Abstract
Background
A prior study found that, among advanced non-small cell lung cancer (aNSCLC) patients
with PD-L1 expression 50% to 100% receiving immunotherapy as monotherapy, PD-L1 expression
≥ 90% was associated with longer survival. We sought to replicate this finding using
real-world data from community oncology practices across the US.
Methods
Retrospective cohort study of aNSCLC patients who initiated pembrolizumab monotherapy
for first line and had a PD-L1 expression ≥ 50% using a nationwide, deidentified longitudinal
electronic health record–derived real-world database. The exposure of interest was
very high PD-L1 expression, which was defined as ≥ 90%, compared to high PD-L1 expression,
defined as 50% to 89%. The primary outcome was overall survival, measured from initiation
of pembrolizumab to date of death, with censoring at last healthcare encounter. Multiple
imputation was used to impute missing covariates. Propensity score-based inverse probability
weighting (IPW) was used to address confounding in Kaplan-Meier curves and Cox proportional
hazard regression models.
Results
The cohort included 1952 aNSCLC patients receiving first-line pembrolizumab monotherapy.
Half of cohort members were female, median age was 73 years (interquartile range,
65-80), 71% had non-squamous histology, 94% had a history of smoking, and 46% had
very high PD-L1 expression. Median overall survival in the propensity score-weighted
sample was 15.84 months for very high PD-L1 expression and 12.72 months for high PD-L1
expression. Having a very high PD-L1 expression was associated with lower hazard of
mortality (IPW hazard ratio 0.79, 95% CI 0.69-0.91).
Conclusions
In this large national US cohort, patients with very high PD-L1 expression (≥ 90%)
aNSCLC receiving first-line pembrolizumab experienced better median survival than
those with high PD-L1 expression (50% to 89%).
Keywords
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Article info
Publication history
Published online: July 21, 2022
Accepted:
July 16,
2022
Received in revised form:
July 15,
2022
Received:
May 29,
2022
Identification
Copyright
© 2022 Elsevier Inc. All rights reserved.
