SynthesisThoracic cancer2020
Predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography for PD-L1 expression in non-small cell lung cancer: A systematic review and meta-analysis.
Synthesis in Thoracic cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Predictive value of machine learning for PD-L1 expression in NSCLC: a systematic review and meta-analysis.World journal of surgical oncology · 2025Pooled it
- Prognostic Role ofCancers · 2026Article
- Tumor Characterization Using [Pharmaceuticals (Basel, Switzerland) · 2026Article
- Article
- Deep learning-based image analysis predicts PD-L1 status fromFrontiers in oncology · 2024Article
- Sensitivity and specificity of amide proton transfer-weighted imaging for assessing programmed death-ligand 1 status in non-small cell lung cancer: a comparative study with intravoxel incoherent motion andQuantitative imaging in medicine and surgery · 2022Article
- Combined SUVmax and localized colonic wall thickening parameters to identify high-risk lesions from incidental focal colorectalFrontiers in oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe purpose of the current study was to investigate the predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for programmed death ligand 1 (PD-L1) in non-small cell lung cancer (NSCLC) patients through a systematic review and meta-analysis.
methodsThe PubMed, Cochrane, and EMBASE database, from the earliest available date of indexing through 30 April 2020, were searched for studies evaluating the diagnostic performance of 18F-FDG PET/CT for prediction of PD-L1 expression in NSCLC patients.
resultsAcross six studies (1739 patients), the pooled sensitivity for 18F-FDG PET/CT was 0.72 (95% CI: 0.58-0.82) with heterogeneity (I
conclusionsThe current meta-analysis showed a moderate sensitivity and specificity of 18F-FDG PET/CT for the prediction of PD-L1 expression in NSCLC patients. The DOR was low and the likelihood ratio scatter-gram indicated that 18F-FDG PET/CT might not be useful for the prediction of PD-L1 expression in NSCLC patients and not for its exclusion. KEY POINTS: Significant findings of the study The current meta-analysis showed a moderate sensitivity and specificity of 18F-FDG PET/CT for the prediction of PD-L1 expression in NSCLC patients. The DOR was low and the likelihood ratio scattergram indicated that 18F-FDG PET/CT might not be useful for the prediction of PD-L1 expression in NSCLC patients and not for its exclusion. What this study adds This study concluded that the role of 18F-FDG PET/CT in predicting tumor expression of PD-L1 should be further elucidated.
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Registered trials
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.