ReviewOncoTargets and therapy2023
Minimal Residual Disease Monitoring in Radically Treated Non-Small Cell Lung Cancer: Challenges and Future Directions.
Review in OncoTargets and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed.
- Monitoring treatment response using an ultra-sensitive ctDNA assay in advanced esophagogastric cancer patients.Scientific reports · 2026Trial
- Molecular Residual Disease in Non-Small Cell Lung Cancer: Technology or Patient Outcomes?Journal of personalized medicine · 2026Review
- Targeting rare oncogenic mutations in resectable non-small cell lung cancer: emerging perioperative strategies.Journal of thoracic disease · 2026Review
- ctDNA-based detection of residual disease: implications for management of non-metastatic NSCLC.Frontiers in oncology · 2026Review
- A comprehensive overview of minimal residual disease in the management of early-stage and locally advanced non-small cell lung cancer.NPJ precision oncology · 2025Article
- A scoping review of factors influencing the implementation of liquid biopsy for cancer care.Journal of experimental & clinical cancer research : CR · 2025Article
- Ultra-sensitive, tumor-informed ctDNA profiling in pembrolizumab-treated esophagogastric cancer patients predicts clinical responses.Research square · 2024Article
- Confirmation of Recurrent Lung Cancer Following Resection Using Liquid Biopsy, a Proof-of-Concept Real-World Study.Current oncology (Toronto, Ont.) · 2024Article
- Technical Advances in Circulating Cell-Free DNA Detection and Analysis for Personalized Medicine in Patients' Care.Biomolecules · 2024Review
- Liquid Biopsy in Lung Cancer: Biomarkers for the Management of Recurrence and Metastasis.International journal of molecular sciences · 2023Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Circulating tumor DNA (ctDNA) analysis can identify patients with residual disease before it is clinically or radiologically evident. Minimal residual disease (MRD) is an advancing area in the management of radically treated solid tumors. Which MRD assay is optimum and when it should be used is still not defined. Whilst promising, the clinical utility of this technology to guide patient care is still investigational in non-small cell lung cancer (NSCLC) and has not entered routine care. Once technically and clinically optimized, MRD may be utilized to personalize adjuvant therapy, detect disease relapse earlier and improve cure rates. In this review, we discuss the current status of MRD monitoring in NSCLC by summarizing frequently used MRD assays and their associated evidence in NSCLC. We discuss the potential applications of these technologies and the challenge of demonstrating MRD clinical utility in trials.
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.