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Why PD-L1 expression varies between studies of lung cancer: results from a bayesian meta-analysis

  • Preston Ngo
  • , Wendy A. Cooper
  • , Stephen Wade
  • , Kwun M. Fong
  • , Karen Canfell
  • , Deme Karikios
  • , Marianne Weber
    • University of Sydney
    • Royal Prince Alfred Hospital
    • University of Queensland
    • Prince Charles Hospital
    • Nepean Hospital

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)
    25 Downloads (Pure)

    Abstract

    PD-L1 expression is an important biomarker for the management of non-small cell lung cancer (NSCLC) but has been highly heterogeneous across studies. We developed a statistical model to reconcile conflicting estimates of PD-L1 prevalence by accounting for between-study variation in test sensitivity, specimen age, and laboratory count. In doing so, we obtained refined estimates for PD-L1 expression prevalence and identified differences by histological subtype, mutational status, and stage. Across 92 studies published between 2015 and 2023, the detectability of PD-L1 declined with increasing specimen age while the consistency of detection rates was greater for studies incorporating data from a higher number of laboratories. Using the 22C3 antibody as a benchmark, we predicted that 58.3% (95% CrI 49.8–66.1%) and 27.0% (95% CrI 21.2–33.1%) of NSCLC will have PD-L1 tumour proportion scores at the ≥ 1% and ≥ 50% threshold. PD-L1 expression was lower in EGFR-mutated NSCLC and higher in NSCLC with ALK, KRAS, MET, ROS1, and RET alterations. PD-L1 expression was more common with later-stage disease. Overall, this work highlights the continuing challenge of consistency in PD-L1 testing. Although the underlying prevalence of PD-L1 expression varies in the lung cancer population based on tumour-related factors, controllable differences in testing parameters also account for variations in PD-L1 prevalence.
    Original languageEnglish
    Article number4166
    Number of pages10
    JournalScientific Reports
    Volume15
    Issue number1
    DOIs
    Publication statusPublished - Feb 2025

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Biomarkers
    • Immunohistochemistry
    • Immunotherapy
    • Non-small cell lung cancer
    • PD-L1

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