Comparison of PD-L1 expression between biopsy specimens and surgical resection specimens in non-small cell lung cancer: a meta-analysis.

Clin Transl OncolMay 24, 2026 (epub)

Ruijie Zhou, Huizhen Yang, Felix J F Herth et al.

✦ AI-curated · Sources linked

In 30 seconds

This meta-analysis compared PD-L1 positivity in biopsy and surgical resection specimens from patients with non-small cell lung cancer, drawing on 13 studies involving 966 patients. At the 1% cutoff, positivity rates did not differ significantly (RR = 0.85, 95% CI [0.71 - 1.01], P = 0.07). At the 50% cutoff, a significant difference was found (RR = 0.76, 95% CI [0.65 - 0.90], P < 0.01). Similar findings were reported among patients without neoadjuvant therapy; the abstract does not specify which specimen type had higher positivity.

Key findings

  • At the 1% cutoff, biopsy and surgical specimens showed no significant difference in PD-L1 positivity (RR = 0.85, 95% CI [0.71 - 1.01], P = 0.07).
  • At the 50% cutoff, PD-L1 positivity differed significantly between specimen types (RR = 0.76, 95% CI [0.65 - 0.90], P < 0.01).
  • Similar cutoff-related findings were observed in patients without neoadjuvant therapy.
  • SP142 showed significantly lower tumor-cell PD-L1 expression than other antibodies at both the 1 and 50% cutoffs.

Why it matters

PD-L1 results can inform assessment of NSCLC, and this analysis indicates that measured positivity may depend on specimen type, particularly at the 50% cutoff. Differences between immunohistochemistry assays may also affect classification. Awareness of these sources of variation helps clinicians interpret PD-L1 results in the context of how the sample was obtained and tested.

What to keep in mind

The meta-analysis combined 13 studies; the abstract does not report their individual designs or provide details on between-study heterogeneity.

Source

Published in Clin Transl Oncol. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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AI-generated summaries may contain errors or omissions. Verify clinically important information with the original publication.

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