TrialCurvePIN: reconstructed Kaplan–Meier curves
Olaparib maintenance versus placebo monotherapy in patients with advanced non-small cell lung cancer (PIN): A multicentre, randomised, controlled, phase 2 trial. Curves rebuilt as patient-level data (Guyot 2012) and checked against the statistics printed on the figure.
| Publication | eClinicalMedicine. 2022 Aug 11;52:101595. doi: 10.1016/j.eclinm.2022.101595 |
|---|---|
| DOI | 10.1016/j.eclinm.2022.101595 |
| Registry | NCT01788332 |
| Phase | Phase 2 |
| Conditions | Non-small Cell Lung Cancer |
| Interventions | Olaparib, Placebo |
| Sponsor | Lisette Nixon |
| Enrolment | 70 |
| Source licence | Figure published under CC BY 4.0 |
Overall survival — ITT population
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: Olaparib 59.4 weeks; Placebo 31.2 weeks. Survival at 8 weeks: Olaparib 100%; Placebo 100%. Hazard ratio Olaparib vs Placebo 0.58 (95% CI 0.29–1.12).
| Arm | N | Events | Median (Weeks) |
|---|---|---|---|
| Olaparib | 32 | 14 | 59.4 |
| Placebo | 38 | 23 | 31.2 |
- Olaparib vs Placebo: reconstructed HR 0.58 (95% CI 0.29–1.12)
Landmark survival (reconstructed)
| Time | Olaparib | Placebo |
|---|---|---|
| 4 wk | 100.0% | 100.0% |
| 8 wk | 100.0% | 100.0% |
| 12 wk | 96.3% | 94.0% |
| 26 wk | 86.9% | 73.3% |
| 52 wk | 59.2% | 31.3% |
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/pin-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/pin-1.csv")
for arm, g in d.groupby("arm"):
KaplanMeierFitter().fit(g.time, g.event, label=arm).plot_survival_function()
Suggested citation: eClinicalMedicine. 2022 Aug 11;52:101595. doi: 10.1016/j.eclinm.2022.101595 doi:10.1016/j.eclinm.2022.101595. Reconstructed data: TrialCurve (2026), https://trialcurve.com/trials/pin
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