Evidence map›Paper›PMID 29426340›Full record

SynthesisDiagnostic pathology2018

PD-L1 diagnostic tests: a systematic literature review of scoring algorithms and test-validation metrics.

Margarita Udall, Maria Rizzo, Juliet Kenny, Jim Doherty, SueAnn Dahm, Paul Robbins, Eric Faulkner

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Diagnostic pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
106citing papers in PubMed, 5 pooled it
12.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

106 citing papers in PubMed, 5 syntheses or guidelines pooled it, 204 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. "Interchangeability" of PD-L1 immunohistochemistry assays: a meta-analysis of diagnostic accuracy.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2020
    Pooled it
  5. Guideline
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

46 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Margarita UdallPfizer Inc, New York, NY, USA. Margarita.Udall@pfizer.com.
Maria RizzoEvidera, Metro Building, 6th Floor, 1 Butterwick, London, W6 8DL, UK.
Juliet KennyEvidera, Metro Building, 6th Floor, 1 Butterwick, London, W6 8DL, UK.
Jim DohertyPfizer Inc, New York, NY, USA.
SueAnn DahmPfizer Inc, New York, NY, USA.
Paul RobbinsPfizer Inc, New York, NY, USA.
Eric FaulknerEvidera, Metro Building, 6th Floor, 1 Butterwick, London, W6 8DL, UK.
Pfizer (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe programmed death receptor 1 (PD-1) protein is a cell-surface receptor on certain lymphocytes that, with its ligand programmed death ligand 1 (PD-L1), helps to down-regulate immune responses. Many cancer types express PD-L1 and evade immune recognition via the PD-1/PD-L1 interaction. Precision therapies targeting the PD-1/PD-L1 pathway have the potential to improve response and thereby offer a novel treatment avenue to some patients with cancer. However, this new therapeutic approach requires reliable methods for identifying patients whose cancers are particularly likely to respond. Therefore, we conducted a systematic literature review assessing evidence on test validation and scoring algorithms for PD-L1 immunohistochemistry (IHC) tests that might be used to select potentially responsive patients with bladder/urothelial cell, lung, gastric, or ovarian cancers for immunotherapy treatment. METHODS AND

resultsTo identify evidence on commercially available PD-L1 IHC assays, we systematically searched MEDLINE and Embase for relevant studies published between January 2010 and September 2016 and appraised abstracts from recent oncology conferences (January 2013 to November 2016). Publications that met the predefined inclusion criteria were extracted and key trends summarized. In total, 26 eligible primary studies were identified, all of which reported on the test validation metrics associated with PD-L1 IHC tests in lung cancer, most using immunohistochemistry testing. There was significant heterogeneity among the available tests for PD-L1. Specifically, no definitive cutoff for PD-L1 positivity was identifiable, with more than one threshold being reported for most antibodies. Studies also differed as to whether they evaluated tumor cells only or tumor cells and tumor-infiltrating immune cells. However, all of the tests developed and validated to support a therapeutic drug in the context of phase 2-3 clinical trials reported more than 90% inter-reader concordance. In contrast, other PD-L1 antibodies identified in the literature reported poorer concordance.

conclusionsPublished validation metric data for PD-L1 tests are mainly focused on immunohistochemistry tests from studies in lung cancer. The variability in test cutoffs and standards for PD-L1 testing suggests that there is presently no standardized approach. This current variability may have implications for the uptake of precision treatments.

Indexed as

Diagnostic Tests, RoutineAlgorithmsAnimalsAntibodies, MonoclonalB7-H1 AntigenBiomarkers, TumorHumansLung NeoplasmsProgrammed Cell Death 1 ReceptorAntibodies, MonoclonalB7-H1 AntigenBiomarkers, TumorCD274 protein, humanProgrammed Cell Death 1 ReceptorAntibodyCancerDiagnosticImmunotherapyPD-1PD-L1Programmed cell death protein 1Programmed death ligand 1TestTests

Identifiers

PMID29426340
PMCPMC5807740
OpenAlexW2797182287

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.