Evidence mapPaperPMID 41899562Full record

ReviewCancers2026

Diagnostic Utility of Neutrophil-to-Lymphocyte Ratio in Differentiating Benign and Malignant Ovarian Masses: A Systematic Review.

Patrick Bayu, Patricia Diana Prasetiyo, Jeremiah Hilkiah Wijaya

Abstract readReview
In one paragraph

Review in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Patrick BayuDepartment of Obstetrics and Gynecology Fertility Endocrinology, Faculty of Medicine, Pelita Harapan University, Tangerang 15811, Indonesia.
Patricia Diana PrasetiyoDepartment of Pathology Anatomy, Faculty of Medicine, Pelita Harapan University, Tangerang 15811, Indonesia.
Jeremiah Hilkiah WijayaSchool of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3800, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesGiven its cost-effectiveness and availability, NLR could play a pivotal role in refining the diagnostic process. We aimed to evaluate whether NLR can serve as a useful marker to differentiate between benign and malignant ovarian masses, synthesizing available evidence to provide a comprehensive assessment of its diagnostic value.

methodsA comprehensive search was conducted across the following electronic databases: PubMed, Europe PMC, and SCOPUS on 4 January 2026. For inclusion, studies were required to report on the use of NLR as a biomarker for differentiating ovarian masses, involve human participants with preoperative measurements of these ratios, and provide data on diagnostic accuracy, such as sensitivity, specificity, or receiver operating characteristic (ROC) curves. Both retrospective and prospective observational studies were considered.

resultsThis systematic review incorporated data from 3675 patients across ten studies. The meta-analysis revealed that malignant masses exhibited a significantly elevated mean NLR (HR -0.80 [95% CI: -1.17 to -0.42]), but found no statistically significant correlation (OR 1.49 [95% CI: 0.67 to 3.30]). NLR had moderate diagnostic performance with an AUC of 0.66 (95% CI: 0.62-0.69).

conclusionsWhile malignant ovarian masses are associated with a significantly higher mean NLR, the overall diagnostic performance of NLR remains moderate, suggesting limited utility in distinguishing between benign and malignant tumors.

Indexed as

benign ovarian massesdiagnostic performancemalignant ovarian massesneutrophil-to-lymphocyte ratio

Identifiers

PMID41899562
PMCPMC13024993

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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.