ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2026
PD-L1 expression scoring using artificial intelligence algorithms in non-small cell lung cancer harbouring ROS1 fusions: potential clinical-biological significance.
Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
backgroundPD-L1 expression in ROS1-positive non-small cell lung carcinoma (NSCLC) patients remains unclear regarding its possible clinical-biological role.
methodsA retrospective, descriptive study of 24 ROS1-positive NSCLC patients (2013-2023) from five Spanish hospitals were evaluated. Manual (clone SP263) PD-L1 tumour proportion score (TPS) was also subjected to two artificial intelligence (AI) testing algorithms. Clinical and molecular data categorized according to PD-L1 levels by double independent review, were retrospectively collected and, potential correlations were analysed.
resultsThe median age was 60 years (46-85), female (54.1%), adenocarcinoma (87.5%), and former/never smokers (83.3%). Predominant ROS1 fusion partner (FP) was CD74 (41.6%). Most patients (79.1%) received crizotinib at some point during their treatment. PDL1 TPS 1-49% (41.7%), ≥ 50% (33.3%), and < 1% (25%). Statistically significant association between the ROS1 FP category and PD-L1 TPS ≥ 50% (p = 0.008), specifically with EZR (mean manual TPS: 62.1) was found. No statistically significant associations for clinical categorical variables and PD-L1 TPS were observed. Although no significant difference among PD-L1 TPS categories in terms of overall survival was detected (p = 0.36), a shorter overall survival was noted in patients with TPS ≥ 50% and EZR. No significant differences were found between the manual PD-L1 TPS evaluation and the use of PD-L1-based AI algorithms.
conclusionsPD-L1 expression may have a biological significance in ROS1-positive NSCLC, particularly when associated with the EZR FP and PD-L1 TPS ≥ 50% which determines a lower overall survival. No significant differences were found between manual PD-L1 TPS evaluation and the use of AI.
Indexed as
Identifiers
40790287What OpenQuestion holds
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.