Evidence map›Paper›PMID 40336114›Full record

SynthesisJournal of ovarian research2025

Emerging nanotechnologies and their role in early ovarian cancer detection, diagnosis and interventions.

Mega Obukohwo Oyowvi, Kehinde Henrietta Babawale, Adedeji David Atere, Benneth Ben-Azu

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of ovarian research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mega Obukohwo OyowviDepartment of Physiology, Adeleke University, Ede, Osun State, Nigeria. megalect@gmail.com.
Kehinde Henrietta BabawaleDepartment of Physiology, Adeleke University, Ede, Osun State, Nigeria.
Adedeji David AtereDepartment of Medical Laboratory Science, College of Health Sciences, Osun State University, Osogbo, Nigeria.
Benneth Ben-AzuDELSU Joint Canada-Israel Neuroscience and Biopsychiatry Laboratory, Department of Pharmacology, Delta State University, Abraka, Delta State, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer presents a significant public health challenge, often being diagnosed at advanced stages due to the limitations of current detection methods. This systematic review addresses the urgent need for innovative approaches to enhance early detection and diagnosis of ovarian cancer. We systematically evaluate recent advancements in nanotechnology, focusing specifically on their novel applications and potential in comparison to traditional diagnostic modalities. Our analysis encompasses a wide range of studies investigating nanoparticles, biosensors, advanced imaging techniques, and biomarker detection platforms, with an emphasis on evaluating key performance indicators such as detection rates, turnaround times, and the accuracy of distinguishing cancerous from non-cancerous tissues. Our findings indicate that nanotechnology-based approaches have the potential to significantly improve early detection capabilities for ovarian cancer. Notably, studies on nanoparticle-based imaging techniques and biosensors consistently demonstrate high sensitivity and specificity for identifying ovarian cancer biomarkers, with detection rates exceeding 90% reported for early-stage cancers in several instances. This review underscores the promise of emerging nanotechnologies to transform the landscape of early detection and diagnosis, offering a pathway toward earlier diagnoses, enhanced therapeutic interventions, and improved patient outcomes. We advocate for future research dedicated to the translational efforts required to move these technologies from bench to bedside, ensuring their effectiveness is validated across diverse clinical populations.

Indexed as

Early Detection of CancerNanotechnologyOvarian NeoplasmsBiomarkers, TumorBiosensing TechniquesFemaleHumansBiomarkers, TumorBiomarkersBiosensorsImaging techniquesNanocarriersNanoparticlesOvarian cancer

Identifiers

PMID40336114
PMCPMC12057071

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.