ArticleScientific reports2025
Integrated machine learning survival framework for consensus modeling in a large multicenter cohort of NSCLC resistant to aumolertinib.
Article in Scientific reports, 2025. 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
9 authors.
Funding
Abstract
Patients with advanced non-small cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations often benefit from third-generation tyrosine kinase inhibitors (TKIs), such as aumolertinib (AUM). However, the development of drug resistance significantly limits the clinical efficacy of AUM. To address this, we established an in vitro model of AUM-resistant cell lines and performed RNA sequencing to identify resistance-associated differentially expressed genes. Using machine learning, we constructed an AUM resistance-related prognostic signature (ARRPS). Our results demonstrated that ARRPS effectively predicts the prognostic risk of patients. Notably, for patients with high ARRPS scores, the addition of CD-437 or TPCA-1 to conventional AUM treatment may help overcome drug resistance. These findings suggest that ARRPS serves as both a prognostic tool and a guide for personalized treatment strategies, potentially optimizing the clinical management of NSCLC patients.
Indexed as
Identifiers
What 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.