TrialCurveHIPECT4 (final analysis): reconstructed Kaplan–Meier curves
Efficacy and safety of intraoperative hyperthermic intraperitoneal chemotherapy for locally advanced colorectal cancer (HIPECT4): final analysis of randomized clinical trial. Curves rebuilt as patient-level data (Guyot 2012) and checked against the statistics printed on the figure.
| Publication | BJS Open. 2026 Mar 27;10(2):zrag002. doi: 10.1093/bjsopen/zrag002 |
|---|---|
| DOI | 10.1093/bjsopen/zrag002 |
| Registry | NCT02614534 |
| Phase | Phase 3 |
| Conditions | Colorectal Cancer |
| Interventions | MITOMYCIN-C 30 mg, Proactive cytoreductive surgery |
| Sponsor | Maimónides Biomedical Research Institute of Córdoba |
| Enrolment | 200 |
| Source licence | Figure published under CC BY 4.0 |
Locoregional control
From figure panel · curves cross-checked by two independent readings · curve source: pixel measurement confirmed by vision model
Reconstructed from the published curve. Median: HIPEC not reached; Surgery only not reached. Survival at 12 months: HIPEC 100%; Surgery only 95%. Hazard ratio HIPEC vs Surgery only 0.19 (95% CI 0.04–0.86).
| Arm | N | Events | Median (Months) |
|---|---|---|---|
| HIPEC | 89 | 2 | not reached |
| Surgery only | 95 | 11 | not reached |
- HIPEC vs Surgery only: reconstructed HR 0.19 (95% CI 0.04–0.86)
Landmark survival (reconstructed)
| Time | HIPEC | Surgery only |
|---|---|---|
| 6 mo | 100.0% | 96.8% |
| 12 mo | 100.0% | 94.7% |
| 18 mo | 97.5% | 92.4% |
| 24 mo | 97.5% | 90.1% |
Checks against the published figure
- Surgery only events: printed 11, reconstructed 11 pass
- Surgery only n: printed 95, reconstructed 95 pass
- HIPEC events: printed 2, reconstructed 2 pass
- HIPEC n: printed 89, reconstructed 89 pass
Overall 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: Surgery only not reached; HIPEC not reached. Survival at 12 months: Surgery only 95%; HIPEC 94%. Hazard ratio Surgery only vs HIPEC 0.92 (95% CI 0.38–2.21).
| Arm | N | Events | Median (Months) |
|---|---|---|---|
| Surgery only | 95 | 10 | not reached |
| HIPEC | 89 | 10 | not reached |
- Surgery only vs HIPEC: reconstructed HR 0.92 (95% CI 0.38–2.21)
Landmark survival (reconstructed)
| Time | Surgery only | HIPEC |
|---|---|---|
| 6 mo | 94.7% | 96.6% |
| 12 mo | 94.7% | 94.4% |
| 18 mo | 92.6% | 93.2% |
| 24 mo | 91.5% | 88.4% |
Checks against the published figure
- Surgery only events: printed 10, reconstructed 10 pass
- Surgery only n: printed 95, reconstructed 95 pass
- HIPEC events: printed 10, reconstructed 10 pass
- HIPEC n: printed 89, reconstructed 89 pass
Disease-free 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: HIPEC not reached; Surgery only not reached. Survival at 12 months: HIPEC 91%; Surgery only 84%. Hazard ratio HIPEC vs Surgery only 0.76 (95% CI 0.41–1.39).
| Arm | N | Events | Median (Months) |
|---|---|---|---|
| HIPEC | 89 | 18 | not reached |
| Surgery only | 95 | 25 | not reached |
- HIPEC vs Surgery only: reconstructed HR 0.76 (95% CI 0.41–1.39)
Landmark survival (reconstructed)
| Time | HIPEC | Surgery only |
|---|---|---|
| 6 mo | 95.5% | 90.5% |
| 12 mo | 91.0% | 84.2% |
| 18 mo | 87.5% | 83.1% |
| 24 mo | 81.4% | 77.8% |
Checks against the published figure
- Surgery only events: printed 25, reconstructed 25 pass
- Surgery only n: printed 95, reconstructed 95 pass
- HIPEC events: printed 18, reconstructed 18 pass
- HIPEC n: printed 89, reconstructed 89 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/hipect4-final-analysis-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/hipect4-final-analysis-1.csv")
for arm, g in d.groupby("arm"):
KaplanMeierFitter().fit(g.time, g.event, label=arm).plot_survival_function()
Suggested citation: BJS Open. 2026 Mar 27;10(2):zrag002. doi: 10.1093/bjsopen/zrag002 doi:10.1093/bjsopen/zrag002. Reconstructed data: TrialCurve (2026), https://trialcurve.com/trials/hipect4-final-analysis
Report a problem with these data
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