ArticleWorld journal of clinical oncology2024
Leveraging electrochemical sensors to improve efficiency of cancer detection.
Article in World journal of clinical oncology, 2024. 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.
- Molecular Biomarkers of Radiosensitivity and Radioresistance in Cervical Cancer: A Systematic Review.International journal of molecular sciences · 2026Pooled it
- Electrochemical Biosensors for Circulating Tumor Cells and ctDNA: Emerging Strategies for Precision Oncology.Annals of biomedical engineering · 2026Review
- Electrochemical Detection of Cancer Biomarkers: From Molecular Sensing to Clinical Translation.Biosensors · 2026Review
- In Search of Ideal Solutions for Cancer Diagnosis: From Conventional Methods to Protein Biomarkers in Liquid Biopsy.Proteomes · 2025Review
- Applications of Nanoparticles in the Diagnosis and Treatment of Ovarian Cancer.Nanomaterials (Basel, Switzerland) · 2025Review
- Fundamentals and research progression on electrochemical sensing of colorectal cancer.Mikrochimica acta · 2025Review
- Current Research in Drug-Free Cancer Therapies.Bioengineering (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electrochemical biosensors have emerged as a promising technology for cancer detection due to their high sensitivity, rapid response, low cost, and capability for non-invasive detection. Recent advances in nanomaterials like nanoparticles, graphene, and nanowires have enhanced sensor performance to allow for cancer biomarker detection, like circulating tumor cells, nucleic acids, proteins and metabolites, at ultra-low concentrations. However, several challenges need to be addressed before electrochemical biosensors can be clinically implemented. These include improving sensor selectivity in complex biological media, device miniaturization for implantable applications, integration with data analytics, handling biomarker variability, and navigating regulatory approval. This editorial critically examines the prospects of electrochemical biosensors for efficient, low-cost and minimally invasive cancer screening. We discuss recent developments in nanotechnology, microfabrication, electronics integration, multiplexing, and machine learning that can help realize the potential of these sensors. However, significant interdisciplinary efforts among researchers, clinicians, regulators and the healthcare industry are still needed to tackle limitations in selectivity, size constraints, data interpretation, biomarker validation, toxicity and commercial translation. With committed resources and pragmatic strategies, electrochemical biosensors could enable routine early cancer detection and dramatically reduce the global cancer burden.
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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.