ReviewNanoscale advances2021
Recent advances in biosensing approaches for point-of-care breast cancer diagnostics: challenges and future prospects.
Review in Nanoscale advances, 2021. 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.
- Shining the Path of Precision Diagnostic: Advancements in Photonic Sensors for Liquid Biopsy.Biosensors · 2025Review
- Innovative Methodologies for the Early Detection of Breast Cancer: A Review Categorized by Target Biological Samples.Biosensors · 2025Review
- Article
- A versatile gold leaf immunosensor with a novel surface functionalization strategy based on protein L and trastuzumab for HER2 detection.Scientific reports · 2025Article
- Article
- Exploring Radioiodinated Anastrozole and Epirubicin as AKT1-Targeted Radiopharmaceuticals in Breast Cancer: In Silico Analysis and Potential Therapeutic Effect with Functional Nuclear Imagining Implications.Molecules (Basel, Switzerland) · 2024Article
- Cytoplasmic viscosity is a potential biomarker for metastatic breast cancer cells.Nanoscale advances · 2024Article
- A review on hybridization of plasmonic and photonic crystal biosensors for effective cancer cell diagnosis.Nanoscale advances · 2023Review
- Recent advances in lab-on-a-chip systems for breast cancer metastasis research.Nanoscale advances · 2023Review
- Liquid crystal-assisted optical biosensor for early-stage diagnosis of mammary glands using HER-2.Scientific reports · 2023Article
- Bi-ECDAQ: An electrochemical dual-immuno-biosensor accompanied by a customized bi-potentiostat for clinical detection of SARS-CoV-2 Nucleocapsid proteins.Biosensors & bioelectronics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Timely and accurate diagnosis of breast cancer is essential for efficient treatment and the best possible survival rates. Biosensors have emerged as a smart diagnostic platform for the detection of biomarkers specific to the onset, recurrence, and therapeutic drug monitoring of breast cancer. There have been exciting recent developments, including significant improvements in the validation, sensitivity, specificity, and integration of sample processing steps to develop point-of-care (POC) integrated micro-total analysis systems for clinical settings. The present review highlights various biosensing modalities (electrical, optical, piezoelectric, mass, and acoustic sensing). It provides deep insights into their design principles, signal amplification strategies, and comparative performance analysis. Finally, this review emphasizes the status of existing integrated micro-total analysis systems (μ-TAS) for personalized breast cancer therapeutics and associated challenges and outlines the approach required to realize their successful translation into clinical settings.
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.