ReviewHeliyon2024
Point-of-care testing for early-stage liver cancer diagnosis and personalized medicine: Biomarkers, current technologies and perspectives.
Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Advances in fluorescence-based point-of-care diagnostics: probes, nanostructures and integrated systems.Journal of materials chemistry. C · 2026Review
- Clinical applications and future perspectives of circulating tumor cells in solid tumors.Discover oncology · 2026Review
- Machine Learning for Individual EV Classification Based on Highly Sensitive Multiplexed Mass Spectrometry Measurements.Journal of the American Society for Mass Spectrometry · 2026Article
- Near-Infrared Fluorescent Probes Targeting LAG-3 for Guiding Immunomodulation and Efficacy Monitoring of Stereotactic Body Radiotherapy in Liver Cancer.Journal of hepatocellular carcinoma · 2026Article
- The Application of Nanomaterials in the Detection of Liver Cancer Biomarkers.International journal of nanomedicine · 2026Review
- Nanotechnology-Enabled Diagnosis and Treatment of Hepatocellular Carcinoma: Theranostics, Combination Regimens, and Translation.International journal of nanomedicine · 2026Review
- Liver Cancer: Artificial Intelligence (AI)-Based Integrated Therapeutic Approaches.Bioengineering (Basel, Switzerland) · 2025Article
- Plasmonic Biosensors in Cancer-Associated miRNA Detection.Biosensors · 2025Review
- Polymerase Chain Reaction Chips for Biomarker Discovery and Validation in Drug Development.Micromachines · 2025Review
- Non-coding RNAs as key regulators in hepatitis B virus-related hepatocellular carcinoma.Frontiers in immunology · 2025Review
- Single-Gene Mutations in Hepatocellular Carcinoma: Applications and Challenges in Precision Medicine.International journal of medical sciences · 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
Liver cancer is a highly prevalent and lethal form of cancer worldwide. In the absence of early diagnosis, treatment options for this disease are severely restricted. Recent advancements in genomics and bioinformatics have facilitated the discovery of a multitude of novel biomarkers that accurately depict an individual's disease diagnosis, progression, and treatment response. Leveraging these breakthroughs, personalized medicine employs an individual's biomarker profile to enable early detection of liver cancer and inform decisions regarding treatment selection, dosage determination, and prognosis assessment. The current lack of readily applicable, timely, and economically viable tools for biomarker analysis has hindered the incorporation of personalized medicine into regular clinical procedures. Over the past decade, significant advancements have been achieved in the field of molecular point-of-care testing (POCT) and amplification techniques, leading to substantial improvements in the diagnosis of liver cancer and the implementation of precision medicine. Instrument-free PCR technology or plasma PCR technology can shorten the complex procedure of in vitro detection of nucleic acid-based biomarkers. Also, compared to traditional ELISA, various nanomaterials modified with monoclonal antibodies to target proteins for recognition, capture, and detection have improved the efficiency of protein-based biomarker detection. These advances have reduced the time and cost of clinical detection of early-stage hepatocellular carcinoma and improved the efficiency of timely diagnosis and survival of suspected patients while reducing unnecessary testing costs and procedures. This review aims to provide a comprehensive overview of the current and emerging biomarkers employed in the early detection of liver cancer, as well as the advancements in point-of-care molecular testing technology and platforms. The primary objective is to assess their potential in facilitating the implementation of personalized medicine. This review ultimately revealed that the diagnosis of early-stage hepatocellular carcinoma not only requires sensitive biomarkers, but its various modifications and changes during the progression of cirrhosis to early-stage hepatocellular carcinoma will be a greater focus of our attention in the future. The rapid development of POCT has facilitated the opportunity to readily detect liver cancer in the general population in the future, and the integration of multi-pathway multiplexing and intelligent algorithms has improved the sensitivity and accuracy of early liver cancer biomarker detection. It is expected that the integration of point-of-care technology will be instrumental in the widespread adoption of personalized medicine in the foreseeable future.
Indexed as
Identifiers
What Socratic 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 Socratic graph.