figure panel A · curves cross-checked by two independent readings · curve source: pixel measurement confirmed by vision model
Reconstructed from the published curve. Median: ASC+Vin 4.1 months; ASC 2.8 months. Survival at 6 months: ASC+Vin 33%; ASC 9%. Hazard ratio ASC+Vin vs ASC 0.58 (95% CI 0.40–0.83).
| Arm | N | Events | Median (Months) |
|---|---|---|---|
| ASC+Vin | 98 | 82 | 4.1 |
| ASC | 56 | 48 | 2.8 |
- ASC+Vin vs ASC: reconstructed HR 0.58 (95% CI 0.40–0.83)
Landmark survival (reconstructed)
| Time | ASC+Vin | ASC |
|---|---|---|
| 6 mo | 33.3% | 8.6% |
| 12 mo | 11.4% | 6.5% |
| 18 mo | 4.3% | 6.5% |
Overall survival
From figure panel B · curves cross-checked by two independent readings · curve source: pixel measurement confirmed by vision model
Reconstructed from the published curve. Median: ASC+Vin 10.0 months; ASC 9.0 months. Survival at 6 months: ASC+Vin 66%; ASC 63%. Hazard ratio ASC+Vin vs ASC 0.83 (95% CI 0.55–1.25).
| Arm | N | Events | Median (Months) |
|---|---|---|---|
| ASC+Vin | 98 | 64 | 10.0 |
| ASC | 56 | 35 | 9.0 |
- ASC+Vin vs ASC: reconstructed HR 0.83 (95% CI 0.55–1.25)
Landmark survival (reconstructed)
| Time | ASC+Vin | ASC |
|---|---|---|
| 6 mo | 66.5% | 62.5% |
| 12 mo | 39.1% | 40.0% |
| 18 mo | 24.6% | 24.9% |
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/vim-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/vim-1.csv")
for arm, g in d.groupby("arm"):
KaplanMeierFitter().fit(g.time, g.event, label=arm).plot_survival_function()
Suggested citation: eClinicalMedicine. 2022 May 19;48:101432. doi: 10.1016/j.eclinm.2022.101432 doi:10.1016/j.eclinm.2022.101432. Reconstructed data: TrialCurve (2026), https://trialcurve.com/trials/vim
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