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KEYNOTE-042 China (5-year update): reconstructed Kaplan–Meier curves

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

Five-year outcomes of pembrolizumab versus chemotherapy in Chinese patients with non-small-cell lung cancer and programmed cell death ligand 1 tumor proportion score ≥1%: KEYNOTE-042 China study. Curves rebuilt as patient-level data (Guyot 2012) and checked against the statistics printed on the figure.

PublicationInt J Cancer. 2025 Dec 31;158(9):2429–39. doi: 10.1002/ijc.70265
DOI10.1002/ijc.70265
RegistryNCT03850444
PhasePhase 3
ConditionsNon-small Cell Lung Cancer
Interventionspembrolizumab, carboplatin, paclitaxel, pemetrexed
SponsorMerck Sharp & Dohme LLC
Enrolment262
Source licenceFigure published under CC BY 4.0

Overall survival — PD-L1 TPS >=50%

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: Pembrolizumab 23.9 months; Chemotherapy 13.4 months. Survival at 18 months: Pembrolizumab 61%; Chemotherapy 39%. Hazard ratio Pembrolizumab vs Chemotherapy 0.65 (95% CI 0.45–0.92).

0%20%40%60%80%100%01224364860MonthsPembrolizumabChemotherapy
ArmNEventsMedian (Months)
Pembrolizumab725823.9
Chemotherapy746713.4

Landmark survival (reconstructed)

TimePembrolizumabChemotherapy
6 mo81.9%83.8%
12 mo70.8%55.4%
18 mo61.1%39.2%
24 mo50.0%29.7%
36 mo33.3%18.4%
48 mo24.7%15.5%
60 mo18.0%8.2%

Checks against the published figure

Download pseudo-IPD (CSV)

Overall survival — PD-L1 TPS >=20%

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: Pembrolizumab 21.8 months; Chemotherapy 13.4 months. Survival at 18 months: Pembrolizumab 58%; Chemotherapy 39%. Hazard ratio Pembrolizumab vs Chemotherapy 0.68 (95% CI 0.50–0.92).

0%20%40%60%80%100%01224364860MonthsPembrolizumabChemotherapy
ArmNEventsMedian (Months)
Pembrolizumab1018021.8
Chemotherapy1039013.4

Landmark survival (reconstructed)

TimePembrolizumabChemotherapy
6 mo81.2%84.3%
12 mo69.2%53.5%
18 mo58.2%38.7%
24 mo46.1%28.7%
36 mo30.1%17.4%
48 mo23.0%15.4%
60 mo19.4%10.2%

Checks against the published figure

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Overall survival — PD-L1 TPS >=1%

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

Reconstructed from the published curve. Median: Pembrolizumab 20.3 months; Chemotherapy 13.5 months. Survival at 18 months: Pembrolizumab 57%; Chemotherapy 41%. Hazard ratio Pembrolizumab vs Chemotherapy 0.68 (95% CI 0.52–0.89).

0%20%40%60%80%100%01224364860MonthsPembrolizumabChemotherapy
ArmNEventsMedian (Months)
Pembrolizumab12810220.3
Chemotherapy13411713.5

Landmark survival (reconstructed)

TimePembrolizumabChemotherapy
6 mo80.4%82.6%
12 mo68.5%52.8%
18 mo56.7%40.5%
24 mo44.1%27.5%
36 mo28.4%16.2%
48 mo22.1%13.0%
60 mo19.0%9.6%

Checks against the published figure

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Overall survival — PD-L1 TPS 1%-49%

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

Reconstructed from the published curve. Median: Pembrolizumab 19.0 months; Chemotherapy 10.4 months. Survival at 18 months: Pembrolizumab 52%; Chemotherapy 41%. Hazard ratio Pembrolizumab vs Chemotherapy 0.74 (95% CI 0.49–1.12).

0%20%40%60%80%100%01224364860MonthsPembrolizumabChemotherapy
ArmNEventsMedian (Months)
Pembrolizumab564319.0
Chemotherapy604910.4

Landmark survival (reconstructed)

TimePembrolizumabChemotherapy
6 mo79.9%82.7%
12 mo66.9%48.5%
18 mo52.0%41.3%
24 mo37.2%26.7%
36 mo20.4%13.4%
48 mo20.4%11.5%
60 mo20.4%11.5%

Checks against the published figure

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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/keynote-042-china-5-year-update-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/keynote-042-china-5-year-update-1.csv")
for arm, g in d.groupby("arm"):
    KaplanMeierFitter().fit(g.time, g.event, label=arm).plot_survival_function()

Suggested citation: Int J Cancer. 2025 Dec 31;158(9):2429–39. doi: 10.1002/ijc.70265 doi:10.1002/ijc.70265. Reconstructed data: TrialCurve (2026), https://trialcurve.com/trials/keynote-042-china-5-year-update

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