Evidence map›Paper›PMID 42909193›Full record

ReviewOncology reviews2026

Blood-based inflammatory biomarkers in ovarian cancer: addressing the challenge of early detection, metastasis, and prognostic stratification.

Emmanuel Ifeanyi Obeagu

Abstract readReview
In one paragraph

Review in Oncology reviews, 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

1 author.

Emmanuel Ifeanyi ObeaguDivision of Haematology, Department of Biomedical and Laboratory Science, Africa University, Mutare, Zimbabwe.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer remains a major cause of gynaecological cancer mortality, largely because early disease is frequently asymptomatic and reliable population-based screening remains unavailable. Systemic inflammation is increasingly recognised as an important component of ovarian cancer biology, linking tumour progression, immune dysregulation, angiogenesis, metastasis and treatment resistance. This narrative review critically evaluates blood-based inflammatory biomarkers, including C-reactive protein, interleukin-6, interleukin-8, tumour necrosis factor-α, fibrinogen, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index (SII), systemic inflammation response index (SIRI) and pan-immune-inflammation value (PIV), across early detection, metastatic assessment, treatment decision-making and prognostic stratification. Available evidence indicates that elevated inflammatory indices are consistently associated with advanced disease and adverse outcomes, although substantial heterogeneity exists in biomarker thresholds, populations, timing of measurement and analytical approaches. Recent evidence also suggests that preoperative NLR and SII may contribute to treatment selection, including neoadjuvant chemotherapy, although prognostic independence is not consistently demonstrated. Importantly, inflammatory biomarkers lack sufficient specificity for standalone ovarian cancer screening and should not replace CA-125, HE4, imaging or histopathological assessment. Their greatest clinical potential lies in multimarker models integrating systemic inflammatory, tumour-specific, molecular and clinical variables. Future research should prioritise prospective multicentre validation, standardised thresholds, longitudinal assessment and clinically interpretable prediction models to determine whether inflammatory profiling can advance precision risk stratification and treatment selection in ovarian cancer.

Indexed as

diagnosisinflammatory biomarkersmetastasisovarian cancerprognosis

Identifiers

PMID42909193
PMCPMC13684002

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.