Evidence map›Paper›PMID 38084173›Full record

ReviewCureus2023

A Comprehensive Review of Screening Methods for Ovarian Masses: Towards Earlier Detection.

Shreya A Sahu, Deepti Shrivastava

Open access · diamondAbstract readReview
In one paragraph

Review in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 5 pooled it
8.5field-weighted citation impact, top 2% of its field
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

23 citing papers in PubMed, 5 syntheses or guidelines pooled it, 31 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Shreya A SahuObstetrics and Gynaecology, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Deepti ShrivastavaObstetrics and Gynaecology, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND.
Jawaharlal Nehru Medical College · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian masses, ranging from benign cysts to malignant tumors, present complex diagnostic challenges in women's healthcare. Early detection of ovarian masses is paramount for improving patient outcomes, as delayed diagnoses often lead to advanced-stage disease with limited treatment options. This comprehensive review explores screening methods' current state, limitations, and emerging technologies to facilitate earlier detection. The limitations of existing screening methods, such as low sensitivity and specificity, underscore the need for improved early detection strategies. Imaging-based techniques, including transvaginal ultrasound, magnetic resonance imaging, and computed tomography, are vital in evaluating ovarian masses. However, the emergence of artificial intelligence (AI) and machine learning (ML) applications enhances the accuracy of image interpretation. Blood-based biomarkers, such as CA-125, have been the focus of research for ovarian mass detection. While CA-125 remains widely used, its limitations have prompted investigations into alternative serum biomarkers, including HE4 and miRNA, along with liquid biopsy and circulating tumor DNA. Ultrasound-based scoring systems, such as the risk of malignancy index (RMI), Ovarian-Adnexal Reporting and Data System (O-RADS), and guidelines from the International Ovarian Tumor Analysis (IOTA) group, provide structured approaches for classifying ovarian masses. These systems aid healthcare providers in clinical decision-making. Emerging technologies, such as liquid biopsy, AI, and proteomic/metabolomic approaches, offer promising avenues for enhancing early detection and risk assessment. Liquid biopsy provides noninvasive, real-time monitoring of ovarian masses, while AI and ML applications improve the accuracy of image interpretation. Proteomic and metabolomic studies reveal novel biomarkers and molecular insights. High-risk populations, often associated with genetic mutations such as BRCA1 and BRCA2, require specialized screening strategies. Current guidelines recommend screening modalities, risk-reduction strategies, and shared decision-making. Ongoing research focuses on refining risk assessment and personalized screening for high-risk individuals. This review underscores the importance of early detection in managing ovarian masses, emphasizing the need for improved screening methods, tailored approaches for high-risk populations, and ongoing research to further enhance diagnostic accuracy and patient outcomes.

Indexed as

biomarkersearly detectionemerging technologieshigh-risk populationsovarian massesscreening methods

Identifiers

PMID38084173
PMCPMC10710762
OpenAlexW4388537370

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.